I build things that grow — apps, funnels, systems. I care about shipping fast, measuring what matters, and making something people actually use. Looking for my next thing.
A habit-tracking app that helps people quit weed by maintaining a daily streak for every day clean. Inspired by RizzGPT's approach to wrapping a simple, sticky mechanic around a real problem people talk about but don't have tools for.
The insight: tons of people want to quit but struggle with consistency. No app existed that made it feel achievable. WeedTrack keeps it dead simple — track your streak, see your progress, stay accountable. Built end-to-end from idea to working app.
View on GitHub →Designed and shipped an end-to-end webinar acquisition funnel for a drop-servicing mentorship program. Previous launches struggled with high CPL ($10–15), low attendance (<50%), and inconsistent lead quality. I rebuilt the entire flow: ads, registration, automated SMS/email nurture, and a live 90-min webinar with direct CTA to book.
Ran 10 customer interviews and analyzed 100+ social comments to build user personas and identify key hesitations (skepticism about online business models, fear of doing physical labor). Addressed each in ad creative and webinar content with proof, case studies, and live Q&A.
Built a full research engine for testing momentum and reversal signals on BTC and 6 altcoins. Designed and backtested three hypotheses (crash reversal, Bollinger-band reversion, low-volume fade), combined them via equal-weight and risk-parity methods, and stress-tested across cost grids and 500+ daily windows.
Composite strategy achieved Sharpe 0.8–1.0 on BTC after 20 bps costs, with cross-asset robustness across ETH, SOL, XRP, ADA, LTC, and DOGE. Engineered the full vectorized Python stack: OHLCV alignment, cost-aware P&L, automated equity/drawdown/turnover reporting.
View on GitHub →I'm a senior at the University of Michigan studying Economics (4.0 GPA). I've spent the last few years building in the gap between product, growth, and engineering — doing customer research, shipping GTM systems, writing Python, and building apps.
Before college, I worked as a research assistant for Nobel laureate Thomas Sargent at NYU, processing 100K+ Revolutionary War debt records and building fuzzy-matching pipelines. I also did ML research on COVID co-infection patterns and artificial-pancreas safety systems at Stony Brook.
I'm an AIME qualifier (score 7) and scored 1540 on the SAT. I think in systems, I like hard problems, and I ship.