Dr. Sharon Zhou teaches some of the most popular AI courses on Coursera, DeeplearningAI, and Stanford, including Intro to Post-Training: Fine-Tuning and Reinforcement Learning for LLMs, which serves as a complementary course for her forthcoming book, AI Post-training. She has also taught other courses like Fine-Tuning LLMs and Diffusion Models, and spoke at ~50 keynotes/talks in 2024, reaching millions of developers and executives. She continues to create new courses, for a developer audience with DeeplearningAI and for a professional audience with Harvard University.

Previously, as a Stanford adjunct faculty member, she led a 50-person AI research group, published award-winning papers in AI, and taught Generative Adversarial Networks. She is the VP of AI at AMD, where she leads AI research and education. Prior to that, she was the founder and CEO of Lamini, an AI post-training startup that won last year’s VentureBeat Generative AI Startup Award and has been recognized as a Forbes Cloud 100 Rising Star.

She earned her PhD from Stanford, advised by Dr. Andrew Ng and co-advised by Dr. Stefano Ermon. Before her PhD, she worked as an AI product manager at Google. Sharon received her bachelor's degree in Classics and computer science from Harvard. Additionally, she’s served as an AI advisor in Washington, DC, and has been featured in MIT Technology Review’s 35 Under 35 list.