NELSON
KANG
CS & Finance · Builder · UWaterloo
ABOUT
ME
I'm a Computing and Financial Management student at the University of Waterloo — bridging CS and Finance to build systems that are both technically rigorous and commercially sharp.
I gravitate toward hard problems: computer vision pipelines, ML engines, and quantitative tools. If it's complex and consequential, I'm in.
TECH
STACK
CLIP
FARM
Automated volleyball highlight generator. Users upload game film; YOLOv8-pose extracts player skeletons frame-by-frame, a rule-based classifier scores spikes, serves, and blocks, and FFmpeg re-encodes clips served via presigned Cloudflare R2 URLs. Audio RMS analysis reduces false-positive clips by ~20%.
VIEW ON GITHUB ›CHESS
AI
Neural-network chess engine trained on millions of Stockfish-labeled positions using distributed GPU compute on Modal. Classical alpha-beta search paired with deep neural evaluation for real-time gameplay, balancing search depth with inference latency.
VIEW ON GITHUB ›STOCK
PORTFOLIO
ENGINE
1st place, Market Beat Competition. Multi-factor portfolio pipeline applying momentum, volatility, correlation, and trend signals (RAAM). Optimized a $1M CAD portfolio across U.S. and Canadian equities — 5.7% return vs. 3.7% benchmark, out of 18 teams.
VIEW ON GITHUB ›QUILLIFY
EDU
Educational content management platform built with ASP.NET Core. Full user auth with email confirmation, account lockout policies, and strong password enforcement. Notes management, contact forms, and content creation with Entity Framework + SQL Server.
VIEW ON GITHUB ›LET'S
BUILD.
Always open to interesting problems and good people. Reach out and let's talk.