Azalia Mirhoseini

Azalia Mirhoseini is an Assistant Professor in the Computer Science Department at Stanford University. Her research interest is in developing capable, reliable, and efficient AI systems for high-impact, real-world problems. Some of her past work includes Mixture-of Experts (MoE) neural architectures, now commonly used in frontier generative AI models, and reinforcement learning for chip design, which was published in Nature and used to design multiple generations of sub-10nm Google AI accelerators. Before Stanford, Prof. Mirhoseini spent several years in industry AI labs, including Anthropic and Google Brain. At Anthropic, she worked on advancing the capabilities and reliability of foundation models. At Google Brain, she co-founded and led the ML for Systems team, focusing on automating and optimizing computer systems and chip design. Currently, she also spends time at Google DeepMind, contributing to the Gemini project. Prof. Mirhoseini earned her PhD in Electrical and Computer Engineering from Rice University. Her work has been recognized through the MIT Technology Reviews 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship AI and systems venues, and coverage by various media outlets, including MIT Technology Review, IEEE Spectrum, The Verge, The Times, and WIRED.