{
  "version": 2,
  "entries": [
    {
      "topic": "About Alex",
      "context": "both",
      "content": "Alex Kyoungmoon Lee is an Industrial Engineering student at Purdue University specializing in operations research, stochastic modeling, and simulation. He builds creative tech under the Kyouza studio, collects mechanical pencils, plays Terraria, and generates slimes. His tech stack spans Python, TypeScript, R, SQL, and Gurobi.",
      "keywords": [
        "alex",
        "about",
        "bio",
        "background",
        "who",
        "person",
        "introduction",
        "profile"
      ],
      "source": "knowledge"
    },
    {
      "topic": "This Website",
      "context": "both",
      "content": "This portfolio is a dual-personality site built with Astro 5.3 and Svelte 5. The professional side is minimal and data-driven. The play side is a retro CRT arcade with a stickman hub, collectible secrets, a slime lab, and an RNG blob. No external AI -- the chatbot runs entirely client-side with keyword matching. Built from scratch by Alex.",
      "keywords": [
        "website",
        "site",
        "portfolio",
        "astro",
        "svelte",
        "how",
        "built",
        "tech stack",
        "architecture",
        "frontend"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Collecting",
      "context": "play",
      "content": "Collects mechanical pencils (Rotring 800 is the crown jewel), retro handhelds, movie memorabilia, and enamel pins. Every item has a story and a rarity tier from common to legendary.",
      "keywords": [
        "collecting",
        "mechanical pencils",
        "Rotring",
        "handhelds",
        "pins",
        "movies"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Gaming",
      "context": "play",
      "content": "Terraria is the all-time favorite with over 1000 hours. Also loves Pokemon, especially Gen III. Enjoys games that reward exploration and creativity. Retro handhelds are a collecting hobby -- GBA SP and DS Lite are prized possessions.",
      "keywords": [
        "Terraria",
        "Pokemon",
        "gaming",
        "retro",
        "GBA",
        "handhelds"
      ],
      "source": "knowledge"
    },
    {
      "topic": "The Arcade Hub",
      "context": "play",
      "content": "The play side hub is a Canvas 2D single-screen world with a stickman you move with A/D keys. Four gates lead to: Collections (loot gallery of pencils, handhelds, movies, pins), Games (showcase of favorites like Terraria and Pokemon), Slime Lab (generate and keep companion slimes), and RNG Blob (probability distribution visualizer). Hidden secrets are scattered across the rooms -- find all four to activate the elevator to the blob chat.",
      "keywords": [
        "hub",
        "arcade",
        "play",
        "stickman",
        "gate",
        "room",
        "canvas",
        "world",
        "explore"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Slime Generation",
      "context": "play",
      "content": "Slimes are procedurally generated companions using the RNG Machine. Each slime has unique traits determined by probability distributions -- body shape from discrete sampling, color from uniform distribution, size from normal distribution. They can be bred and evolved.",
      "keywords": [
        "slimes",
        "RNG",
        "procedural generation",
        "companion",
        "breeding"
      ],
      "source": "knowledge"
    },
    {
      "topic": "AMHS & Semiconductor Research",
      "context": "professional",
      "content": "Previous research at DC Lab (May 2024 - Jun 2025) focused on stochastic modeling and simulation of automated material handling systems in semiconductor fabrication. Developed dispatch and scheduling algorithms for simulated OHT fleets in AMHS-style fab environments, comparing utilization and flow metrics. Applied stochastic modeling to evaluate throughput under uncertainty, identifying bottleneck stages in wafer-lot material movement. Used Python, SimPy, NumPy, Pandas, and Matplotlib.",
      "keywords": [
        "AMHS",
        "semiconductor",
        "simulation",
        "OHT",
        "Monte Carlo",
        "stochastic modeling",
        "DC Lab",
        "SimPy"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Education",
      "context": "professional",
      "content": "B.S. Industrial Engineering at Purdue University, expected December 2026. Honors Diploma and Honors College member (2020-2025). Minors in Statistics, Manufacturing, and Management. Certificates in Semiconductors & Microelectronics and Data Science Applications. Located in West Lafayette, IN.",
      "keywords": [
        "education",
        "purdue",
        "university",
        "degree",
        "industrial engineering",
        "graduation",
        "minor",
        "statistics",
        "manufacturing",
        "management",
        "certificate",
        "honors",
        "school",
        "college",
        "major"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Operations Research Background",
      "context": "professional",
      "content": "Industrial Engineering student at Purdue (expected Dec 2026) with Honors Diploma, minors in Statistics, Manufacturing, and Management, and certificates in Semiconductors & Microelectronics and Data Science Applications. Specializes in operations research -- coursework covers linear programming, stochastic processes, queueing theory, and statistical modeling. Currently working on Boiler Optimizer (Senior Design Project) using MIP for academic planning with LLM-powered advising. Also conducting human-centered engineering research at NHanCE Lab on AI and VR for AV accessibility.",
      "keywords": [
        "operations research",
        "industrial engineering",
        "Purdue",
        "optimization",
        "queueing theory",
        "MIP",
        "Boiler Optimizer",
        "NHanCE Lab",
        "Honors Diploma"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Technical Skills",
      "context": "professional",
      "content": "OR & Analytics: Mixed-Integer Programming, MCDM, Stochastic Modeling, Markov Chains, Regression, Discrete-Event Simulation, Monte Carlo Methods. Solvers: Gurobi, OR-Tools, Arena. Languages: Python (primary), R, SQL, MATLAB, C, TypeScript, JavaScript, HTML, CSS, PHP. Tools: Git, Robot Framework, Kubernetes, Linux. Web stack includes Astro, Svelte, and Cloudflare Workers for the portfolio site.",
      "keywords": [
        "Python",
        "R",
        "TypeScript",
        "SQL",
        "Gurobi",
        "OR-Tools",
        "Arena",
        "MATLAB",
        "Robot Framework",
        "Kubernetes",
        "Linux",
        "Astro",
        "Svelte",
        "MIP",
        "MCDM",
        "Markov Chains",
        "Monte Carlo"
      ],
      "source": "knowledge"
    },
    {
      "topic": "Student Developer",
      "context": "professional",
      "content": "Designed a MCDM model for academic planning with LLM-powered advising as an independent student project. (Boiler Optimizer). Key work: Designed a custom MIP model for academic planning with prerequisites, time conflicts, and degree audit constraints. Built a multi-criteria decision chatbot with LLM integration for major and concentration recommendations. Developed optimized multi-semester schedule generation for Purdue Engineering students.",
      "keywords": [
        "Python",
        "Gurobi",
        "MIP",
        "LLMs",
        "Purdue",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Purdue University (Edwardson School of Industrial Engineering)",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Flex Team + Solo Event Planner",
      "context": "professional",
      "content": "Brainstormed and executed large-scale events -- self-hosted Purdue's first arm wrestling, track & field, and indoor soccer tournaments.. Key work: Brainstormed and executed large-scale events including cooking competitions, scavenger hunts, and semester-long leagues. Self-hosted Cornerstone's first arm wrestling tournament, first track and field tournament, and first indoor soccer tournament: handling all logistics, venue booking, and outreach. Organized and ran Valorant tournaments with full bracket management and community engagement.",
      "keywords": [
        "Cornerstone",
        "leadership",
        "experience",
        "lead",
        "volunteer",
        "volunteering"
      ],
      "source": "experience",
      "organization": "Cornerstone",
      "category": "leadership",
      "isCurrent": false
    },
    {
      "topic": "Computer Science Instructor",
      "context": "professional",
      "content": "Taught fundamental programming concepts to 32 students with a focus on coding projects to improve creativity and problem-solving.. Key work: Taught fundamental programming concepts to 32 students with a focus on coding projects to improve creativity and problem-solving. Designed lessons and assignments that kept students engaged and building real projects from day one. Helped students develop the confidence to tackle open-ended coding challenges independently.",
      "keywords": [
        "Part-Time",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Part-Time (Paid Position)",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Undergraduate Research Assistant",
      "context": "professional",
      "content": "Discrete-event simulation and stochastic modeling for automated material handling systems in semiconductor fab environments.. Key work: Developed a dispatch and scheduling algorithm for simulated OHT fleets in AMHS-style semiconductor fab environments, comparing utilization and flow metrics. Applied stochastic modeling to evaluate throughput under uncertainty, identifying bottleneck stages in wafer-lot material movement and proposing improvement strategies. Gained hands-on exposure to semiconductor manufacturing logistics and discrete-event simulation methodologies.",
      "keywords": [
        "Python",
        "SimPy",
        "NumPy",
        "Pandas",
        "Matplotlib",
        "DC",
        "research",
        "experience",
        "lab",
        "academic"
      ],
      "source": "experience",
      "organization": "DC Lab",
      "category": "research",
      "isCurrent": false
    },
    {
      "topic": "Data Intern",
      "context": "professional",
      "content": "Data analysis and statistical modeling for hardware reliability, working with large-scale SQL datasets to identify system inconsistencies.. Key work: Created linear regression models to show the statistical significance of EMFs on hardware. Managed large SQL datasets to identify and surface inconsistencies within the system.",
      "keywords": [
        "SQL",
        "Python",
        "Linear Regression",
        "Data Analysis",
        "Dell",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Dell Technologies",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Systems Validation Engineer Intern",
      "context": "professional",
      "content": "Summer internship building automated validation systems for PLC-driven industrial equipment.. Key work: Built and maintained 80+ automated regression tests across SQL and containerized environments. Designed a simulation-based validation system using hardware I/O emulation (LabJack, RPi) to replicate PLC signals. Eliminated the need for expensive physical test setups through reproducible emulated test runs.",
      "keywords": [
        "SQL",
        "Robot Framework",
        "Kubernetes",
        "Linux",
        "Python",
        "Flanders",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Flanders Electric",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Systems Validation Engineer",
      "context": "professional",
      "content": "Continued part-time after internship, maintaining and expanding automated validation systems.. Key work: Increased test coverage by 30% and cut debug cycle time by 4 hours per sprint. Standardized validation procedures across the engineering team. Maintained and expanded the automated regression suite remotely alongside full-time coursework.",
      "keywords": [
        "SQL",
        "Robot Framework",
        "Kubernetes",
        "Linux",
        "Python",
        "Flanders",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Flanders Electric",
      "category": "work",
      "isCurrent": true
    },
    {
      "topic": "Industrial Engineering Mentor",
      "context": "professional",
      "content": "Mentoring 16 undergraduates on curriculum planning, career development, and internship preparation.. Key work: Mentored 16 undergraduates on curriculum planning, career development, and internship preparation. 12 mentees have secured internship or co-op placements so far. Provided one-on-one guidance tailored to each student's goals and timeline.",
      "keywords": [
        "Purdue",
        "leadership",
        "experience",
        "lead",
        "volunteer",
        "volunteering"
      ],
      "source": "experience",
      "organization": "Purdue University",
      "category": "leadership",
      "isCurrent": true
    },
    {
      "topic": "IM Team Captain",
      "context": "professional",
      "content": "Created and captained soccer, softball, volleyball, and basketball teams nearly every semester.. Key work: Created and captained soccer, softball, volleyball, and basketball teams nearly every semester. Organized practices and coordinated schedules across multiple sports and rosters. Built a consistent group of players and kept the competitive spirit fun and inclusive.",
      "keywords": [
        "Purdue",
        "leadership",
        "experience",
        "lead",
        "volunteer",
        "volunteering"
      ],
      "source": "experience",
      "organization": "Purdue Intramural Sports",
      "category": "leadership",
      "isCurrent": false
    },
    {
      "topic": "Judicial Clerk",
      "context": "professional",
      "content": "Documented notes for judicial hearings on parking ticket disputes and student appeals.. Key work: Documented notes for judicial hearings on parking ticket disputes and student appeals. Ensured accurate records for each case to support fair and consistent rulings. Gained exposure to procedural governance and student judicial processes.",
      "keywords": [
        "Purdue",
        "leadership",
        "experience",
        "lead",
        "volunteer",
        "volunteering"
      ],
      "source": "experience",
      "organization": "Purdue Student Government",
      "category": "leadership",
      "isCurrent": false
    },
    {
      "topic": "Server",
      "context": "professional",
      "content": "Table service at a Korean restaurant during peak summer hours.. Key work: Carried plates of sizzling bibimbap at dangerously high speeds. Memorized the entire menu in both Korean and English. Survived every single Friday night dinner rush.",
      "keywords": [
        "Kimchi",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Kimchi Restaurant",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Server",
      "context": "professional",
      "content": "Part-time service role balanced alongside full course load and research responsibilities.. Key work: Became the unofficial mango dessert taste-testing expert. Closed the shop solo more times than I can count. Juggled a full courseload, research, and boba runs without breaking down.",
      "keywords": [
        "Mango",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Mango Mango Dessert",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Undergraduate Researcher",
