Experience Timeline
Mar 2025 – Present
Founder & Solo Full-Stack Engineer
DemandEngine
- Built a data pipeline ingesting 5k+ Reddit/HN posts daily, extracting 32k pain-point signals to generate 1-2k unique SaaS ideas.
- Deployed a DeepSeek-7B LLM with a twin-pass ranking system, achieving a 95% manual QA pass rate for generated ideas.
- Engineered a scalable React + Django/FastAPI stack on GCP/Vercel, handling 100 concurrent users with p99 latency under 1s.
Jan 2025 – Present
VP External & Quant Sports Betting Team Lead
Michigan Finance and Mathematics Society
- Leading development of a multi-factor sports betting strategy for NCAA basketball, achieving significant backtested ROI.
Sep 2024 – Nov 2024
Structural Analysis Intern
Rocket Lab
- Reduced full-satellite modal analysis compute time by over 95% (1.5 hours to <5 mins) by developing a reduced-order composite fuel tank model.
- Closed a critical thermal analysis risk item for a preliminary design review by verifying satellite structural integrity under orbital temperature gradients.
- Established a standardized test workflow for composite inserts and used chi-square analysis to determine B-basis load allowables per NASA standards.
May 2024 – Jul 2024
Building Physics Intern
Harris
- Co-authored the first ASHRAE paper on modular-build emissions.
- Designed a data center thermal-storage cooling system.
Jan 2024 – Apr 2024
Mechanical Engineering Co-op
Copeland
- Simulated compressor part collisions in NX Nastran and automated lab-test analytics in Python to verify long-term component reliability.
Sep 2023 – Jan 2024
Mechanical Team Member
Michigan Robotic Submarine
- Designed and CFD-optimized a torpedo launcher, bumping RoboSub scoring potential by 2k+ points while integrating cleanly into the hull.
May 2023 – Jul 2023
Software Engineer
Stealth Startup
- Shipped bilingual FastPitch TTS and LoRA-tuned RAG LLMs, wiring the stack into a fully conversational voice customer-service platform.
Jun 2021 – Aug 2021
Engineering Research Intern
EMTECH
- Co-authored an ESA CubeSat subsystem guide and delivered thermal/electrical analyses for the mission’s hardware simulator, with work being later used in ESA's Space Rider mission.
Featured Project
Deep Reinforcement Learning Hedging Agent
Engineered a PPO+LSTM agent to dynamically hedge an equity position using options, drastically outperforming traditional delta-hedging. This project involved building a custom Gym/Backtrader environment with realistic market frictions and a C++ based rough volatility simulation.
-93%
Transaction Costs
-45%
P&L Volatility
NCAA Basketball Market Prediction Model
Developed an end-to-end prediction pipeline for NCAA point spreads, integrating a multi-model sentiment analysis from 50+ subreddits. The sentiment pipeline alone lifted ROI by 7%.
+9.8%
ROI (15k+ bets)
3.0
Sharpe Ratio
Hybrid Monte Carlo Pricer for American Options
Built a C++ pricer combining four estimation methods with a Bayesian neural network meta-model under a rough Bergomi volatility framework to capture realistic market dynamics and automate parameter calibration.
View on GitHub →Published Research
Trader Behavior in 2024 Election Prediction Markets
An analysis of retail and institutional impact on Kalshi prediction markets. This research investigates the microstructure of political prediction markets, segmenting traders using a Gaussian Mixture Model to analyze their respective impacts on price movements and market efficiency.
View Data & Code on GitHub →Key Findings
→ Retail Influence: Retail flow was more predictive of subsequent price changes in the KH market.
→ Institutional Impact: Institutional impact was more significant in the DJT market.
→ Market Resilience: Markets showed high resilience to large volume trades from either group.
→ Complex Corrections: Institutional behavior post-mispricing was complex and not purely corrective.
Skills Visualization
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