Sanmi Koyejo

Sanmi Koyejo, an assistant professor at the University of Illinois, dives into the intricacies of machine learning metrics and robust distributed learning. He highlights how traditional metrics fail in real-world decision-making, proposing innovative methods like pairwise preferences for better performance evaluation. The discussion also covers cognitive radio technology, promoting efficient spectrum use, and addresses the challenges of adversarial attacks in distributed training. Sanmi's interdisciplinary research uniquely blends cognitive science with machine learning, paving the way for more adaptive systems.