Mehra-Prescott with Rare Disasters (Equity Premium Puzzle)
Published:
Extends the Mehra-Prescott consumption-based asset pricing model with a mathematical rare disasters framework calibrated to U.S. data.
Portfolio
RobustSight: AI Safety & Alignment Framework
Published:
Comprehensive CV + LLM safety framework investigating adversarial robustness, interpretability, and human-guided alignment across frontier models.
Traffic Flow Optimization
Published:
Urban traffic management embedding graph theory, linear algebra, and calculus into C++ and JAX to optimize signal timing for city planners.
Volatility Alchemist: Quantitative Options Trading
Published:
End-to-end quant options trading system with real-time data integration, ML volatility models, interactive dashboards, and automated signal generation.
GameNGen: Diffusion World Model for Game Simulation
Published:
Trained a latent diffusion world model on 737K+ Super Mario Bros frames with VAE encoder, CNN reward model, and PPO agents.
Market Microstructure Forecasting with Deep RL
Published:
DRL agent predicting short-horizon price movements from order book snapshots and executing trades via event-driven backtesting.
NFL Veteran Transition: Causal Inference on Player Performance
Published:
Hierarchical mixed-effects models and ML ensembles to isolate the effect of team transitions from individual skill trajectories in NFL player data.
ACL Injury Risk Predictor
Published:
ML pipeline predicting ACL injury risk from biomechanical and performance data, combining sports science domain knowledge with gradient boosting and interpretability tools.
MOSAIC: Calibrated Multi-Stream Outbreak Early Warning
Published:
Fuses wastewater, genomic, and outbreak-text surveillance into one calibrated probability that transmission is growing right now, and proves the number is trustworthy.
VeriGrad RL: Mechanistic Interpretability for Safety RL
Published:
An open-source mechanistic interpretability and AI-safety lab for RL post-training: train policies to choose activation-level interventions, then verify they’re behaviorally safe, useful, and mechanistically faithful.
Popper: Falsifying Specifications Before You Prove Them
Published:
An open-source tool that hunts for counterexamples to mathematical and logical statements, catching wrong specifications rather than just mismatched proofs.
RallyScope: Tennis ML & Computer Vision in the Browser
Published:
36,342 ATP/WTA matches turned into an unsupervised playstyle map, an exactly-explainable win-probability model, and an in-browser ball tracker, trained at build time and inferred client-side.
PodBench: Agent Evaluation at Fleet Scale
Published:
Deterministic, resettable task environments for LLM agents with a programmatic verifier, per-run token/cost metering, and Kubernetes autoscaling: pod health and model behavior on one pane.
Context Forge: The Pareto Frontier of Prompt Compression
Published:
An open, reproducible benchmark of context compression (tokens saved vs. quality retained vs. latency) across the tokenizers production apps actually pay for, on real public data.
Shannon’s Gambit: A Chess Engine That Learns at an Honest Rating
Published:
An end-to-end chess RL system that routes each position to the method that owns it, retrains itself nightly by gated self-play, and reports only the Elo Stockfish says it can actually play.
Covera: An Insurance Marketplace That Texts You the Right Plan
Published:
A multi-agent concierge you text like a person: it simulates thousands of years of your real care against every real plan, ranks on risk-adjusted all-in cost, and stays on as a year-round advocate.