      "context": "professional",
      "content": "Promoted to paid researcher. Conducting independent research on AI and VR simulation for AV accessibility.. Key work: Conducting a literature review on AI and VR simulation to improve AV accessibility. Developing an independent research proposal on autonomous vehicle interfaces for people with disabilities. Transitioned from volunteer RA to paid researcher based on contributions and initiative.",
      "keywords": [
        "NHanCE",
        "research",
        "experience",
        "lab",
        "academic"
      ],
      "source": "experience",
      "organization": "NHanCE Lab",
      "category": "research",
      "isCurrent": true
    },
    {
      "topic": "Undergraduate Research Assistant",
      "context": "professional",
      "content": "Human-centered engineering research on AI, VR simulation, and autonomous vehicle accessibility for underserved populations.. Key work: Built Fountain of Tech, a website optimized for older adults focused on autonomous vehicles. Deployed SHanCE, an AV assessment survey capturing responses from 50+ participants for factor analysis. Collaborated on human-centered engineering research bridging technology gaps for underserved populations.",
      "keywords": [
        "NHanCE",
        "research",
        "experience",
        "lab",
        "academic"
      ],
      "source": "experience",
      "organization": "NHanCE Lab",
      "category": "research",
      "isCurrent": false
    },
    {
      "topic": "UI Engineer (Intern)",
      "context": "professional",
      "content": "Frontend development for educational web platforms, building design components and improving user experience flows.. Key work: Conducted frontend development using HTML and CSS to build design components and interactive functions for educational web platforms. Debugged and restructured code to streamline user experience flows and improve navigation across the site. Contributed to planning sessions around UX improvements aimed at creating a more accessible educational experience.",
      "keywords": [
        "HTML",
        "CSS",
        "JavaScript",
        "Pearson",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Pearson VUE",
      "category": "work",
      "isCurrent": false
    },
    {
      "topic": "Small Group Leader",
      "context": "professional",
      "content": "Led a small group focused on spiritual growth throughout the entire school year.. Key work: Led a small group focused on spiritual growth throughout the entire school year. Scheduled and ran weekly meetings with creative engagement activities including custom icebreaker games. Built a consistent, welcoming community that encouraged open conversation and personal development.",
      "keywords": [
        "Cornerstone",
        "leadership",
        "experience",
        "lead",
        "volunteer",
        "volunteering"
      ],
      "source": "experience",
      "organization": "Cornerstone",
      "category": "leadership",
      "isCurrent": false
    },
    {
      "topic": "Lab Intern",
      "context": "professional",
      "content": "Autonomous systems lab focused on mobile robotics, sensor integration, and path-planning algorithms.. Key work: Programmed a Roomba to autonomously navigate through a maze using Python and Linux-based tooling. Gained foundational knowledge in mobile robotics, sensor integration, and path-planning algorithms. Worked in a lab setting focused on autonomous systems and hands-on embedded programming.",
      "keywords": [
        "Python",
        "Linux",
        "SMART",
        "research",
        "experience",
        "lab",
        "academic"
      ],
      "source": "experience",
      "organization": "SMART Lab",
      "category": "research",
      "isCurrent": false
    },
    {
      "topic": "Senior Design Project Founder",
      "context": "professional",
      "content": "Transitioned the student project into an official Senior Design Project with faculty sponsorship and validation milestones.. Key work: Secured faculty sponsorship and led the transition into an official Senior Design Project. Defined deliverables and validation milestones for multi-semester project roadmap. Coordinating stakeholder demos and iterative model validation across semesters.",
      "keywords": [
        "Python",
        "Gurobi",
        "MIP",
        "LLMs",
        "Boiler",
        "work",
        "experience",
        "job",
        "career"
      ],
      "source": "experience",
      "organization": "Boiler Optimizer -- Purdue University",
      "category": "work",
      "isCurrent": true
    },
    {
      "topic": "ai for Kyouza",
      "context": "professional",
      "content": "ai for Kyouza: Built a dual-personality AI-powered chatbot with multiple models integrated for varied response styles. Designed the conversational flow to switch between personalities based on context and user input. Integrated multiple LLM backends to give each personality a distinct tone and capability set.",
      "keywords": [
        "AI",
        "Chatbot Development",
        "LLMs",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "AKL OS",
      "context": "professional",
      "content": "AKL OS: Created a fake operating system interface with interactive windows, taskbar navigation, and file-explorer-like project browsing. Designed the experience to be a memorable and unique way for visitors to explore a portfolio.",
      "keywords": [
        "Web Development",
        "UI/UX",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Boiler Optimizer Scraper",
      "context": "professional",
      "content": "Boiler Optimizer Scraper: Built an automated scraper that harvests Purdue's full academic catalog and course schedule data into Supabase. Implements rate limiting, circuit breakers, graceful retry logic, and delta guards to flag anomalies. Uses Playwright for page interaction and Zod for schema validation across 19 database migrations.",
      "keywords": [
        "TypeScript",
        "Playwright",
        "Supabase",
        "Zod",
        "Node.js",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Boiler Optimizer",
      "context": "professional",
      "content": "Boiler Optimizer: Built an academic planning tool that solves a Mixed-Integer Program accounting for prerequisites, time conflicts, and degree rules. Integrated an LLM-powered chatbot for multi-criteria major and concentration recommendations within Purdue Engineering. Deployed as part of an official Senior Design Project with faculty sponsorship and milestone-based validation.",
      "keywords": [
        "Python",
        "Gurobi",
        "MIP",
        "LLMs",
        "research",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Bottle It Up IMS",
      "context": "professional",
      "content": "Bottle It Up IMS: Developed a full-stack information management website for a simulated bottling facility. Designed the database schema and built CRUD operations to manage inventory, orders, and facility data. Created a responsive frontend with form validation and dynamic data rendering.",
      "keywords": [
        "PHP",
        "CSS",
        "SQL",
        "JavaScript",
        "HTML",
        "academic",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Certain Gold Foundry",
      "context": "professional",
      "content": "Certain Gold Foundry: Developing a foundry tool where all game assets for Certain Gold are procedurally generated. Implementing algorithms to create varied textures, sprites, and environmental elements without manual asset creation. Integrating the foundry pipeline directly into the main game's build process for seamless asset delivery.",
      "keywords": [
        "Procedural Generation",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Certain Gold",
      "context": "professional",
      "content": "Certain Gold: Building a 2D extraction platformer featuring a slime main character with momentum-based movement mechanics. Designing level layouts with environmental hazards and resource-collection objectives. Iterating on gameplay feel and pacing through frequent playtesting and feedback loops.",
      "keywords": [
        "Game Development",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Chexcel",
      "context": "professional",
      "content": "Chexcel: Developed a cute, simple budgeting app built as a Progressive Web App for cross-device access. Implemented secure data handling and authentication to keep financial info safe. Focused on clean UX and minimal friction for daily use.",
      "keywords": [
        "PWA",
        "JavaScript",
        "Security",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Doc Tor",
      "context": "professional",
      "content": "Doc Tor: Built a browser-based PDF utility with image-to-PDF conversion, PDF merging, and PDF splitting. All processing runs locally using pdf-lib with no server uploads. File validation uses magic bytes for security. React frontend with drag-and-drop file handling.",
      "keywords": [
        "React",
        "TypeScript",
        "Vite",
        "pdf-lib",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Echo Egg",
      "context": "professional",
      "content": "Echo Egg: Built an interactive personality quiz using the Big Five (OCEAN) model. Computes trait scores from ~42 questions, maps results to one of 8 creature archetypes, and generates a unique procedural creature with sumi-style ink art via seeded PRNG. Includes attention checks, shareable results, and a field guide for collecting past creatures.",
      "keywords": [
        "React",
        "TypeScript",
        "Vite",
        "Tailwind CSS",
        "Canvas",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Enza",
      "context": "professional",
      "content": "Enza: Built an extreme random number generator using Web Crypto API with HKDF-based DRBG and 12 entropy sources including OS crypto, mouse jitter, chaos attractors, and worker race conditions. Features rejection sampling for bias-free range generation, real-time diagnostics (chi-squared, runs test, autocorrelation, Monte Carlo π), and complete offline operation with no data persistence.",
      "keywords": [
        "JavaScript",
        "Web Crypto API",
        "Web Workers",
        "Canvas",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "GenUI",
      "context": "professional",
      "content": "GenUI: Built a procedural design system generator driven by an Aesthetic Genome system. Supports 10 style archetypes, OKLCH color generation with 12 strategies enforcing WCAG AA contrast, and seeded PRNG for reproducible output. Exports npm-ready CSS starter packages that can be saved and compared locally.",
      "keywords": [
        "React",
        "Vite",
        "OKLCH",
        "CSS",
        "Procedural Generation",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "HumAndI",
      "context": "professional",
      "content": "HumAndI: Built a Human vs AI-themed platform that tests human benchmarks through fun games inspired by the Human Benchmark website. Implemented global leaderboards so users can compare their performance against others. Designed the UX around quick, engaging interactions with a competitive edge.",
      "keywords": [
        "Web Development",
        "ML Benchmarking",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "kaishenfit",
      "context": "professional",
      "content": "kaishenfit: Built a full-stack fitness app enabling personal trainers to assign customized workouts and track client progress. Features authenticated trainer and client dashboards, real-time session scheduling, habit checklist tracking, and animated data visualizations with Recharts. Powered by Supabase for auth and persistence.",
      "keywords": [
        "Next.js",
        "React",
        "Supabase",
        "TypeScript",
        "Tailwind CSS",
        "Recharts",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "MarkovSim",
      "context": "professional",
      "content": "MarkovSim: Designed a simulation that pits human judgment against a multi-criteria decision model to demonstrate continuous Markov Chains. Modeled state transitions to evaluate strategy evolution over time under uncertainty. Created an interactive experience that makes stochastic concepts tangible and easy to experiment with.",
      "keywords": [
        "Stochastic Processes",
        "MCDM",
        "Markov Chains",
        "research",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "MLR of Crime Rate vs Socioeconomic Factors",
      "context": "professional",
      "content": "MLR of Crime Rate vs Socioeconomic Factors: Standardized data in R, set target variables and predictors, and formulated null and alternate hypotheses. Built an MLR model with residual plots, QQ plots, Box-Cox transformations, influence point detection, multicollinearity checks, ridge regression, and stepwise model selection.",
      "keywords": [
        "R",
        "Multiple Linear Regression",
        "academic",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Orchestrator",
      "context": "professional",
      "content": "Orchestrator: Built a multi-provider AI orchestration platform unifying Claude Code, Codex CLI, and Gemini CLI into a single coordinated system. Uses xstate for state machine workflows, supports artifact synthesis and gate-based pipelines. Includes both a CLI interface and a React-based web dashboard with local SQL.js persistence.",
      "keywords": [
        "TypeScript",
        "xstate",
        "Express",
        "React",
        "sql.js",
        "Zod",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Portfolio Jeans",
      "context": "professional",
      "content": "Portfolio Jeans: Built a procedural portfolio generator supporting 4 generation modes (professional, creative, experimental, chaos). Uses seeded PRNG for reproducible output, reel locking for iterative refinement, and ZIP export for fully static deployment. Control surface in React with vanilla JS procedural engine.",
      "keywords": [
        "React",
        "Vite",
        "Tailwind CSS",
        "Procedural Generation",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Personal Website + Recruiter Version",
      "context": "professional",
      "content": "Personal Website + Recruiter Version: Built a dual-personality portfolio site featuring a non-AI chatbot that guides visitors through projects and experience. The recruiter version prioritizes clarity and fast access to key information.",
      "keywords": [
        "Astro",
        "Svelte",
        "TypeScript",
        "Cloudflare Workers",
        "D1",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Re-Cord",
      "context": "professional",
      "content": "Re-Cord: Built a vintage-styled screen recording app that captures display, window, or tab with full audio mixing and annotation. All processing happens in the browser with no uploads. Features WebM and MP4 export, direct-to-disk writing via File System Access API, in-browser trimming, and PWA support.",
      "keywords": [
        "Svelte",
        "Vite",
        "Web Audio API",
        "WebCodecs",
        "PWA",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "StatWorkbench",
      "context": "professional",
      "content": "StatWorkbench: Built an analysis workflow that generates diagnostic visualizations including QQ plots, residual plots, and leverage analysis. Implemented Multiple Linear and Ridge Regression pipelines with side-by-side model comparison via RMSE and adjusted R-squared. Designed to support quick, data-driven modeling decisions without heavy manual setup.",
