Srijan Sood is an AI Research Lead and Vice President at J.P. Morgan AI Research, where he leads a team conducting foundational research at the intersection of artificial intelligence and finance. His current work focuses on generative foundation models for market microstructure, deep reinforcement learning for dynamic portfolio optimization, and knowledge graphs for financial analysis.
As a founding member of J.P. Morgan’s AI Research group led by Dr. Manuela Veloso, Srijan has presented research to the JPMC Operating Committee and CEO, and cultivated university partnerships with Columbia, CMU, and BreakThrough AI.
He holds M.Sc. and B.Sc. degrees in Computer Science from Georgia Institute of Technology, where he researched reinforcement learning for language model alignment with Dr. Mark Riedl and domain adaptation with Dr. Charles Isbell.
Research Interests#
- Generative foundation models for financial markets
- Deep reinforcement learning for portfolio optimization
- Knowledge graphs and LLMs for financial analysis
- Fairness in machine learning