Keynote Speakers

Dr. Sharon Zhou is the VP of AI at AMD and was the founder and CEO of Lamini, an AI startup that won last year’s VentureBeat Gen AI Startup Award and has been recognized as a Forbes Cloud 100 Rising Star. As a former faculty member at Stanford, she led a 50+ person Generative AI research group and published award-winning papers in generative AI. Sharon teaches some of the most popular AI courses on Coursera, including Fine-tuning LLMs and Diffusion models, reaching millions of developers and executives. She earned her PhD in AI from Stanford, where she was advised by Dr. Andrew Ng. Before her PhD, she worked as an AI product manager at Google. She received her bachelor’s degree in computer science and Classics from Harvard. Additionally, Sharon has served as an AI advisor in Washington, D.C., and has been featured in MIT Technology Review’s 35 Under 35 list.

Professor Eric P. Xing is the President of the Mohamed bin Zayed University of Artificial Intelligence, Professor of Computer Science at Carnegie Mellon University, and Chief Scientist at GenBio AI. His main research interests are the development of machine learning and statistical methodology, and large-scale computational system and architectures, for solving problems involving automated learning, reasoning, and decision-making in artificial, biological, and social systems. Prof. Xing has served on the editorial boards of leading scientific journals including the Journal of the American Statistical Association, Annals of Applied Statistics, PLOS Journal of Computational Biology, IEEE Journal of Pattern Analysis and Machine Intelligence, Machine Learning Journal, and Journal of Machine Learning Research. He was elected Fellows AAAI, ACM, ASA, IEEE, and IMS.

Nathan is a machine learning researcher who works on building, understanding, and advocating for open language models and other responsible autonomous systems.

He is currently a post-training lead at the Allen Institute for AI.

I am an Associate professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. In my research, I focus on algorithms that can enable autonomous agents to acquire complex behaviors through learning, especially general-purpose methods that could enable any autonomous system to learn to solve any task. Applications of such methods include robotics, as well as a range of other domains that require autonomous decision making. To see a more formal biography, click here.

Robert Nishihara is one of the co-founders of Anyscale and one of the co-creators of Ray, the leading open source framework for scalable AI. He did his PhD in machine learning and distributed systems in the computer science department at UC Berkeley. Before that, he majored in math at Harvard.

Ion Stoica is a Professor in the EECS Department and holds the Xu Bao Chancellor Chair at the University of California at Berkeley, the Director of Sky Computing Lab, and the Executive Chairman of Databricks and Anyscale. He is currently doing research on AI systems and cloud computing, and his work includes numerous open-source projects such as SkyPilot, vLLM, ChatBot Arena , Ray and Apache Spark. He is a Member of National Academy of Engineering, an Honorary Member of the Romanian Academy and an ACM Fellow. He also co-founded three companies, Anyscale (2019), Databricks (2013) and Conviva (2006)

Professor Anandkumar’s research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. Tensor decomposition methods are embarrassingly parallel and scalable to enormous datasets. They are guaranteed to converge to the global optimum and yield consistent estimates for many probabilistic models such as topic models, community models, and hidden Markov models. More generally, Professor Anandkumar has been investigating efficient techniques to speed up non-convex optimization such as escaping saddle points efficiently.

Matt White is the Executive Director of the PyTorch Foundation and GM of AI at the Linux Foundation. He is also the Director of the Generative AI Commons, an open community initiative focused on advancing responsible generative AI under the LF AI & Data Foundation. Matt has nearly 30 years of experience in applied research and standards in AI and data in telecom, media and gaming industries. He began his career programming expert systems in the telecom industry and since 2012 has been focused on machine learning and research at the intersection of AI, simulations and multi-sensory learning. Matt is the Co-founder and Chair of the Open Metaverse Foundation at the Linux Foundation. He is also a Chair at the Metaverse Standards Forum and runs the Silicon Valley Generative AI paper reading group and is a co-organizer at the GenAI Collective.