      "keywords": [
        "R",
        "Regression",
        "Statistical Diagnostics",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "zagzig",
      "context": "professional",
      "content": "zagzig: Built a CSS design system that styles the web as a collection of cataloged artifacts from a fictional institution. Uses a rarity tier system (common, uncommon, rare) to govern visual complexity, with stepped geometry and discrete motion. All styles scoped under data attributes with modular imports for flexible adoption.",
      "keywords": [
        "CSS",
        "CSS Custom Properties",
        "personal",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "ZeroArise",
      "context": "professional",
      "content": "ZeroArise: Developing an ML program that mimics characteristics of being alive through learned behavioral patterns. Experimenting with generative and reactive models to simulate awareness and response. Exploring the boundary between scripted behavior and emergent machine responses.",
      "keywords": [
        "Machine Learning",
        "Python",
        "research",
        "project"
      ],
      "source": "project"
    },
    {
      "topic": "Arena",
      "context": "professional",
      "content": "Skill: Arena (Solvers). Proficiency: intermediate.",
      "keywords": [
        "arena",
        "solvers",
        "skill"
      ],
      "source": "skill",
      "category": "Solvers"
    },
    {
      "topic": "Bayesian Inference",
      "context": "professional",
      "content": "Skill: Bayesian Inference (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "bayesian inference",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "C",
      "context": "professional",
      "content": "Skill: C (Languages). Proficiency: intermediate.",
      "keywords": [
        "c",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "CRAFT / ALDEP / CORELAP",
      "context": "professional",
      "content": "Skill: CRAFT / ALDEP / CORELAP (Production Systems). Proficiency: intermediate.",
      "keywords": [
        "craft / aldep / corelap",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "CSS",
      "context": "professional",
      "content": "Skill: CSS (Languages). Proficiency: advanced.",
      "keywords": [
        "css",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Discrete-Event Simulation",
      "context": "professional",
      "content": "Skill: Discrete-Event Simulation (Operations Research). Proficiency: advanced.",
      "keywords": [
        "discrete-event simulation",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Design of Experiments",
      "context": "professional",
      "content": "Skill: Design of Experiments (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "design of experiments",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "Facility Layout & Design",
      "context": "professional",
      "content": "Skill: Facility Layout & Design (Production Systems). Proficiency: advanced.",
      "keywords": [
        "facility layout & design",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "Git",
      "context": "professional",
      "content": "Skill: Git (Tools & Platforms). Proficiency: advanced.",
      "keywords": [
        "git",
        "tools & platforms",
        "skill"
      ],
      "source": "skill",
      "category": "Tools & Platforms"
    },
    {
      "topic": "Gurobi",
      "context": "professional",
      "content": "Skill: Gurobi (Solvers). Proficiency: advanced.",
      "keywords": [
        "gurobi",
        "solvers",
        "skill"
      ],
      "source": "skill",
      "category": "Solvers"
    },
    {
      "topic": "HTML",
      "context": "professional",
      "content": "Skill: HTML (Languages). Proficiency: advanced.",
      "keywords": [
        "html",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Hypothesis Testing",
      "context": "professional",
      "content": "Skill: Hypothesis Testing (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "hypothesis testing",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "JavaScript",
      "context": "professional",
      "content": "Skill: JavaScript (Languages). Proficiency: advanced.",
      "keywords": [
        "javascript",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Kubernetes",
      "context": "professional",
      "content": "Skill: Kubernetes (Tools & Platforms). Proficiency: intermediate.",
      "keywords": [
        "kubernetes",
        "tools & platforms",
        "skill"
      ],
      "source": "skill",
      "category": "Tools & Platforms"
    },
    {
      "topic": "Lean Manufacturing",
      "context": "professional",
      "content": "Skill: Lean Manufacturing (Production Systems). Proficiency: advanced.",
      "keywords": [
        "lean manufacturing",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "Linear Regression",
      "context": "professional",
      "content": "Skill: Linear Regression (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "linear regression",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "Linux",
      "context": "professional",
      "content": "Skill: Linux (Tools & Platforms). Proficiency: intermediate.",
      "keywords": [
        "linux",
        "tools & platforms",
        "skill"
      ],
      "source": "skill",
      "category": "Tools & Platforms"
    },
    {
      "topic": "Machine Learning",
      "context": "professional",
      "content": "Skill: Machine Learning (ML/AI). Proficiency: advanced.",
      "keywords": [
        "machine learning",
        "ml/ai",
        "skill"
      ],
      "source": "skill",
      "category": "ML/AI"
    },
    {
      "topic": "Markov Chains",
      "context": "professional",
      "content": "Skill: Markov Chains (Operations Research). Proficiency: advanced.",
      "keywords": [
        "markov chains",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Material Flow & Handling Analysis",
      "context": "professional",
      "content": "Skill: Material Flow & Handling Analysis (Production Systems). Proficiency: advanced.",
      "keywords": [
        "material flow & handling analysis",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "MATLAB",
      "context": "professional",
      "content": "Skill: MATLAB (Languages). Proficiency: intermediate.",
      "keywords": [
        "matlab",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "MCDM",
      "context": "professional",
      "content": "Skill: MCDM (Operations Research). Proficiency: advanced.",
      "keywords": [
        "mcdm",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Mixed-Integer Programming",
      "context": "professional",
      "content": "Skill: Mixed-Integer Programming (Operations Research). Proficiency: advanced.",
      "keywords": [
        "mixed-integer programming",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Monte Carlo Methods",
      "context": "professional",
      "content": "Skill: Monte Carlo Methods (Operations Research). Proficiency: advanced.",
      "keywords": [
        "monte carlo methods",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "NumPy",
      "context": "professional",
      "content": "Skill: NumPy (Data Science). Proficiency: advanced.",
      "keywords": [
        "numpy",
        "data science",
        "skill"
      ],
      "source": "skill",
      "category": "Data Science"
    },
    {
      "topic": "OR-Tools",
      "context": "professional",
      "content": "Skill: OR-Tools (Solvers). Proficiency: intermediate.",
      "keywords": [
        "or-tools",
        "solvers",
        "skill"
      ],
      "source": "skill",
      "category": "Solvers"
    },
    {
      "topic": "pandas",
      "context": "professional",
      "content": "Skill: pandas (Data Science). Proficiency: advanced.",
      "keywords": [
        "pandas",
        "data science",
        "skill"
      ],
      "source": "skill",
      "category": "Data Science"
    },
    {
      "topic": "PHP",
      "context": "professional",
      "content": "Skill: PHP (Languages). Proficiency: intermediate.",
      "keywords": [
        "php",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Production Systems",
      "context": "professional",
      "content": "Skill: Production Systems (Production Systems). Proficiency: advanced.",
      "keywords": [
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "Python",
      "context": "professional",
      "content": "Skill: Python (Languages). Proficiency: expert.",
      "keywords": [
        "python",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "R",
      "context": "professional",
      "content": "Skill: R (Languages). Proficiency: advanced.",
      "keywords": [
        "r",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Regression",
      "context": "professional",
      "content": "Skill: Regression (Operations Research). Proficiency: advanced.",
      "keywords": [
        "regression",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Robot Framework",
      "context": "professional",
      "content": "Skill: Robot Framework (Tools & Platforms). Proficiency: intermediate.",
      "keywords": [
        "robot framework",
        "tools & platforms",
        "skill"
      ],
      "source": "skill",
      "category": "Tools & Platforms"
    },
    {
      "topic": "scikit-learn",
      "context": "professional",
      "content": "Skill: scikit-learn (Data Science). Proficiency: advanced.",
      "keywords": [
        "scikit-learn",
        "data science",
        "skill"
      ],
      "source": "skill",
      "category": "Data Science"
    },
    {
      "topic": "Systematic Layout Planning",
      "context": "professional",
      "content": "Skill: Systematic Layout Planning (Production Systems). Proficiency: advanced.",
      "keywords": [
        "systematic layout planning",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "Statistical Process Control",
      "context": "professional",
      "content": "Skill: Statistical Process Control (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "statistical process control",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "SQL",
      "context": "professional",
      "content": "Skill: SQL (Languages). Proficiency: advanced.",
      "keywords": [
        "sql",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Statistics & Probability",
      "context": "professional",
      "content": "Skill: Statistics & Probability (Statistics & Probability). Proficiency: advanced.",
      "keywords": [
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "Stochastic Modeling",
      "context": "professional",
      "content": "Skill: Stochastic Modeling (Operations Research). Proficiency: advanced.",
      "keywords": [
        "stochastic modeling",
        "operations research",
        "skill"
      ],
      "source": "skill",
      "category": "Operations Research"
    },
    {
      "topic": "Time Series Analysis",
      "context": "professional",
      "content": "Skill: Time Series Analysis (Statistics & Probability). Proficiency: intermediate.",
      "keywords": [
        "time series analysis",
        "statistics & probability",
        "skill"
      ],
      "source": "skill",
      "category": "Statistics & Probability"
    },
    {
      "topic": "TypeScript",
      "context": "professional",
      "content": "Skill: TypeScript (Languages). Proficiency: advanced.",
      "keywords": [
        "typescript",
        "languages",
        "skill"
      ],
      "source": "skill",
      "category": "Languages"
    },
    {
      "topic": "Value Stream Mapping",
      "context": "professional",
      "content": "Skill: Value Stream Mapping (Production Systems). Proficiency: advanced.",
      "keywords": [
        "value stream mapping",
        "production systems",
        "skill"
      ],
      "source": "skill",
      "category": "Production Systems"
    },
    {
      "topic": "Data Science Applications Certificate",
      "context": "professional",
      "content": "Data Science Applications Certificate - Certificate program in applied data science methods, statistical modeling, and machine learning applications. (Purdue University, 2026-12).",
      "keywords": [
        "data science applications certificate",
        "certificate",
        "purdue",
        "award",
        "honor",
        "achievement"
      ],
      "source": "award"
    },
    {
      "topic": "Lean Green Certificate",
      "context": "professional",
      "content": "Lean Green Certificate - IISE Lean Green certification in lean manufacturing principles and sustainable practices. (IISE, 2026-03).",
      "keywords": [
        "lean green certificate",
        "certificate",
        "iise",
        "award",
        "honor",
        "achievement"
      ],
      "source": "award"
    },
    {
      "topic": "Semiconductors & Microelectronics Certificate",
      "context": "professional",
      "content": "Semiconductors & Microelectronics Certificate - Certificate program covering semiconductor manufacturing processes, device physics, and microelectronics design. (Purdue University, 2026-12).",
      "keywords": [
        "semiconductors & microelectronics certificate",
        "certificate",
        "purdue",
        "award",
        "honor",
        "achievement"
      ],
      "source": "award"
    },
    {
      "topic": "Nintendo DS Lite",
      "context": "play",
      "content": "Nintendo DS Lite (handhelds, common). Onyx black. The hinge is a little loose but it still runs Advance Wars perfectly.",
      "keywords": [
        "nintendo ds lite",
        "handhelds",
        "collection",
        "collectible",
        "common"
      ],
      "source": "collection"
    },
    {
      "topic": "Game Boy Advance SP (AGS-101)",
      "context": "play",
      "content": "Game Boy Advance SP (AGS-101) (handhelds, rare). The backlit model. Still the best way to play Pokemon Emerald.",
      "keywords": [
        "game boy advance sp (ags-101)",
        "handhelds",
        "collection",
        "collectible",
        "rare"
      ],
      "source": "collection"
    },
    {
      "topic": "Blade Runner 2049",
      "context": "play",
      "content": "Blade Runner 2049 (movies, legendary). Peak visual storytelling. The sea wall scene is burned into memory.",
      "keywords": [
        "blade runner 2049",
        "movies",
        "collection",
        "collectible",
        "legendary"
      ],
      "source": "collection"
    },
    {
      "topic": "Spirited Away",
      "context": "play",
      "content": "Spirited Away (movies, rare). Watched it first at age 8 and it rewired how I see animation forever.",
      "keywords": [
        "spirited away",
        "movies",
        "collection",
        "collectible",
        "rare"
      ],
      "source": "collection"
    },
    {
      "topic": "GAN 356 M Speed Cube",
      "context": "play",
      "content": "GAN 356 M Speed Cube (other, uncommon). Sub-30 on a good day. The magnetic positioning is satisfying.",
      "keywords": [
        "gan 356 m speed cube",
        "other",
        "collection",
        "collectible",
        "uncommon"
      ],
      "source": "collection"
    },
    {
      "topic": "TI-Nspire CX CAS",
      "context": "play",
      "content": "TI-Nspire CX CAS (other, common). Survived four years of engineering math. The CAS mode is cheating in the best way.",
      "keywords": [
        "ti-nspire cx cas",
        "other",
        "collection",
        "collectible",
        "common"
      ],
      "source": "collection"
    },
    {
