
About
Sanmi Koyejo is an Assistant Professor at Stanford University's Department of Computer Science and an Adjunct Associate Professor at the University of Illinois at Urbana-Champaign. He leads the Stanford Trustworthy AI Research (STAIR) group, focusing on developing principles for robust and ethical machine learning, with applications in healthcare and neuroimaging. His work spans federated learning, metric elicitation, generative models, and interpretable AI.
He holds a PhD from the University of Texas at Austin and completed postdoctoral research at Stanford. His research is supported by grants from NSF, NIH, DARPA, and industry partnerships. Notable awards include the Frederick E. Terman Faculty Fellowship, NSF CAREER Award, and the Skip Ellis Early Career Award.
Key research interests include trustworthy AI, distributed learning security, fairness metrics, and biomedical imaging. His lab has developed frameworks like CSER for secure federated learning and contributed to healthcare applications such as diabetes detection from X-rays.
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