Abstract: Fair division is a problem of dividing a set of items among heterogeneous agents in a fair and efficient manner. This age-old problem, mentioned even in the Bible, arises naturally in a wide range of real-life settings. I will discuss recent advances on the computability of fair division, and possible applications to algorithmic fairness, machine learning, robotics, etc.. The last part will be more like a discussion.
Bio: Ruta Mehta is an Assistant Professor of Computer Science at the University of Illinois at Urbana-Champaign. Prior to joining UIUC, she was a postdoctoral fellow at the Simons Institute, UC Berkeley, and at the College of Computing, Georgia Tech. She did her Ph.D. from the Indian Institute of Technology Bombay, India. Her research interests lie in theoretical computer science and its interface with economics, games theory, fair division, and learning. For her research, she has received the NSF CAREER Award, the Simons-Berkeley Research Fellowship, and the Best Postdoctoral Award (given by CoC@GT). Her Ph.D. thesis won the ACM India Doctoral Dissertation Award and the IIT-Bombay Excellence in Ph.D. Thesis Award.