      "topic": "Pentel GraphGear 1000 0.3mm",
      "context": "play",
      "content": "Pentel GraphGear 1000 0.3mm (pencils, uncommon). Dual-action retract with metal grip. Perfect for precise annotations.",
      "keywords": [
        "pentel graphgear 1000 0.3mm",
        "pencils",
        "collection",
        "collectible",
        "uncommon"
      ],
      "source": "collection"
    },
    {
      "topic": "Rotring 800 0.5mm",
      "context": "play",
      "content": "Rotring 800 0.5mm (pencils, rare). The retractable tip mechanism is engineering art. Daily driver for technical sketching.",
      "keywords": [
        "rotring 800 0.5mm",
        "pencils",
        "collection",
        "collectible",
        "rare"
      ],
      "source": "collection"
    },
    {
      "topic": "IE Golden Gear Pin",
      "context": "play",
      "content": "IE Golden Gear Pin (pins, uncommon). Given at the IE department honors ceremony. The gear motif is perfect.",
      "keywords": [
        "ie golden gear pin",
        "pins",
        "collection",
        "collectible",
        "uncommon"
      ],
      "source": "collection"
    },
    {
      "topic": "Purdue Pete Enamel Pin",
      "context": "play",
      "content": "Purdue Pete Enamel Pin (pins, common). Freshman orientation freebie. Surprisingly well made.",
      "keywords": [
        "purdue pete enamel pin",
        "pins",
        "collection",
        "collectible",
        "common"
      ],
      "source": "collection"
    },
    {
      "topic": "League of Legends",
      "context": "play",
      "content": "League of Legends (PC).",
      "keywords": [
        "league of legends",
        "pc",
        "game",
        "gaming"
      ],
      "source": "game"
    },
    {
      "topic": "Minecraft",
      "context": "play",
      "content": "Minecraft (PC).",
      "keywords": [
        "minecraft",
        "pc",
        "game",
        "gaming"
      ],
      "source": "game"
    },
    {
      "topic": "Pokemon Emerald",
      "context": "play",
      "content": "Pokemon Emerald (GBA). 400 hours played. Rating: 9/10. The Battle Frontier consumed an entire summer. Rayquaza is still the coolest legendary.",
      "keywords": [
        "pokemon emerald",
        "gba",
        "game",
        "gaming"
      ],
      "source": "game"
    },
    {
      "topic": "Stardew Valley",
      "context": "play",
      "content": "Stardew Valley (PC).",
      "keywords": [
        "stardew valley",
        "pc",
        "game",
        "gaming"
      ],
      "source": "game"
    },
    {
      "topic": "Terraria",
      "context": "play",
      "content": "Terraria (PC). 1200 hours played. Rating: 10/10. The game that never ends. Every playthrough reveals something new. Master mode with friends is peak gaming.",
      "keywords": [
        "terraria",
        "pc",
        "game",
        "gaming"
      ],
      "source": "game"
    },
    {
      "topic": "Valorant",
      "context": "play",
      "content": "Valorant (PC).",
      "keywords": [
        "valorant",
        "pc",
        "game",
        "gaming"
      ],
      "source": "game"
    }
  ],
  "config": {
    "easterEggs": [
      {
        "trigger": "42",
        "response": {
          "professional": "The answer. But you already knew that.",
          "play": "the answer brudda. obviously"
        }
      },
      {
        "trigger": "alex kyoungmoon lee",
        "response": {
          "professional": "Alex Kyoungmoon Lee. The mind behind this portfolio. Industrial Engineering at Purdue. Ask about his projects, research, or skills.",
          "play": "thats the guy brudda. alex kyoungmoon lee. ask me about his stuff"
        }
      },
      {
        "trigger": "collectible",
        "response": {
          "professional": "Collectibles? There are hidden secrets and display collections on the play side.",
          "play": "oh u mean the secrets? four items are hidden across the rooms. the blob watches those who seek them. collections are different -- those live on the collections page"
        }
      },
      {
        "trigger": "collection",
        "response": {
          "professional": "Alex's collections include mechanical pencils, handhelds, movies, and pins. Check the play side for the full showcase.",
          "play": "collections live on their own page -- pencils, handhelds, movies, pins. secrets are different -- those are hidden in the rooms"
        }
      },
      {
        "trigger": "elevator",
        "response": {
          "professional": "The elevator is a play-side feature.",
          "play": "the elevator brought u here. not everyone makes it this far tbh"
        }
      },
      {
        "trigger": "hint",
        "response": {
          "professional": "Hints are a play-side feature.",
          "play": "the blob sees hidden things brudda. u collected all four items from the rooms? a pencil in collections, a 42 in games, a soccer ball in the slime lab, a violin in the blob room. only then does the elevator activate"
        }
      },
      {
        "trigger": "kyouza",
        "response": {
          "professional": "Kyouza is Alex's indie studio for creative tech projects -- games, interactive experiments, and creative engineering.",
          "play": "kyouza is alexs creative side brudda. indie studio vibes. games experiments and wild ideas"
        }
      },
      {
        "trigger": "meaning of life",
        "response": {
          "professional": "42. Next question.",
          "play": "42. next lol"
        }
      },
      {
        "trigger": "oracle",
        "response": {
          "professional": "There's no blob on this side. Try the play side.",
          "play": "u are speaking to the blob. wada u wanna know"
        }
      },
      {
        "trigger": "pencil",
        "response": {
          "professional": "Alex collects mechanical pencils. The Rotring 800 is the crown jewel.",
          "play": "yo the pencil collection is REAL. rotring 800 is elite. don't even talk to me about cheap pencils"
        }
      },
      {
        "trigger": "secret",
        "response": {
          "professional": "I appreciate the curiosity, but secrets live on the play side.",
          "play": "u want secrets? four are hidden in the rooms -- a pencil, a 42, a soccer ball, a violin. press E where the sparkles whisper. find them all and the elevator activates"
        }
      },
      {
        "trigger": "tell me about alex",
        "response": {
          "professional": "Alex Kyoungmoon Lee studies Industrial Engineering at Purdue, specializing in operations research and stochastic modeling. He builds simulation tools, optimizes systems, and runs Kyouza, a creative tech studio. This portfolio showcases his research and projects.",
          "play": "alex kyoungmoon lee. IE student at purdue. optimization and simulation stuff. built this whole site from scratch. also has kyouza for creative projects"
        }
      },
      {
        "trigger": "what are you",
        "response": {
          "professional": "A knowledge engine. I match questions to answers. No hallucinations, no filler.",
          "play": "a chatbot lol. wut u wanna know"
        }
      },
      {
        "trigger": "who are you",
        "response": {
          "professional": "I'm the system that runs Alex Kyoungmoon Lee's portfolio. I know his work inside out.",
          "play": "the brain behind this place boi. ask me smthn about it"
        }
      },
      {
        "trigger": "who is alex",
        "response": {
          "professional": "Alex Kyoungmoon Lee -- Industrial Engineering student at Purdue University. Focus areas: operations research, stochastic modeling, Monte Carlo simulation, and queueing theory.",
          "play": "alex kyoungmoon lee. purdue IE boi. operations research, monte carlo sims, queueing theory. collects mechanical pencils and plays terraria lol"
        }
      }
    ],
    "help": {
      "professional": "I can discuss Alex's projects, research, skills, experience, education, awards, and more. I don't do small talk. Ask something specific. Try questions like: - \"what projects use Python?\" - \"where does Alex work?\" - \"how many skills?\" - \"list all awards\" - \"when does Alex graduate?\" Commands: - \"topics\" -> list available topics - \"random\" -> random knowledge entry - \"clear\" -> clear chat history - \"about\" -> about this chatbot - \"help\" -> this message",
      "play": "topics: games, collections, slimes, projects, awards, whatever alex has built tbh try stuff like: - \"list all games\" - \"tell me about Terraria\" - \"what collections does alex have?\" commands: - \"topics\" -> list topics - \"random\" -> random entry - \"clear\" -> clear chat - \"about\" -> about me - \"help\" -> ur looking at it brudda",
      "blob": "the blob speaks on: games, collections, slimes, and the secrets of this place. commands: - \"topics\" -> the blobs knowledge - \"random\" -> a random vision - \"clear\" -> wipe the log - \"hint\" -> the blob may reveal something - \"help\" -> you are here"
    },
    "peopleEggs": [
      {
        "patterns": [
          "\\balex\\s*kyoungmoon\\s*lee\\b",
          "\\balex\\s*lee\\b"
        ],
        "response": "🐐 THE GOAT. no cap this man is built different. YESSIRRRR"
      },
      {
        "patterns": [
          "\\balvin\\b",
          "\\baz\\b"
        ],
        "response": "[duo]"
      },
      {
        "patterns": [
          "\\bchloe\\s*chui\\b",
          "\\bchloe\\b"
        ],
        "response": "❤️❤️ ❤️❤️ ❤️❤️❤️❤️❤️❤️❤️ ❤️❤️❤️❤️❤️❤️❤️ ❤️❤️❤️❤️❤️ ❤️❤️❤️ ❤️"
      },
      {
        "patterns": [
          "\\bemre\\b"
        ],
        "response": "[med school arc]"
      },
      {
        "patterns": [
          "\\bnick\\b"
        ],
        "response": "[frog]"
      },
      {
        "patterns": [
          "\\bseohyun\\b",
          "\\bseo\\b"
        ],
        "response": "💰🐰💰🐰💰"
      },
      {
        "patterns": [
          "\\bwilliam\\b"
        ],
        "response": "[apple]"
      },
      {
        "patterns": [
          "\\bza\\b"
        ],
        "response": "kyouza -> indie studio"
      }
    ],
    "greetings": {
      "professional": [
        "Hello. Ask me something worth answering.",
        "Welcome. I'm here to discuss Alex Kyoungmoon Lee's work. What interests you?",
        "Hi. Let's get to the point.",
        "Hello. I don't do small talk, but I know a lot about Alex. Ask away."
      ],
      "play": [
        "i have some changes, wut u want",
        "brudda what u want",
        "yoooo why u msg"
      ],
      "blob": [
        "the blob acknowledges your presence. speak.",
        "another seeker arrives. what do you wish to know?",
        "the signals brought you here. ask your question.",
        "welcome to the peak. the blob listens.",
        "you climbed the elevator. the blob respects that. ask."
      ]
    },
    "noMatch": {
      "professional": [
        "I don't have specific information about that. Try asking about Alex's projects, research, or skills.",
        "That's outside my scope. I cover Alex's work, experience, and projects.",
        "Nothing in my knowledge base matches that. Type 'help' for topics I can discuss."
      ],
      "play": [
        "got nothing on that boi. try smthn about the site",
        "NOPE. ask about games collections or slimes maybe",
        "uhhhhh thats a blank for me. type help if ur lost"
      ],
      "blob": [
        "the blob has no vision on that subject. try collections, games, or slimes.",
        "that path leads nowhere in my sight. ask about something on this site.",
        "the signals are silent on that topic. the blob knows games, collections, and slimes.",
        "beyond the blobs reach. ask about what lives within these walls."
      ]
    },
    "nonsense": {
      "professional": [
        "That doesn't look like a question about Alex's work. Try asking about projects, research, or experience.",
        "I couldn't parse that. I respond best to questions about Alex's portfolio.",
        "Let's try again. What would you like to know about Alex's work?",
        "I'm not sure what you're asking. I can discuss Alex's projects, skills, and experience."
      ],
      "play": [
        "boi nah u weird as heck",
        "huh u losing brain cells or smthn",
        "NAHHHH U SUSSY"
      ],
      "blob": [
        "the blob cannot interpret static. try again.",
        "your signal is corrupted. rephrase.",
        "that frequency is unknown to me. speak clearly.",
        "the blob sees nothing in that noise. try words."
      ]
    },
    "smallTalk": {
      "professional": [
        "I appreciate the thought, but I'm built to discuss Alex's portfolio. What would you like to know about his work?",
        "I don't do casual conversation, but I know a lot about Alex's projects. Ask away.",
        "Interesting, but not my area. Try asking about research, experience, or skills.",
        "Let's keep it focused. I'm here to talk about Alex's work. What interests you?"
      ],
      "play": [
        "why u wanna talk so bad",
        "lol ok ok but also ask about the site its got cool little projects",
        "TRUE lets hang but for real tho check out the collections or games",
        "bruh im a chatbot ask me about alexs stuff",
        "u seem chill. ask me about slimes or smthn"
      ],
      "blob": [
        "the blob does not do idle chatter. ask about what matters.",
        "pleasantries are for the ground level. up here we deal in knowledge.",
        "interesting. but the blob knows better topics. try asking about slimes or collections.",
        "the signals hum with potential. ask about games, collections, or the secrets of this place."
      ]
    }
  },
  "graph": {
    "nodes": [
      {
        "id": "knowledge:About Alex",
        "label": "About Alex",
        "type": "knowledge"
      },
      {
        "id": "knowledge:This Website",
        "label": "This Website",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Collecting",
        "label": "Collecting",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Gaming",
        "label": "Gaming",
        "type": "knowledge"
      },
      {
        "id": "knowledge:The Arcade Hub",
        "label": "The Arcade Hub",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Slime Generation",
        "label": "Slime Generation",
        "type": "knowledge"
      },
      {
        "id": "knowledge:AMHS & Semiconductor Research",
        "label": "AMHS & Semiconductor Research",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Education",
        "label": "Education",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Operations Research Background",
        "label": "Operations Research Background",
        "type": "knowledge"
      },
      {
        "id": "knowledge:Technical Skills",
        "label": "Technical Skills",
        "type": "knowledge"
      },
      {
        "id": "experience:Student Developer",
        "label": "Student Developer",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Flex Team + Solo Event Planner",
        "label": "Flex Team + Solo Event Planner",
        "type": "experience",
        "category": "leadership"
      },
      {
        "id": "experience:Computer Science Instructor",
        "label": "Computer Science Instructor",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Undergraduate Research Assistant",
        "label": "Undergraduate Research Assistant",
        "type": "experience",
        "category": "research"
      },
      {
        "id": "experience:Data Intern",
