Information / Data Science @ Cornell
I study Information Science at Cornell, with a Data Science concentration and Artificial Intelligence minor. I work across Python, R, JavaScript, statistics, dashboarding, and AI modeling to turn messy datasets into clear decisions.
My projects focus on research data products, instrument dashboards, literature extraction, and decision tools. My experience spans AI modeling, fixed income banking, venture capital, business analytics, and content analytics, which helps me connect technical work to real users and business questions.
cocoylh.comResearch constraint-aware LLM reasoning and build RAG and AI agent workflows for retrievable, executable, and verifiable question answering across open-domain knowledge, professional documents, and structured datasets.
Build AI-assisted modeling workflows for ARPES and superconductivity research, linking materials, temperature features, literature evidence, and model-ready experiment records.
Prepare issuer research, market comparables, and client-ready materials for fixed income banking workstreams. Analyze credit fundamentals, transaction precedents, and bond market conditions.
Conduct due diligence on early-stage healthtech and biotech companies, translating market sizing, unit economics, competitive analysis, and downside risks into investment memos.
Built Excel models and dashboards across 10+ enterprise software firms to evaluate revenue drivers, cash flow sustainability, unit economics, and operating metrics.
Analyzed engagement patterns and tested content strategy adjustments, driving 468% engagement growth and 287% impression growth through data-informed iteration.
Conducted structured quantitative analysis using Excel and SPSS, synthesized analytical outputs, and supported empirical research deliverables for senior researchers.
Selected projects with the product surface, technical stack, and links visible at a glance.
Research Data Product
2026
Searchable research site for ARPES and superconductivity literature, with materials, figures, keywords, and source records in one browser workflow.
Frontend: HTML, CSS, JavaScript
Data: Python extraction scripts, JSON datasets
ARPES Temperature Control Dashboard
2026
Browser dashboard and EPICS IOC for Lake Shore 336 temperature control, with live channel readbacks, ramp/setpoint controls, safety limits, bilingual UI, and CSV logging.
Frontend: HTML, CSS, JavaScript, Canvas charts
Control: Python serial dashboard, EPICS IOC, StreamDevice
Student Organization Website
2026
Cornell HAMA site for the chapter mission, people, events, alumni network, employers, and member-facing resources.
Frontend: HTML, CSS, JavaScript
Hosting: GitHub Pages, custom domain
Consumer Web Prototype
2026
Group meal ordering prototype with active orders, member thresholds, countdown deadlines, cart state, pickup points, and order progress.
Frontend: HTML, CSS, JavaScript
Product: Cart state, countdown UI, flow simulation
Interactive Learning & Coding Tool
2026
Beginner-friendly workspace for solving the Hot 100, writing Python beside each prompt, explaining code line by line, keeping review notes, and checking solutions with in-browser tests.
Frontend: React, TypeScript, responsive CSS
Runtime: Pyodide, Web Worker, local browser storage
In my free time, I like to take pictures and collect small visual stories from daily life, travel, food, and the places I spend time in.
Financial modeling, forecasting, unit economics, scenario analysis, sensitivity analysis, and valuation.
Advanced Excel, Python, Java, R, dashboard development, data cleaning, and KPI tracking.
English, Mandarin, Cantonese, Spanish, tennis, golf, business strategy, and applied data analysis.
I'm always happy to connect about analytics, finance, research, data projects, or opportunities where clear thinking and practical tools matter.