School of Engineering
Showing 241-250 of 6,800 Results
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Jacy Reese Anthis
Graduate, Computer Science
BioJacy Anthis is a computational social scientist researching human-AI interaction and machine learning, particularly the rise of "digital minds" and how humanity can work together with highly capable AI systems. His research has been published in top academic venues, such as CHI, HRI, and NeurIPS, and featured in global media outlets, such as Vox, Forbes, and The Guardian. Anthis has presented his work at conferences and seminars in over 20 countries. He is a co-founder of the nonprofit research organization Sentience Institute, a PhD candidate at the University of Chicago, and currently a visiting scholar at the Institute for Human-Centered AI (HAI) at Stanford University. He lives in San Francisco with his wife Kelly Anthis and their adopted dogs Apollo and Dio(nysus).
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Yann Aouidef
Postdoctoral Scholar, Management Science and Engineering
BioYann Aouidef is a PhD candidate at the Paris Center of Law and Economics, in applied Mathematics in Economics : Game Theory, Social Choice Theory, Law and Economics.
He's currently a VSR at Stanford with interests in Computational Contracts applied to Smartcontracts. -
Siddharth Aphale
Graduate, Stanford Center for Professional Development
BioHi, I am a data scientist working on cloud battery analytics and a part time student at Stanford University pursuing a Graduate Certificate in Artificial Intelligence. My work focuses on developing diagnostic and prognostic methods at the intersection of probabilistic machine learning and physics-based modeling for battery packs used in automotive and energy storage applications.
My research interests span post training and reinforcement learning for large language models and embodied agents, aiming for policies that are robust and generalize out of distribution. I am currently exploring deep RL and expressive policies, along with the post training dynamics that govern how these methods behave at scale. My most recent focus is the intersection of vision language action (VLA) models and policy alignment, improving generalization through language feedback and multimodal reasoning.