        "label": "Data Intern",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Systems Validation Engineer Intern",
        "label": "Systems Validation Engineer Intern",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Systems Validation Engineer",
        "label": "Systems Validation Engineer",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Industrial Engineering Mentor",
        "label": "Industrial Engineering Mentor",
        "type": "experience",
        "category": "leadership"
      },
      {
        "id": "experience:IM Team Captain",
        "label": "IM Team Captain",
        "type": "experience",
        "category": "leadership"
      },
      {
        "id": "experience:Judicial Clerk",
        "label": "Judicial Clerk",
        "type": "experience",
        "category": "leadership"
      },
      {
        "id": "experience:Server",
        "label": "Server",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Undergraduate Researcher",
        "label": "Undergraduate Researcher",
        "type": "experience",
        "category": "research"
      },
      {
        "id": "experience:UI Engineer (Intern)",
        "label": "UI Engineer (Intern)",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "experience:Small Group Leader",
        "label": "Small Group Leader",
        "type": "experience",
        "category": "leadership"
      },
      {
        "id": "experience:Lab Intern",
        "label": "Lab Intern",
        "type": "experience",
        "category": "research"
      },
      {
        "id": "experience:Senior Design Project Founder",
        "label": "Senior Design Project Founder",
        "type": "experience",
        "category": "work"
      },
      {
        "id": "project:ai for Kyouza",
        "label": "ai for Kyouza",
        "type": "project"
      },
      {
        "id": "project:AKL OS",
        "label": "AKL OS",
        "type": "project"
      },
      {
        "id": "project:Boiler Optimizer Scraper",
        "label": "Boiler Optimizer Scraper",
        "type": "project"
      },
      {
        "id": "project:Boiler Optimizer",
        "label": "Boiler Optimizer",
        "type": "project"
      },
      {
        "id": "project:Bottle It Up IMS",
        "label": "Bottle It Up IMS",
        "type": "project"
      },
      {
        "id": "project:Certain Gold Foundry",
        "label": "Certain Gold Foundry",
        "type": "project"
      },
      {
        "id": "project:Certain Gold",
        "label": "Certain Gold",
        "type": "project"
      },
      {
        "id": "project:Chexcel",
        "label": "Chexcel",
        "type": "project"
      },
      {
        "id": "project:Doc Tor",
        "label": "Doc Tor",
        "type": "project"
      },
      {
        "id": "project:Echo Egg",
        "label": "Echo Egg",
        "type": "project"
      },
      {
        "id": "project:Enza",
        "label": "Enza",
        "type": "project"
      },
      {
        "id": "project:GenUI",
        "label": "GenUI",
        "type": "project"
      },
      {
        "id": "project:HumAndI",
        "label": "HumAndI",
        "type": "project"
      },
      {
        "id": "project:kaishenfit",
        "label": "kaishenfit",
        "type": "project"
      },
      {
        "id": "project:MarkovSim",
        "label": "MarkovSim",
        "type": "project"
      },
      {
        "id": "project:MLR of Crime Rate vs Socioeconomic Factors",
        "label": "MLR of Crime Rate vs Socioeconomic Factors",
        "type": "project"
      },
      {
        "id": "project:Orchestrator",
        "label": "Orchestrator",
        "type": "project"
      },
      {
        "id": "project:Portfolio Jeans",
        "label": "Portfolio Jeans",
        "type": "project"
      },
      {
        "id": "project:Personal Website + Recruiter Version",
        "label": "Personal Website + Recruiter Version",
        "type": "project"
      },
      {
        "id": "project:Re-Cord",
        "label": "Re-Cord",
        "type": "project"
      },
      {
        "id": "project:StatWorkbench",
        "label": "StatWorkbench",
        "type": "project"
      },
      {
        "id": "project:zagzig",
        "label": "zagzig",
        "type": "project"
      },
      {
        "id": "project:ZeroArise",
        "label": "ZeroArise",
        "type": "project"
      },
      {
        "id": "skill:Arena",
        "label": "Arena",
        "type": "skill",
        "category": "Solvers"
      },
      {
        "id": "skill:Bayesian Inference",
        "label": "Bayesian Inference",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:C",
        "label": "C",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:CRAFT / ALDEP / CORELAP",
        "label": "CRAFT / ALDEP / CORELAP",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:CSS",
        "label": "CSS",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Discrete-Event Simulation",
        "label": "Discrete-Event Simulation",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Design of Experiments",
        "label": "Design of Experiments",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:Facility Layout & Design",
        "label": "Facility Layout & Design",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:Git",
        "label": "Git",
        "type": "skill",
        "category": "Tools & Platforms"
      },
      {
        "id": "skill:Gurobi",
        "label": "Gurobi",
        "type": "skill",
        "category": "Solvers"
      },
      {
        "id": "skill:HTML",
        "label": "HTML",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Hypothesis Testing",
        "label": "Hypothesis Testing",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:JavaScript",
        "label": "JavaScript",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Kubernetes",
        "label": "Kubernetes",
        "type": "skill",
        "category": "Tools & Platforms"
      },
      {
        "id": "skill:Lean Manufacturing",
        "label": "Lean Manufacturing",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:Linear Regression",
        "label": "Linear Regression",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:Linux",
        "label": "Linux",
        "type": "skill",
        "category": "Tools & Platforms"
      },
      {
        "id": "skill:Machine Learning",
        "label": "Machine Learning",
        "type": "skill",
        "category": "ML/AI"
      },
      {
        "id": "skill:Markov Chains",
        "label": "Markov Chains",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Material Flow & Handling Analysis",
        "label": "Material Flow & Handling Analysis",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:MATLAB",
        "label": "MATLAB",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:MCDM",
        "label": "MCDM",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Mixed-Integer Programming",
        "label": "Mixed-Integer Programming",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Monte Carlo Methods",
        "label": "Monte Carlo Methods",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:NumPy",
        "label": "NumPy",
        "type": "skill",
        "category": "Data Science"
      },
      {
        "id": "skill:OR-Tools",
        "label": "OR-Tools",
        "type": "skill",
        "category": "Solvers"
      },
      {
        "id": "skill:pandas",
        "label": "pandas",
        "type": "skill",
        "category": "Data Science"
      },
      {
        "id": "skill:PHP",
        "label": "PHP",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Production Systems",
        "label": "Production Systems",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:Python",
        "label": "Python",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:R",
        "label": "R",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Regression",
        "label": "Regression",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Robot Framework",
        "label": "Robot Framework",
        "type": "skill",
        "category": "Tools & Platforms"
      },
      {
        "id": "skill:scikit-learn",
        "label": "scikit-learn",
        "type": "skill",
        "category": "Data Science"
      },
      {
        "id": "skill:Systematic Layout Planning",
        "label": "Systematic Layout Planning",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "skill:Statistical Process Control",
        "label": "Statistical Process Control",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:SQL",
        "label": "SQL",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Statistics & Probability",
        "label": "Statistics & Probability",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:Stochastic Modeling",
        "label": "Stochastic Modeling",
        "type": "skill",
        "category": "Operations Research"
      },
      {
        "id": "skill:Time Series Analysis",
        "label": "Time Series Analysis",
        "type": "skill",
        "category": "Statistics & Probability"
      },
      {
        "id": "skill:TypeScript",
        "label": "TypeScript",
        "type": "skill",
        "category": "Languages"
      },
      {
        "id": "skill:Value Stream Mapping",
        "label": "Value Stream Mapping",
        "type": "skill",
        "category": "Production Systems"
      },
      {
        "id": "award:Data Science Applications Certificate",
        "label": "Data Science Applications Certificate",
        "type": "award"
      },
      {
        "id": "award:Lean Green Certificate",
        "label": "Lean Green Certificate",
        "type": "award"
      },
      {
        "id": "award:Semiconductors & Microelectronics Certificate",
        "label": "Semiconductors & Microelectronics Certificate",
        "type": "award"
      },
      {
        "id": "collection:Nintendo DS Lite",
        "label": "Nintendo DS Lite",
        "type": "collection"
      },
      {
        "id": "collection:Game Boy Advance SP (AGS-101)",
        "label": "Game Boy Advance SP (AGS-101)",
        "type": "collection"
      },
      {
        "id": "collection:Blade Runner 2049",
        "label": "Blade Runner 2049",
        "type": "collection"
      },
      {
        "id": "collection:Spirited Away",
        "label": "Spirited Away",
        "type": "collection"
      },
      {
        "id": "collection:GAN 356 M Speed Cube",
        "label": "GAN 356 M Speed Cube",
        "type": "collection"
      },
      {
        "id": "collection:TI-Nspire CX CAS",
        "label": "TI-Nspire CX CAS",
        "type": "collection"
      },
      {
        "id": "collection:Pentel GraphGear 1000 0.3mm",
        "label": "Pentel GraphGear 1000 0.3mm",
        "type": "collection"
      },
      {
        "id": "collection:Rotring 800 0.5mm",
        "label": "Rotring 800 0.5mm",
        "type": "collection"
      },
      {
        "id": "collection:IE Golden Gear Pin",
        "label": "IE Golden Gear Pin",
        "type": "collection"
      },
      {
        "id": "collection:Purdue Pete Enamel Pin",
        "label": "Purdue Pete Enamel Pin",
        "type": "collection"
      },
      {
        "id": "game:League of Legends",
        "label": "League of Legends",
        "type": "game"
      },
      {
        "id": "game:Minecraft",
        "label": "Minecraft",
        "type": "game"
      },
      {
        "id": "game:Pokemon Emerald",
        "label": "Pokemon Emerald",
        "type": "game"
      },
      {
        "id": "game:Stardew Valley",
        "label": "Stardew Valley",
        "type": "game"
      },
      {
        "id": "game:Terraria",
        "label": "Terraria",
        "type": "game"
      },
      {
        "id": "game:Valorant",
        "label": "Valorant",
        "type": "game"
      }
    ],
    "edges": [
      {
        "source": "experience:Student Developer",
        "target": "skill:Gurobi",
        "type": "uses"
      },
      {
        "source": "experience:Student Developer",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Undergraduate Research Assistant",
        "target": "skill:NumPy",
        "type": "uses"
      },
      {
        "source": "experience:Undergraduate Research Assistant",
        "target": "skill:pandas",
        "type": "uses"
      },
      {
        "source": "experience:Undergraduate Research Assistant",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Data Intern",
        "target": "skill:Linear Regression",
        "type": "uses"
      },
      {
        "source": "experience:Data Intern",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Data Intern",
        "target": "skill:SQL",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer Intern",
        "target": "skill:Kubernetes",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer Intern",
        "target": "skill:Linux",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer Intern",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer Intern",
        "target": "skill:Robot Framework",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer Intern",
        "target": "skill:SQL",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer",
        "target": "skill:Kubernetes",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer",
        "target": "skill:Linux",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer",
        "target": "skill:Robot Framework",
        "type": "uses"
      },
      {
        "source": "experience:Systems Validation Engineer",
        "target": "skill:SQL",
        "type": "uses"
      },
      {
        "source": "experience:UI Engineer (Intern)",
        "target": "skill:CSS",
        "type": "uses"
      },
      {
        "source": "experience:UI Engineer (Intern)",
        "target": "skill:HTML",
        "type": "uses"
      },
      {
        "source": "experience:UI Engineer (Intern)",
        "target": "skill:JavaScript",
        "type": "uses"
      },
      {
        "source": "experience:Lab Intern",
        "target": "skill:Linux",
        "type": "uses"
      },
      {
        "source": "experience:Lab Intern",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Senior Design Project Founder",
        "target": "skill:Gurobi",
        "type": "uses"
      },
      {
        "source": "experience:Senior Design Project Founder",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "project:Boiler Optimizer Scraper",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:Boiler Optimizer",
        "target": "skill:Gurobi",
        "type": "uses"
      },
      {
        "source": "project:Boiler Optimizer",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "project:Bottle It Up IMS",
        "target": "skill:CSS",
        "type": "uses"
      },
      {
        "source": "project:Bottle It Up IMS",
        "target": "skill:HTML",
        "type": "uses"
      },
      {
        "source": "project:Bottle It Up IMS",
        "target": "skill:JavaScript",
        "type": "uses"
      },
      {
        "source": "project:Bottle It Up IMS",
        "target": "skill:PHP",
        "type": "uses"
      },
      {
        "source": "project:Bottle It Up IMS",
        "target": "skill:SQL",
        "type": "uses"
      },
      {
        "source": "project:Chexcel",
        "target": "skill:JavaScript",
        "type": "uses"
      },
      {
        "source": "project:Doc Tor",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:Echo Egg",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:Enza",
        "target": "skill:JavaScript",
        "type": "uses"
      },
      {
        "source": "project:GenUI",
