Srijan Sood is a Vice President and founding member of J.P. Morgan AI Research, led by Dr. Manuela Veloso (former head of ML at CMU). He leads a team building AI systems that learn market dynamics from trade-level data – from generative foundation models for market microstructure to reinforcement learning for portfolio optimization. Srijan has presented research to the J.P. Morgan Operating Committee and CEO, and built university partnerships with Columbia, CMU, and BreakThroughAI.

His team built TradeFM, a foundation model for financial markets, trained on billions of trades, that learns universal price-formation dynamics and generalizes across unseen markets and liquidity regimes. Srijan also architected a global-scale trade monitoring system processing billions of monthly transactions across 4 international markets, and led deep RL research for portfolio optimization, adopted by an institutional client and presented across hedge funds, banks, and asset managers.

Originally from New Delhi, he attended St. Columba's School before earning his M.Sc. and B.Sc. (Highest Honors) in Computer Science from Georgia Institute of Technology, where he researched reinforcement learning for language model alignment with Dr. Mark Riedl, equities portfolios with Dr. Tucker Balch, and domain adaptation with Dr. Charles Isbell. Srijan lives in New York City.