Software Engineer & Computational Finance Researcher

Shipping features for Mantis, the lab's swarm-intelligence software, alongside research on financial representation learning.

• Developed production features and bug-fixes for Mantis (lab software) using React, TypeScript, FastAPI, Zustand, and Docker.
• Designed full-stack swarm intelligence simulator Mantis feature, modeling evolving agent representations using aligned UMAP.
• Trained 4.9M-param financial time series transformer encoder on 24.8M observations (499 tickers, 12 features, 4,149 daily bars).
• Designed temporal/cross-asset architecture extending temporal neighborhood encoding (TNC) with graph convolution layers and forward-aligned objectives over 120-day historical correlations or learned attention; submitted to ICLR 2027.
• Benchmarked 9 representations across 21 targets, 3 horizons, and 3 seeds on 37,500 embargoed windows; at 21 days, achieved +0.110 relative-volatility and +0.090 beta rank-IC lift over strongest baselines with under 0.015 seed variation.