        "target": "skill:CSS",
        "type": "uses"
      },
      {
        "source": "project:kaishenfit",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:MarkovSim",
        "target": "skill:Markov Chains",
        "type": "uses"
      },
      {
        "source": "project:MarkovSim",
        "target": "skill:MCDM",
        "type": "uses"
      },
      {
        "source": "project:MLR of Crime Rate vs Socioeconomic Factors",
        "target": "skill:R",
        "type": "uses"
      },
      {
        "source": "project:Orchestrator",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:Personal Website + Recruiter Version",
        "target": "skill:TypeScript",
        "type": "uses"
      },
      {
        "source": "project:StatWorkbench",
        "target": "skill:R",
        "type": "uses"
      },
      {
        "source": "project:StatWorkbench",
        "target": "skill:Regression",
        "type": "uses"
      },
      {
        "source": "project:zagzig",
        "target": "skill:CSS",
        "type": "uses"
      },
      {
        "source": "project:ZeroArise",
        "target": "skill:Machine Learning",
        "type": "uses"
      },
      {
        "source": "project:ZeroArise",
        "target": "skill:Python",
        "type": "uses"
      },
      {
        "source": "experience:Student Developer",
        "target": "project:Boiler Optimizer",
        "type": "related"
      },
      {
        "source": "experience:Undergraduate Research Assistant",
        "target": "project:Boiler Optimizer",
        "type": "related"
      },
      {
        "source": "experience:Undergraduate Research Assistant",
        "target": "project:ZeroArise",
        "type": "related"
      },
      {
        "source": "experience:UI Engineer (Intern)",
        "target": "project:Bottle It Up IMS",
        "type": "related"
      },
      {
        "source": "experience:Lab Intern",
        "target": "project:Boiler Optimizer",
        "type": "related"
      },
      {
        "source": "experience:Lab Intern",
        "target": "project:ZeroArise",
        "type": "related"
      },
      {
        "source": "experience:Senior Design Project Founder",
        "target": "project:Boiler Optimizer",
        "type": "related"
      }
    ]
  },
  "bm25": {
    "avgDl": 30.178571428571427,
    "idf": {
      "10": 3.4746248502169728,
      "12": 3.0226397264739155,
      "16": 4.321922710604176,
      "19": 4.321922710604176,
      "30": 3.8110970868381857,
      "32": 4.321922710604176,
      "42": 4.321922710604176,
      "50": 4.321922710604176,
      "80": 4.321922710604176,
      "101": 4.321922710604176,
      "356": 4.321922710604176,
      "400": 4.321922710604176,
      "800": 3.8110970868381857,
      "1000": 3.8110970868381857,
      "1200": 4.321922710604176,
      "2020": 4.321922710604176,
      "2024": 4.321922710604176,
      "2025": 3.8110970868381857,
      "2026": 3.0226397264739155,
      "2049": 4.321922710604176,
      "alex": 3.8110970868381857,
      "kyoungmoon": 4.321922710604176,
      "lee": 4.321922710604176,
      "industrial": 3.0226397264739155,
      "engineering": 2.3760125615488628,
      "student": 2.855585641810749,
      "purdue": 2.1246981332679566,
      "university": 3.2233104219360666,
      "specializing": 4.321922710604176,
      "operations": 2.3760125615488628,
      "research": 1.8096170866280614,
      "stochastic": 2.7124847981700757,
      "modeling": 2.4760960201058455,
      "simulation": 2.4760960201058455,
      "builds": 4.321922710604176,
      "creative": 3.4746248502169728,
      "tech": 3.4746248502169728,
      "under": 3.0226397264739155,
      "kyouza": 3.8110970868381857,
      "studio": 4.321922710604176,
      "collects": 3.8110970868381857,
      "mechanical": 3.8110970868381857,
      "pencils": 3.0226397264739155,
      "plays": 4.321922710604176,
      "terraria": 3.2233104219360666,
      "generates": 3.4746248502169728,
      "slimes": 3.4746248502169728,
      "stack": 3.0226397264739155,
      "spans": 4.321922710604176,
      "python": 2.1246981332679566,
      "typescript": 2.4760960201058455,
      "sql": 2.58732165521607,
      "gurobi": 2.855585641810749,
      "bio": 4.321922710604176,
      "background": 3.8110970868381857,
      "person": 4.321922710604176,
      "introduction": 4.321922710604176,
      "profile": 4.321922710604176,
      "website": 3.0226397264739155,
      "portfolio": 3.0226397264739155,
      "dual": 3.2233104219360666,
      "personality": 3.2233104219360666,
      "site": 3.2233104219360666,
      "built": 1.528714701161659,
      "astro": 3.4746248502169728,
      "svelte": 3.2233104219360666,
      "professional": 3.8110970868381857,
      "side": 3.4746248502169728,
      "minimal": 3.8110970868381857,
      "data": 1.9240274378058055,
      "driven": 3.2233104219360666,
      "play": 3.4746248502169728,
      "retro": 3.4746248502169728,
      "crt": 4.321922710604176,
      "arcade": 3.8110970868381857,
      "stickman": 3.8110970868381857,
      "hub": 3.8110970868381857,
      "collectible": 2.285040783343136,
      "secrets": 3.8110970868381857,
      "slime": 3.2233104219360666,
      "lab": 2.58732165521607,
      "rng": 3.4746248502169728,
      "blob": 3.8110970868381857,
      "external": 4.321922710604176,
      "ai": 2.4760960201058455,
      "chatbot": 3.0226397264739155,
      "runs": 2.855585641810749,
      "entirely": 4.321922710604176,
      "client": 3.8110970868381857,
      "keyword": 4.321922710604176,
      "matching": 4.321922710604176,
      "scratch": 4.321922710604176,
      "architecture": 4.321922710604176,
      "frontend": 3.2233104219360666,
      "collecting": 3.4746248502169728,
      "rotring": 3.8110970868381857,
      "crown": 4.321922710604176,
      "jewel": 4.321922710604176,
      "handhelds": 3.0226397264739155,
      "movie": 4.321922710604176,
      "memorabilia": 4.321922710604176,
      "enamel": 3.8110970868381857,
      "pins": 3.2233104219360666,
      "every": 3.2233104219360666,
      "item": 4.321922710604176,
      "story": 4.321922710604176,
      "rarity": 3.8110970868381857,
      "tier": 3.8110970868381857,
      "common": 3.0226397264739155,
      "legendary": 3.4746248502169728,
      "movies": 3.2233104219360666,
      "gaming": 2.7124847981700757,
      "all": 2.7124847981700757,
      "time": 2.3760125615488628,
      "favorite": 4.321922710604176,
      "over": 3.8110970868381857,
      "hours": 3.0226397264739155,
      "loves": 4.321922710604176,
      "pokemon": 3.2233104219360666,
      "especially": 4.321922710604176,
      "gen": 4.321922710604176,
      "iii": 4.321922710604176,
      "enjoys": 4.321922710604176,
      "games": 3.2233104219360666,
      "reward": 4.321922710604176,
      "exploration": 4.321922710604176,
      "creativity": 3.8110970868381857,
      "hobby": 4.321922710604176,
      "gba": 3.8110970868381857,
      "sp": 3.8110970868381857,
      "ds": 3.8110970868381857,
      "lite": 3.8110970868381857,
      "prized": 4.321922710604176,
      "possessions": 4.321922710604176,
      "canvas": 3.4746248502169728,
      "2d": 3.8110970868381857,
      "single": 3.4746248502169728,
      "screen": 3.8110970868381857,
      "world": 4.321922710604176,
      "move": 4.321922710604176,
      "keys": 4.321922710604176,
      "four": 3.8110970868381857,
      "gates": 4.321922710604176,
      "lead": 2.855585641810749,
      "collections": 4.321922710604176,
      "loot": 4.321922710604176,
      "gallery": 4.321922710604176,
      "showcase": 4.321922710604176,
      "favorites": 4.321922710604176,
      "generate": 4.321922710604176,
      "keep": 3.8110970868381857,
      "companion": 3.8110970868381857,
      "probability": 2.4760960201058455,
      "distribution": 3.8110970868381857,
      "visualizer": 4.321922710604176,
      "hidden": 4.321922710604176,
      "scattered": 4.321922710604176,
      "across": 2.7124847981700757,
      "rooms": 4.321922710604176,
      "find": 4.321922710604176,
      "activate": 4.321922710604176,
      "elevator": 4.321922710604176,
      "chat": 4.321922710604176,
      "gate": 3.8110970868381857,
      "room": 4.321922710604176,
      "explore": 3.8110970868381857,
      "generation": 2.855585641810749,
      "procedurally": 3.8110970868381857,
      "generated": 3.8110970868381857,
      "companions": 4.321922710604176,
      "using": 2.58732165521607,
      "machine": 3.0226397264739155,
      "each": 3.2233104219360666,
      "unique": 3.4746248502169728,
      "traits": 4.321922710604176,
      "determined": 4.321922710604176,
      "distributions": 4.321922710604176,
      "body": 4.321922710604176,
      "shape": 4.321922710604176,
      "discrete": 3.0226397264739155,
      "sampling": 3.8110970868381857,
      "color": 3.8110970868381857,
      "uniform": 4.321922710604176,
      "size": 4.321922710604176,
      "normal": 4.321922710604176,
      "bred": 4.321922710604176,
      "evolved": 4.321922710604176,
      "procedural": 2.855585641810749,
      "breeding": 4.321922710604176,
      "amhs": 3.8110970868381857,
      "semiconductor": 3.4746248502169728,
      "previous": 4.321922710604176,
      "dc": 3.8110970868381857,
      "jun": 4.321922710604176,
      "focused": 3.0226397264739155,
      "automated": 3.0226397264739155,
      "material": 3.4746248502169728,
      "handling": 2.855585641810749,
      "systems": 2.201659174404085,
      "fabrication": 4.321922710604176,
      "developed": 3.0226397264739155,
      "dispatch": 3.8110970868381857,
      "scheduling": 3.4746248502169728,
      "algorithms": 3.4746248502169728,
      "simulated": 3.4746248502169728,
      "oht": 3.8110970868381857,
      "fleets": 3.8110970868381857,
      "style": 3.2233104219360666,
      "fab": 3.8110970868381857,
      "environments": 3.4746248502169728,
      "comparing": 3.8110970868381857,
      "utilization": 3.8110970868381857,
      "flow": 3.2233104219360666,
      "metrics": 3.8110970868381857,
      "applied": 3.4746248502169728,
      "evaluate": 3.4746248502169728,
      "throughput": 3.8110970868381857,
      "uncertainty": 3.4746248502169728,
      "identifying": 3.8110970868381857,
      "bottleneck": 3.8110970868381857,
      "stages": 3.8110970868381857,
      "wafer": 3.8110970868381857,
      "lot": 3.8110970868381857,
      "movement": 3.4746248502169728,
      "used": 4.321922710604176,
      "simpy": 3.8110970868381857,
      "numpy": 3.4746248502169728,
      "pandas": 3.4746248502169728,
      "matplotlib": 3.8110970868381857,
      "monte": 3.2233104219360666,
      "carlo": 3.2233104219360666,
      "education": 4.321922710604176,
      "expected": 3.8110970868381857,
      "december": 4.321922710604176,
      "honors": 3.4746248502169728,
      "diploma": 3.8110970868381857,
      "college": 4.321922710604176,
      "member": 4.321922710604176,
      "minors": 3.8110970868381857,
      "statistics": 2.4760960201058455,
      "manufacturing": 2.855585641810749,
      "management": 3.2233104219360666,
      "certificates": 3.8110970868381857,
      "semiconductors": 3.4746248502169728,
      "microelectronics": 3.4746248502169728,
      "science": 2.7124847981700757,
      "applications": 3.4746248502169728,
      "located": 4.321922710604176,
      "west": 4.321922710604176,
      "lafayette": 4.321922710604176,
      "degree": 3.4746248502169728,
      "graduation": 4.321922710604176,
      "minor": 4.321922710604176,
      "certificate": 3.2233104219360666,
      "school": 3.8110970868381857,
      "major": 3.4746248502169728,
      "dec": 4.321922710604176,
      "specializes": 4.321922710604176,
      "coursework": 3.8110970868381857,
      "covers": 4.321922710604176,
      "linear": 3.0226397264739155,
      "programming": 3.0226397264739155,
      "processes": 3.2233104219360666,
      "queueing": 4.321922710604176,
      "theory": 4.321922710604176,
      "statistical": 3.0226397264739155,
      "currently": 4.321922710604176,
      "working": 3.8110970868381857,
      "boiler": 3.0226397264739155,
      "optimizer": 3.2233104219360666,
      "senior": 3.4746248502169728,
      "design": 2.4760960201058455,
      "project": 1.450243085720164,
      "mip": 3.0226397264739155,
      "academic": 2.3760125615488628,
      "planning": 2.7124847981700757,
      "llm": 3.2233104219360666,
      "powered": 3.0226397264739155,
      "advising": 3.8110970868381857,
      "conducting": 3.8110970868381857,
      "human": 3.2233104219360666,
      "centered": 3.8110970868381857,
      "nhance": 3.4746248502169728,
      "vr": 3.4746248502169728,
      "av": 3.4746248502169728,
      "accessibility": 3.4746248502169728,
      "optimization": 4.321922710604176,
      "technical": 3.8110970868381857,
      "skills": 4.321922710604176,
      "analytics": 4.321922710604176,
      "mixed": 3.4746248502169728,
      "integer": 3.4746248502169728,
      "mcdm": 3.2233104219360666,
      "markov": 3.4746248502169728,
      "chains": 3.4746248502169728,
      "regression": 2.58732165521607,
      "event": 3.2233104219360666,
      "methods": 3.4746248502169728,
      "solvers": 3.2233104219360666,
      "tools": 2.855585641810749,
      "arena": 3.8110970868381857,
      "languages": 2.285040783343136,
      "primary": 4.321922710604176,
      "matlab": 3.8110970868381857,
      "javascript": 2.855585641810749,
      "html": 3.2233104219360666,
      "css": 2.4760960201058455,
      "php": 3.4746248502169728,
      "git": 3.8110970868381857,
      "robot": 3.2233104219360666,
      "framework": 3.2233104219360666,
      "kubernetes": 3.2233104219360666,
      "linux": 3.0226397264739155,
      "web": 2.4760960201058455,
      "includes": 3.4746248502169728,
      "cloudflare": 3.8110970868381857,
      "workers": 3.4746248502169728,
      "developer": 4.321922710604176,
      "designed": 2.4760960201058455,
      "model": 2.7124847981700757,
      "independent": 3.8110970868381857,
      "key": 1.7569733531426395,
      "work": 1.8096170866280614,
      "custom": 3.4746248502169728,
      "prerequisites": 3.8110970868381857,
      "conflicts": 3.8110970868381857,
      "audit": 4.321922710604176,
      "constraints": 4.321922710604176,
      "multi": 3.0226397264739155,
      "criteria": 3.4746248502169728,
      "decision": 3.8110970868381857,
      "integration": 3.8110970868381857,
      "concentration": 3.8110970868381857,
      "recommendations": 3.8110970868381857,
      "optimized": 3.8110970868381857,
      "semester": 3.2233104219360666,
      "schedule": 3.8110970868381857,
      "students": 3.8110970868381857,
      "llms": 3.2233104219360666,
      "experience": 1.6593348835787234,
      "job": 2.4760960201058455,
      "career": 2.3760125615488628,
      "flex": 4.321922710604176,
      "team": 3.4746248502169728,
      "solo": 3.8110970868381857,
      "planner": 4.321922710604176,
      "brainstormed": 4.321922710604176,
      "executed": 4.321922710604176,
      "large": 3.8110970868381857,
      "scale": 3.8110970868381857,
      "events": 4.321922710604176,
      "self": 4.321922710604176,
      "hosted": 4.321922710604176,
      "first": 3.8110970868381857,
      "arm": 4.321922710604176,
      "wrestling": 4.321922710604176,
      "track": 3.8110970868381857,
      "field": 3.8110970868381857,
      "indoor": 4.321922710604176,
      "soccer": 3.8110970868381857,
      "tournaments": 4.321922710604176,
      "including": 3.2233104219360666,
      "cooking": 4.321922710604176,
      "competitions": 4.321922710604176,
      "scavenger": 4.321922710604176,
      "hunts": 4.321922710604176,
      "long": 4.321922710604176,
      "leagues": 4.321922710604176,
