Theory Seminar: Decision Making under Uncertainty and Strategic Behavior

Abstract: The emergence of internet-based markets, automated decision-making tools, and the consideration of societal factors in algorithms have led to new standards and criteria for algorithm design. These applications have inspired the study and development of algorithms that go beyond classical settings and can adapt to uncertain decision-making and strategic behavior. In this talk, I will provide an overview of my research and contributions in this field and demonstrate how techniques from mechanism design, online optimization, and machine learning can help us solve these problems. I will focus on applications in search problems and the classification of strategic entities.

Bio: Hedyeh Beyhaghi is a postdoctoral research associate in the School of Computer Science at Carnegie Mellon University, hosted by Maria-Florina Balcan. Her research interests lie in algorithmic game theory and mechanism design, machine learning theory, and algorithms under uncertainty. Hedyeh received her Ph.D. in Computer Science from Cornell University, advised by Eva Tardos. Before joining CMU, Hedyeh was a postdoctoral research fellow at Toyota Technological Institute at Chicago (TTIC) and Northwestern University, where she was hosted by Avrim Blum, Jason Hartline, and Samir Khuller.

Refreshments will be served.