Mingda Qiao

Mingda Qiao is a postdoc at MIT, and an incoming assistant professor at UMass Amherst (starting Fall'25). His research focuses on the theory of prediction, learning, and decision-making in sequential settings, as well as collaborative federated learning. Prior to MIT, Mingda was a FODSI postdoc at UC Berkeley, received his PhD in Computer Science from Stanford University, and received his BEng in Computer Science from Tsinghua University.