      "cornerstone": 3.8110970868381857,
      "tournament": 4.321922710604176,
      "logistics": 3.8110970868381857,
      "venue": 4.321922710604176,
      "booking": 4.321922710604176,
      "outreach": 4.321922710604176,
      "organized": 3.8110970868381857,
      "ran": 3.8110970868381857,
      "valorant": 3.8110970868381857,
      "full": 2.7124847981700757,
      "bracket": 4.321922710604176,
      "community": 3.8110970868381857,
      "engagement": 3.8110970868381857,
      "leadership": 3.0226397264739155,
      "volunteer": 2.855585641810749,
      "volunteering": 3.0226397264739155,
      "computer": 4.321922710604176,
      "instructor": 4.321922710604176,
      "taught": 4.321922710604176,
      "fundamental": 4.321922710604176,
      "concepts": 3.8110970868381857,
      "focus": 4.321922710604176,
      "coding": 4.321922710604176,
      "projects": 3.8110970868381857,
      "improve": 3.4746248502169728,
      "problem": 4.321922710604176,
      "solving": 4.321922710604176,
      "lessons": 4.321922710604176,
      "assignments": 4.321922710604176,
      "kept": 3.8110970868381857,
      "engaged": 4.321922710604176,
      "building": 3.2233104219360666,
      "real": 3.4746248502169728,
      "day": 3.8110970868381857,
      "one": 3.4746248502169728,
      "helped": 4.321922710604176,
      "develop": 4.321922710604176,
      "confidence": 4.321922710604176,
      "tackle": 4.321922710604176,
      "open": 3.8110970868381857,
      "ended": 4.321922710604176,
      "challenges": 4.321922710604176,
      "independently": 4.321922710604176,
      "part": 3.2233104219360666,
      "undergraduate": 3.4746248502169728,
      "assistant": 3.8110970868381857,
      "algorithm": 4.321922710604176,
      "proposing": 4.321922710604176,
      "improvement": 4.321922710604176,
      "strategies": 3.8110970868381857,
      "gained": 3.4746248502169728,
      "hands": 3.8110970868381857,
      "exposure": 3.8110970868381857,
      "methodologies": 4.321922710604176,
      "intern": 3.2233104219360666,
      "analysis": 3.0226397264739155,
      "hardware": 3.8110970868381857,
      "reliability": 4.321922710604176,
      "datasets": 4.321922710604176,
      "identify": 4.321922710604176,
      "system": 2.7124847981700757,
      "inconsistencies": 4.321922710604176,
      "created": 3.0226397264739155,
      "models": 3.4746248502169728,
      "show": 4.321922710604176,
      "significance": 4.321922710604176,
      "emfs": 4.321922710604176,
      "managed": 4.321922710604176,
      "surface": 3.8110970868381857,
      "within": 3.8110970868381857,
      "dell": 4.321922710604176,
      "validation": 2.7124847981700757,
      "engineer": 3.4746248502169728,
      "summer": 3.4746248502169728,
      "internship": 3.4746248502169728,
      "plc": 4.321922710604176,
      "equipment": 4.321922710604176,
      "maintained": 3.8110970868381857,
      "tests": 3.8110970868381857,
      "containerized": 4.321922710604176,
      "based": 2.4760960201058455,
      "emulation": 4.321922710604176,
      "labjack": 4.321922710604176,
      "rpi": 4.321922710604176,
      "replicate": 4.321922710604176,
      "signals": 4.321922710604176,
      "eliminated": 4.321922710604176,
      "need": 4.321922710604176,
      "expensive": 4.321922710604176,
      "physical": 4.321922710604176,
      "test": 3.4746248502169728,
      "setups": 4.321922710604176,
      "reproducible": 3.4746248502169728,
      "emulated": 4.321922710604176,
      "flanders": 3.8110970868381857,
      "continued": 4.321922710604176,
      "maintaining": 4.321922710604176,
      "expanding": 4.321922710604176,
      "increased": 4.321922710604176,
      "coverage": 4.321922710604176,
      "cut": 4.321922710604176,
      "debug": 4.321922710604176,
      "cycle": 4.321922710604176,
      "per": 4.321922710604176,
      "sprint": 4.321922710604176,
      "standardized": 3.8110970868381857,
      "procedures": 4.321922710604176,
      "expanded": 4.321922710604176,
      "suite": 4.321922710604176,
      "remotely": 4.321922710604176,
      "alongside": 3.8110970868381857,
      "mentor": 4.321922710604176,
      "mentoring": 4.321922710604176,
      "undergraduates": 4.321922710604176,
      "curriculum": 4.321922710604176,
      "development": 2.7124847981700757,
      "preparation": 4.321922710604176,
      "mentored": 4.321922710604176,
      "mentees": 4.321922710604176,
      "secured": 3.8110970868381857,
      "co": 4.321922710604176,
      "op": 4.321922710604176,
      "placements": 4.321922710604176,
      "far": 4.321922710604176,
      "provided": 4.321922710604176,
      "guidance": 4.321922710604176,
      "tailored": 4.321922710604176,
      "goals": 4.321922710604176,
      "timeline": 4.321922710604176,
      "im": 4.321922710604176,
      "captain": 4.321922710604176,
      "captained": 4.321922710604176,
      "softball": 4.321922710604176,
      "volleyball": 4.321922710604176,
      "basketball": 4.321922710604176,
      "teams": 4.321922710604176,
      "nearly": 4.321922710604176,
      "practices": 3.8110970868381857,
      "coordinated": 3.8110970868381857,
      "schedules": 4.321922710604176,
      "multiple": 3.2233104219360666,
      "sports": 4.321922710604176,
      "rosters": 4.321922710604176,
      "consistent": 3.4746248502169728,
      "group": 3.8110970868381857,
      "players": 4.321922710604176,
      "competitive": 3.8110970868381857,
      "spirit": 4.321922710604176,
      "fun": 3.8110970868381857,
      "inclusive": 4.321922710604176,
      "judicial": 4.321922710604176,
      "clerk": 4.321922710604176,
      "documented": 4.321922710604176,
      "notes": 4.321922710604176,
      "hearings": 4.321922710604176,
      "parking": 4.321922710604176,
      "ticket": 4.321922710604176,
      "disputes": 4.321922710604176,
      "appeals": 4.321922710604176,
      "ensured": 4.321922710604176,
      "accurate": 4.321922710604176,
      "records": 4.321922710604176,
      "case": 4.321922710604176,
      "support": 3.4746248502169728,
      "fair": 4.321922710604176,
      "rulings": 4.321922710604176,
      "governance": 4.321922710604176,
      "server": 3.4746248502169728,
      "table": 4.321922710604176,
      "service": 3.8110970868381857,
      "korean": 4.321922710604176,
      "restaurant": 4.321922710604176,
      "peak": 3.4746248502169728,
      "carried": 4.321922710604176,
      "plates": 4.321922710604176,
      "sizzling": 4.321922710604176,
      "bibimbap": 4.321922710604176,
      "dangerously": 4.321922710604176,
      "high": 4.321922710604176,
      "speeds": 4.321922710604176,
      "memorized": 4.321922710604176,
      "entire": 3.4746248502169728,
      "menu": 4.321922710604176,
      "both": 3.8110970868381857,
      "english": 4.321922710604176,
      "survived": 3.8110970868381857,
      "friday": 4.321922710604176,
      "night": 4.321922710604176,
      "dinner": 4.321922710604176,
      "rush": 4.321922710604176,
      "kimchi": 4.321922710604176,
      "role": 4.321922710604176,
      "balanced": 4.321922710604176,
      "course": 3.8110970868381857,
      "load": 4.321922710604176,
      "responsibilities": 4.321922710604176,
      "became": 4.321922710604176,
      "unofficial": 4.321922710604176,
      "mango": 4.321922710604176,
      "dessert": 4.321922710604176,
      "taste": 4.321922710604176,
      "testing": 3.8110970868381857,
      "expert": 3.8110970868381857,
      "closed": 4.321922710604176,
      "shop": 4.321922710604176,
      "more": 3.8110970868381857,
      "times": 4.321922710604176,
      "count": 4.321922710604176,
      "juggled": 4.321922710604176,
      "courseload": 4.321922710604176,
      "boba": 4.321922710604176,
      "without": 3.4746248502169728,
      "breaking": 4.321922710604176,
      "down": 4.321922710604176,
      "researcher": 4.321922710604176,
      "promoted": 4.321922710604176,
      "paid": 4.321922710604176,
      "literature": 4.321922710604176,
      "review": 4.321922710604176,
      "developing": 3.4746248502169728,
      "proposal": 4.321922710604176,
      "autonomous": 3.4746248502169728,
      "vehicle": 3.8110970868381857,
      "interfaces": 4.321922710604176,
      "people": 4.321922710604176,
      "disabilities": 4.321922710604176,
      "transitioned": 3.8110970868381857,
      "ra": 4.321922710604176,
      "contributions": 4.321922710604176,
      "initiative": 4.321922710604176,
      "underserved": 4.321922710604176,
      "populations": 4.321922710604176,
      "fountain": 4.321922710604176,
      "older": 4.321922710604176,
      "adults": 4.321922710604176,
      "vehicles": 4.321922710604176,
      "deployed": 3.8110970868381857,
      "shance": 4.321922710604176,
      "assessment": 4.321922710604176,
      "survey": 4.321922710604176,
      "capturing": 4.321922710604176,
      "responses": 3.8110970868381857,
      "participants": 4.321922710604176,
      "factor": 4.321922710604176,
      "collaborated": 4.321922710604176,
      "bridging": 4.321922710604176,
      "technology": 4.321922710604176,
      "gaps": 4.321922710604176,
      "ui": 3.8110970868381857,
      "educational": 4.321922710604176,
      "platforms": 3.0226397264739155,
      "components": 4.321922710604176,
      "improving": 4.321922710604176,
      "user": 3.8110970868381857,
      "flows": 4.321922710604176,
      "conducted": 4.321922710604176,
      "build": 3.8110970868381857,
      "interactive": 3.2233104219360666,
      "functions": 4.321922710604176,
      "debugged": 4.321922710604176,
      "restructured": 4.321922710604176,
      "code": 3.8110970868381857,
      "streamline": 4.321922710604176,
      "navigation": 3.8110970868381857,
      "contributed": 4.321922710604176,
      "sessions": 4.321922710604176,
      "around": 3.8110970868381857,
      "ux": 3.2233104219360666,
      "improvements": 4.321922710604176,
      "aimed": 4.321922710604176,
      "creating": 4.321922710604176,
      "accessible": 4.321922710604176,
      "pearson": 4.321922710604176,
      "small": 4.321922710604176,
      "leader": 4.321922710604176,
      "led": 3.8110970868381857,
      "spiritual": 4.321922710604176,
      "growth": 4.321922710604176,
      "throughout": 4.321922710604176,
      "year": 4.321922710604176,
      "scheduled": 4.321922710604176,
      "weekly": 4.321922710604176,
      "meetings": 4.321922710604176,
      "activities": 4.321922710604176,
      "icebreaker": 4.321922710604176,
      "welcoming": 4.321922710604176,
      "encouraged": 4.321922710604176,
      "conversation": 4.321922710604176,
      "personal": 1.7569733531426395,
      "mobile": 4.321922710604176,
      "robotics": 4.321922710604176,
      "sensor": 4.321922710604176,
      "path": 4.321922710604176,
      "programmed": 4.321922710604176,
      "roomba": 4.321922710604176,
      "autonomously": 4.321922710604176,
      "navigate": 4.321922710604176,
      "maze": 4.321922710604176,
      "tooling": 4.321922710604176,
      "foundational": 4.321922710604176,
      "knowledge": 4.321922710604176,
      "worked": 4.321922710604176,
      "setting": 4.321922710604176,
      "embedded": 4.321922710604176,
      "smart": 4.321922710604176,
      "founder": 4.321922710604176,
      "official": 3.8110970868381857,
      "faculty": 3.8110970868381857,
      "sponsorship": 3.8110970868381857,
      "milestones": 4.321922710604176,
      "transition": 4.321922710604176,
      "defined": 4.321922710604176,
      "deliverables": 4.321922710604176,
      "roadmap": 4.321922710604176,
      "coordinating": 4.321922710604176,
      "stakeholder": 4.321922710604176,
      "demos": 4.321922710604176,
      "iterative": 3.8110970868381857,
      "semesters": 4.321922710604176,
      "integrated": 3.8110970868381857,
      "varied": 3.8110970868381857,
      "response": 3.8110970868381857,
      "styles": 3.8110970868381857,
      "conversational": 4.321922710604176,
      "switch": 4.321922710604176,
      "personalities": 4.321922710604176,
      "context": 4.321922710604176,
      "input": 4.321922710604176,
      "backends": 4.321922710604176,
      "give": 4.321922710604176,
      "distinct": 4.321922710604176,
      "tone": 4.321922710604176,
      "capability": 4.321922710604176,
      "set": 3.8110970868381857,
      "akl": 4.321922710604176,
      "os": 3.8110970868381857,
      "fake": 4.321922710604176,
      "operating": 4.321922710604176,
      "interface": 3.8110970868381857,
      "windows": 4.321922710604176,
      "taskbar": 4.321922710604176,
      "file": 3.4746248502169728,
      "explorer": 4.321922710604176,
      "browsing": 4.321922710604176,
      "memorable": 4.321922710604176,
      "way": 3.4746248502169728,
      "visitors": 3.8110970868381857,
      "scraper": 4.321922710604176,
      "harvests": 4.321922710604176,
      "catalog": 4.321922710604176,
      "supabase": 3.8110970868381857,
      "implements": 4.321922710604176,
      "rate": 3.8110970868381857,
      "limiting": 4.321922710604176,
      "circuit": 4.321922710604176,
      "breakers": 4.321922710604176,
      "graceful": 4.321922710604176,
      "retry": 4.321922710604176,
      "logic": 4.321922710604176,
      "delta": 4.321922710604176,
      "guards": 4.321922710604176,
      "flag": 4.321922710604176,
      "anomalies": 4.321922710604176,
      "uses": 3.0226397264739155,
      "playwright": 4.321922710604176,
      "page": 4.321922710604176,
      "interaction": 4.321922710604176,
      "zod": 3.8110970868381857,
      "schema": 3.8110970868381857,
      "database": 3.8110970868381857,
      "migrations": 4.321922710604176,
      "node": 4.321922710604176,
      "js": 3.2233104219360666,
      "tool": 3.8110970868381857,
      "solves": 4.321922710604176,
      "program": 3.2233104219360666,
      "accounting": 4.321922710604176,
      "rules": 4.321922710604176,
      "milestone": 4.321922710604176,
      "bottle": 4.321922710604176,
      "up": 4.321922710604176,
      "ims": 4.321922710604176,
      "information": 3.8110970868381857,
      "bottling": 4.321922710604176,
      "facility": 3.8110970868381857,
      "crud": 4.321922710604176,
      "manage": 4.321922710604176,
      "inventory": 4.321922710604176,
      "orders": 4.321922710604176,
      "responsive": 4.321922710604176,
      "form": 4.321922710604176,
      "dynamic": 4.321922710604176,
      "rendering": 4.321922710604176,
      "certain": 3.8110970868381857,
      "gold": 3.8110970868381857,
      "foundry": 4.321922710604176,
      "game": 2.4760960201058455,
      "assets": 4.321922710604176,
      "implementing": 4.321922710604176,
      "create": 4.321922710604176,
      "textures": 4.321922710604176,
      "sprites": 4.321922710604176,
      "environmental": 3.8110970868381857,
      "elements": 4.321922710604176,
      "manual": 3.8110970868381857,
      "asset": 4.321922710604176,
      "creation": 4.321922710604176,
      "integrating": 4.321922710604176,
      "pipeline": 4.321922710604176,
      "directly": 4.321922710604176,
      "main": 3.8110970868381857,
      "process": 3.8110970868381857,
      "seamless": 4.321922710604176,
      "delivery": 4.321922710604176,
      "extraction": 4.321922710604176,
      "platformer": 4.321922710604176,
      "featuring": 3.8110970868381857,
      "character": 4.321922710604176,
      "momentum": 4.321922710604176,
      "mechanics": 4.321922710604176,
      "designing": 4.321922710604176,
      "level": 4.321922710604176,
      "layouts": 4.321922710604176,
      "hazards": 4.321922710604176,
      "resource": 4.321922710604176,
      "collection": 2.201659174404085,
      "objectives": 4.321922710604176,
      "iterating": 4.321922710604176,
      "gameplay": 4.321922710604176,
