Summary
Saee Paliwal is an interdisciplinary AI leader with 12 years of experience applying cutting-edge machine learning to drug discovery, bridging academic rigor from a PhD in Machine Learning and Computational Cognitive Science with product-focused roles at BenevolentAI and NVIDIA. She has built foundational AI stacks—including tensor factorization for graph link prediction, causal inference on Pseudo-Riemannian manifolds, and large language models for biomedical Q&A—while establishing evaluation frameworks and data science roadmaps that translate research into robust, human-in-the-loop pipelines. As a site lead and manager she combines people leadership with technical stewardship, growing teams, setting scientific direction, and championing inclusive cultures that develop others. Her background in modeling human decision-making and prior quantitative trading experience give her a rare blend of mechanistic understanding, probabilistic thinking, and practical risk-aware engineering.
12 years of coding experience
6 years of employment as a software developer
Research Rotation Bayesian Cognitive Modelling and Probabilistic Programming, Research Rotation Bayesian Cognitive Modelling and Probabilistic Programming at Massachusetts Institute of Technology
BA Physics, BA Physics at Harvard University
Doctor of Philosophy - PhD Machine Learning and Computational Cognitive Science, Doctor of Philosophy - PhD Machine Learning and Computational Cognitive Science at ETH Zürich
German, German, Spanish, French