Saee Paliwal Email & Phone Number | I am a highly trained interdisciplinary researcher with 10+ years of experience developing state-of-the- art machine learning algorithms, spanning variational methods, reinforcement learning, recommender systems, and generative AI. As an AI Scientist at BenevolentAI, I have had the opportunity to help build BAI’s foundational AI stack, including tensor factorization models for graph-based link prediction, causal inference algorithms using Pseudo-Riemannian manifolds, and, most recently, large language models for biomedical Q&A. I also helped develop BAI’s core AI evaluation framework, to optimally adapt AI innovations to multi-modal biomedical data. As Director of AI Science at BAI, I lead the data science function within the AI function, and set the company’s data science strategy and roadmap. Formerly, in my doctorate, I focused on developing reinforcement learning algorithms of human decision-making under uncertainty, with the aim of creating a mechanistic, computational assay of mental illnesses, specifically, of behavioral addictions. I am passionate about working side-by-side with domain experts to help foster trust between humans and algorithms, in order to deliver impactful solutions to complex, interdisciplinary problems. I deeply value sharing my skills and knowledge in order to help develop others, and am committed to creating inclusive, diverse workplaces that celebrate and foster every individual’s unique skill set.

Saee Paliwal

I am a highly trained interdisciplinary researcher with 10+ years of experience developing state-of-...
Brooklyn, New York, United States

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Saee Paliwal’s Location Brooklyn, New York, United States

Saee Paliwal’s Current Industry Nvidia Benevolentai

Saee Paliwal’s Prior Industry Ponder | Fdo Partners

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Manager, Drug Discovery AI

2024-01-01 00:00:00 - Present

NYC Site Lead

2022-06-01 00:00:00 - Present

Co-Founder

2014-01-01 00:00:00 - 2015-06-01 00:00:00

Vice President, Research and Trading

2007-07-01 00:00:00 - 2011-03-01 00:00:00

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Saee Paliwal is a I am a highly trained interdisciplinary researcher with 10+ years of experience developing state-of-the- art machine learning algorithms, spanning variational methods, reinforcement learning, recommender systems, and generative AI. As an AI Scientist at BenevolentAI, I have had the opportunity to help build BAI’s foundational AI stack, including tensor factorization models for graph-based link prediction, causal inference algorithms using Pseudo-Riemannian manifolds, and, most recently, large language models for biomedical Q&A. I also helped develop BAI’s core AI evaluation framework, to optimally adapt AI innovations to multi-modal biomedical data. As Director of AI Science at BAI, I lead the data science function within the AI function, and set the company’s data science strategy and roadmap. Formerly, in my doctorate, I focused on developing reinforcement learning algorithms of human decision-making under uncertainty, with the aim of creating a mechanistic, computational assay of mental illnesses, specifically, of behavioral addictions. I am passionate about working side-by-side with domain experts to help foster trust between humans and algorithms, in order to deliver impactful solutions to complex, interdisciplinary problems. I deeply value sharing my skills and knowledge in order to help develop others, and am committed to creating inclusive, diverse workplaces that celebrate and foster every individual’s unique skill set.