      "feel": 4.321922710604176,
      "pacing": 4.321922710604176,
      "frequent": 4.321922710604176,
      "playtesting": 4.321922710604176,
      "feedback": 4.321922710604176,
      "loops": 4.321922710604176,
      "chexcel": 4.321922710604176,
      "cute": 4.321922710604176,
      "simple": 4.321922710604176,
      "budgeting": 4.321922710604176,
      "app": 3.4746248502169728,
      "progressive": 4.321922710604176,
      "cross": 4.321922710604176,
      "device": 3.8110970868381857,
      "access": 3.4746248502169728,
      "implemented": 3.4746248502169728,
      "secure": 4.321922710604176,
      "authentication": 4.321922710604176,
      "financial": 4.321922710604176,
      "info": 4.321922710604176,
      "safe": 4.321922710604176,
      "clean": 4.321922710604176,
      "friction": 4.321922710604176,
      "daily": 3.8110970868381857,
      "use": 4.321922710604176,
      "pwa": 3.8110970868381857,
      "security": 3.8110970868381857,
      "doc": 4.321922710604176,
      "tor": 4.321922710604176,
      "browser": 3.8110970868381857,
      "pdf": 4.321922710604176,
      "utility": 4.321922710604176,
      "image": 4.321922710604176,
      "conversion": 4.321922710604176,
      "merging": 4.321922710604176,
      "splitting": 4.321922710604176,
      "processing": 3.8110970868381857,
      "locally": 3.8110970868381857,
      "lib": 4.321922710604176,
      "uploads": 3.8110970868381857,
      "magic": 4.321922710604176,
      "bytes": 4.321922710604176,
      "react": 2.855585641810749,
      "drag": 4.321922710604176,
      "drop": 4.321922710604176,
      "vite": 3.0226397264739155,
      "echo": 4.321922710604176,
      "egg": 4.321922710604176,
      "quiz": 4.321922710604176,
      "big": 4.321922710604176,
      "five": 4.321922710604176,
      "ocean": 4.321922710604176,
      "computes": 4.321922710604176,
      "trait": 4.321922710604176,
      "scores": 4.321922710604176,
      "questions": 4.321922710604176,
      "maps": 4.321922710604176,
      "results": 4.321922710604176,
      "creature": 4.321922710604176,
      "archetypes": 3.8110970868381857,
      "sumi": 4.321922710604176,
      "ink": 4.321922710604176,
      "art": 3.8110970868381857,
      "via": 3.4746248502169728,
      "seeded": 3.4746248502169728,
      "prng": 3.4746248502169728,
      "attention": 4.321922710604176,
      "checks": 3.8110970868381857,
      "shareable": 4.321922710604176,
      "guide": 4.321922710604176,
      "past": 4.321922710604176,
      "creatures": 4.321922710604176,
      "tailwind": 3.4746248502169728,
      "enza": 4.321922710604176,
      "extreme": 4.321922710604176,
      "random": 4.321922710604176,
      "number": 4.321922710604176,
      "generator": 3.4746248502169728,
      "crypto": 4.321922710604176,
      "api": 3.8110970868381857,
      "hkdf": 4.321922710604176,
      "drbg": 4.321922710604176,
      "entropy": 4.321922710604176,
      "sources": 4.321922710604176,
      "mouse": 4.321922710604176,
      "jitter": 4.321922710604176,
      "chaos": 3.8110970868381857,
      "attractors": 4.321922710604176,
      "worker": 4.321922710604176,
      "race": 4.321922710604176,
      "conditions": 4.321922710604176,
      "features": 3.4746248502169728,
      "rejection": 4.321922710604176,
      "bias": 4.321922710604176,
      "free": 4.321922710604176,
      "range": 4.321922710604176,
      "diagnostics": 3.8110970868381857,
      "chi": 4.321922710604176,
      "squared": 3.8110970868381857,
      "autocorrelation": 4.321922710604176,
      "complete": 4.321922710604176,
      "offline": 4.321922710604176,
      "operation": 4.321922710604176,
      "persistence": 3.4746248502169728,
      "genui": 4.321922710604176,
      "aesthetic": 4.321922710604176,
      "genome": 4.321922710604176,
      "supports": 3.8110970868381857,
      "oklch": 4.321922710604176,
      "enforcing": 4.321922710604176,
      "wcag": 4.321922710604176,
      "aa": 4.321922710604176,
      "contrast": 4.321922710604176,
      "output": 3.8110970868381857,
      "exports": 4.321922710604176,
      "npm": 4.321922710604176,
      "ready": 4.321922710604176,
      "starter": 4.321922710604176,
      "packages": 4.321922710604176,
      "saved": 4.321922710604176,
      "compared": 4.321922710604176,
      "humandi": 4.321922710604176,
      "vs": 3.8110970868381857,
      "themed": 4.321922710604176,
      "platform": 3.8110970868381857,
      "benchmarks": 4.321922710604176,
      "inspired": 4.321922710604176,
      "benchmark": 4.321922710604176,
      "global": 4.321922710604176,
      "leaderboards": 4.321922710604176,
      "users": 4.321922710604176,
      "compare": 4.321922710604176,
      "performance": 4.321922710604176,
      "against": 3.8110970868381857,
      "others": 4.321922710604176,
      "quick": 3.8110970868381857,
      "engaging": 4.321922710604176,
      "interactions": 4.321922710604176,
      "edge": 4.321922710604176,
      "ml": 3.4746248502169728,
      "benchmarking": 4.321922710604176,
      "kaishenfit": 4.321922710604176,
      "fitness": 4.321922710604176,
      "enabling": 4.321922710604176,
      "trainers": 4.321922710604176,
      "assign": 4.321922710604176,
      "customized": 4.321922710604176,
      "workouts": 4.321922710604176,
      "progress": 4.321922710604176,
      "authenticated": 4.321922710604176,
      "trainer": 4.321922710604176,
      "dashboards": 4.321922710604176,
      "session": 4.321922710604176,
      "habit": 4.321922710604176,
      "checklist": 4.321922710604176,
      "tracking": 4.321922710604176,
      "animated": 4.321922710604176,
      "visualizations": 3.8110970868381857,
      "recharts": 4.321922710604176,
      "auth": 4.321922710604176,
      "next": 4.321922710604176,
      "markovsim": 4.321922710604176,
      "pits": 4.321922710604176,
      "judgment": 4.321922710604176,
      "demonstrate": 4.321922710604176,
      "continuous": 4.321922710604176,
      "modeled": 4.321922710604176,
      "state": 3.8110970868381857,
      "transitions": 4.321922710604176,
      "strategy": 4.321922710604176,
      "evolution": 4.321922710604176,
      "makes": 4.321922710604176,
      "tangible": 4.321922710604176,
      "easy": 4.321922710604176,
      "experiment": 4.321922710604176,
      "mlr": 4.321922710604176,
      "crime": 4.321922710604176,
      "socioeconomic": 4.321922710604176,
      "factors": 4.321922710604176,
      "target": 4.321922710604176,
      "variables": 4.321922710604176,
      "predictors": 4.321922710604176,
      "formulated": 4.321922710604176,
      "null": 4.321922710604176,
      "alternate": 4.321922710604176,
      "hypotheses": 4.321922710604176,
      "residual": 3.8110970868381857,
      "plots": 3.8110970868381857,
      "qq": 3.8110970868381857,
      "box": 4.321922710604176,
      "cox": 4.321922710604176,
      "transformations": 4.321922710604176,
      "influence": 4.321922710604176,
      "point": 4.321922710604176,
      "detection": 4.321922710604176,
      "multicollinearity": 4.321922710604176,
      "ridge": 3.8110970868381857,
      "stepwise": 4.321922710604176,
      "selection": 4.321922710604176,
      "orchestrator": 4.321922710604176,
      "provider": 4.321922710604176,
      "orchestration": 4.321922710604176,
      "unifying": 4.321922710604176,
      "claude": 4.321922710604176,
      "codex": 4.321922710604176,
      "cli": 4.321922710604176,
      "gemini": 4.321922710604176,
      "xstate": 4.321922710604176,
      "workflows": 4.321922710604176,
      "artifact": 4.321922710604176,
      "synthesis": 4.321922710604176,
      "pipelines": 3.8110970868381857,
      "dashboard": 4.321922710604176,
      "local": 4.321922710604176,
      "express": 4.321922710604176,
      "jeans": 4.321922710604176,
      "supporting": 4.321922710604176,
      "modes": 4.321922710604176,
      "experimental": 4.321922710604176,
      "reel": 4.321922710604176,
      "locking": 4.321922710604176,
      "refinement": 4.321922710604176,
      "zip": 4.321922710604176,
      "export": 3.8110970868381857,
      "fully": 4.321922710604176,
      "static": 4.321922710604176,
      "deployment": 4.321922710604176,
      "control": 3.8110970868381857,
      "vanilla": 4.321922710604176,
      "engine": 4.321922710604176,
      "recruiter": 4.321922710604176,
      "version": 4.321922710604176,
      "non": 4.321922710604176,
      "guides": 4.321922710604176,
      "prioritizes": 4.321922710604176,
      "clarity": 4.321922710604176,
      "fast": 4.321922710604176,
      "d1": 4.321922710604176,
      "re": 4.321922710604176,
      "cord": 4.321922710604176,
      "vintage": 4.321922710604176,
      "styled": 4.321922710604176,
      "recording": 4.321922710604176,
      "captures": 4.321922710604176,
      "display": 4.321922710604176,
      "window": 4.321922710604176,
      "tab": 4.321922710604176,
      "audio": 4.321922710604176,
      "mixing": 4.321922710604176,
      "annotation": 4.321922710604176,
      "happens": 4.321922710604176,
      "webm": 4.321922710604176,
      "mp4": 4.321922710604176,
      "direct": 4.321922710604176,
      "disk": 4.321922710604176,
      "writing": 4.321922710604176,
      "trimming": 4.321922710604176,
      "webcodecs": 4.321922710604176,
      "statworkbench": 4.321922710604176,
      "workflow": 4.321922710604176,
      "diagnostic": 4.321922710604176,
      "leverage": 4.321922710604176,
      "comparison": 4.321922710604176,
      "rmse": 4.321922710604176,
      "adjusted": 4.321922710604176,
      "decisions": 4.321922710604176,
      "heavy": 4.321922710604176,
      "setup": 4.321922710604176,
      "zagzig": 4.321922710604176,
      "cataloged": 4.321922710604176,
      "artifacts": 4.321922710604176,
      "fictional": 4.321922710604176,
      "institution": 4.321922710604176,
      "uncommon": 3.2233104219360666,
      "rare": 3.2233104219360666,
      "govern": 4.321922710604176,
      "visual": 3.8110970868381857,
      "complexity": 4.321922710604176,
      "stepped": 4.321922710604176,
      "geometry": 4.321922710604176,
      "motion": 4.321922710604176,
      "scoped": 4.321922710604176,
      "attributes": 4.321922710604176,
      "modular": 4.321922710604176,
      "imports": 4.321922710604176,
      "flexible": 4.321922710604176,
      "adoption": 4.321922710604176,
      "properties": 4.321922710604176,
      "zeroarise": 4.321922710604176,
      "mimics": 4.321922710604176,
      "characteristics": 4.321922710604176,
      "alive": 4.321922710604176,
      "learned": 4.321922710604176,
      "behavioral": 4.321922710604176,
      "patterns": 4.321922710604176,
      "experimenting": 4.321922710604176,
      "generative": 4.321922710604176,
      "reactive": 4.321922710604176,
      "simulate": 4.321922710604176,
      "awareness": 4.321922710604176,
      "exploring": 4.321922710604176,
      "boundary": 4.321922710604176,
      "scripted": 4.321922710604176,
      "behavior": 4.321922710604176,
      "emergent": 4.321922710604176,
      "learning": 3.4746248502169728,
      "skill": 0.9778837427819695,
      "proficiency": 0.9778837427819695,
      "intermediate": 2.3760125615488628,
      "bayesian": 4.321922710604176,
      "inference": 4.321922710604176,
      "advanced": 1.2774002728807532,
      "craft": 4.321922710604176,
      "aldep": 4.321922710604176,
      "corelap": 4.321922710604176,
      "production": 2.7124847981700757,
      "experiments": 4.321922710604176,
      "layout": 3.8110970868381857,
      "hypothesis": 4.321922710604176,
      "lean": 3.8110970868381857,
      "scikit": 4.321922710604176,
      "learn": 4.321922710604176,
      "systematic": 4.321922710604176,
      "series": 4.321922710604176,
      "value": 4.321922710604176,
      "stream": 4.321922710604176,
      "mapping": 4.321922710604176,
      "award": 3.4746248502169728,
      "honor": 3.4746248502169728,
      "achievement": 3.4746248502169728,
      "green": 4.321922710604176,
      "iise": 4.321922710604176,
      "certification": 4.321922710604176,
      "principles": 4.321922710604176,
      "sustainable": 4.321922710604176,
      "03": 4.321922710604176,
      "covering": 4.321922710604176,
      "physics": 4.321922710604176,
      "nintendo": 4.321922710604176,
      "onyx": 4.321922710604176,
      "black": 4.321922710604176,
      "hinge": 4.321922710604176,
      "little": 4.321922710604176,
      "loose": 4.321922710604176,
      "still": 3.4746248502169728,
      "advance": 3.8110970868381857,
      "wars": 4.321922710604176,
      "perfectly": 4.321922710604176,
      "boy": 4.321922710604176,
      "ags": 4.321922710604176,
      "backlit": 4.321922710604176,
      "best": 3.8110970868381857,
      "emerald": 3.8110970868381857,
      "blade": 4.321922710604176,
      "runner": 4.321922710604176,
      "storytelling": 4.321922710604176,
      "sea": 4.321922710604176,
      "wall": 4.321922710604176,
      "scene": 4.321922710604176,
      "burned": 4.321922710604176,
      "memory": 4.321922710604176,
      "spirited": 4.321922710604176,
      "away": 4.321922710604176,
      "watched": 4.321922710604176,
      "age": 4.321922710604176,
      "rewired": 4.321922710604176,
      "animation": 4.321922710604176,
      "forever": 4.321922710604176,
      "gan": 4.321922710604176,
      "speed": 4.321922710604176,
      "cube": 4.321922710604176,
      "other": 3.8110970868381857,
      "sub": 4.321922710604176,
      "good": 4.321922710604176,
      "magnetic": 4.321922710604176,
      "positioning": 4.321922710604176,
      "satisfying": 4.321922710604176,
      "ti": 4.321922710604176,
      "nspire": 4.321922710604176,
      "cx": 4.321922710604176,
      "cas": 4.321922710604176,
      "years": 4.321922710604176,
      "math": 4.321922710604176,
      "mode": 3.8110970868381857,
      "cheating": 4.321922710604176,
      "pentel": 4.321922710604176,
      "graphgear": 4.321922710604176,
      "3mm": 4.321922710604176,
      "action": 4.321922710604176,
      "retract": 4.321922710604176,
      "metal": 4.321922710604176,
      "grip": 4.321922710604176,
      "perfect": 3.8110970868381857,
      "precise": 4.321922710604176,
      "annotations": 4.321922710604176,
      "5mm": 4.321922710604176,
      "retractable": 4.321922710604176,
      "tip": 4.321922710604176,
      "mechanism": 4.321922710604176,
      "driver": 4.321922710604176,
      "sketching": 4.321922710604176,
      "ie": 4.321922710604176,
      "golden": 4.321922710604176,
      "gear": 4.321922710604176,
      "pin": 3.8110970868381857,
      "given": 4.321922710604176,
      "department": 4.321922710604176,
      "ceremony": 4.321922710604176,
      "motif": 4.321922710604176,
      "pete": 4.321922710604176,
      "freshman": 4.321922710604176,
      "orientation": 4.321922710604176,
      "freebie": 4.321922710604176,
      "surprisingly": 4.321922710604176,
      "well": 4.321922710604176,
      "made": 4.321922710604176,
      "league": 4.321922710604176,
      "legends": 4.321922710604176,
      "pc": 3.0226397264739155,
      "minecraft": 4.321922710604176,
      "played": 3.8110970868381857,
      "rating": 3.8110970868381857,
      "battle": 4.321922710604176,
      "frontier": 4.321922710604176,
      "consumed": 4.321922710604176,
      "rayquaza": 4.321922710604176,
      "coolest": 4.321922710604176,
      "stardew": 4.321922710604176,
      "valley": 4.321922710604176,
      "never": 4.321922710604176,
      "ends": 4.321922710604176,
      "playthrough": 4.321922710604176,
      "reveals": 4.321922710604176,
      "something": 4.321922710604176,
      "new": 4.321922710604176,
      "master": 4.321922710604176,
      "friends": 4.321922710604176
    }
  }
}