ECGI 2026

Yiling Chen is a Gordon McKay Professor of Computer Science at Harvard University. She received her Ph.D. in Information Sciences and Technology from the Pennsylvania State University. Prior to working at Harvard, she spent two years at Yahoo! Research in New York City. Her research lies in the intersection of computer science, economics and other social sciences, with a focus on incentive alignment of computational systems. She was a recipient of the Penn State Alumni Association Early Career Award and was selected by IEEE Intelligent Systems as one of "AI's 10 to Watch” early in her career. Her work received best paper awards at ACM EC, AAMAS, ACM FAT* (now ACM FAccT), and ACM CSCW conferences. She was a program co-chair for the 2013 Conference on Web and Internet Economics (WINE’13), the 2016 ACM Conference on Economics and Computation (EC’16), the 2018 AAAI Conference on Human Computation and Crowdsourcing (HCOMP’18), and the 2023 AAAI Conference on Artificial Intelligence (AAAI-23), and has served as an associate editor for several journals. 

Nika Haghtalab is an Associate Professor with tenure in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. She works broadly on problems related to machine learning, algorithms, economics, and society. Her work contributes to an emerging mathematical foundation for learning and decision-making systems in the presence of economic and societal forces. She received her Ph.D. from the Computer Science Department of Carnegie Mellon University, where her thesis won the CMU School of Computer Science Dissertation Award (ACM nomination) and the SIGecom Dissertation Honorable Mention. She is a co-founder of Learning Theory Alliance (LeT-All). Among her honors are an NSF CAREER award, Sloan fellowship, Schmidt Sciences AI2050 fellowship, NeurIPS and ICAPS best paper awards, an EC exemplary in AI track award, and several industry awards and fellowships.

Éva Tardos is a Jacob Gould Schurman Professor of Computer Science, was chair of the Department of Computer Science 2006-2010 and 2020-2023. She was Interim Dean for Computing and Information Sciences 2012-2013. She received her BA and PhD from Eötvös University in Budapest. Tardos’s research interest is algorithms and interface of algorithms and incentives.  She is most known for her work on quantifying the efficiency of selfish routing. She has been elected to the National Academy of Sciences, the National Academy of Engineering, the American Philosophical Society, the American Academy of Arts and Sciences, and external member of the Hungarian and Austrian Academies of Sciences. She is the recipient of a number of fellowships and awards including the Packard Fellowship, the Gödel Prize, Dantzig Prize, Fulkerson Prize, ETACS prize, the IEEE von Neumann Medal and the SIGecom Lifetime achievement award. She co-wrote the widely used textbook Algorithms Design. She has been Editor-in-Chief of the Journal of the ACM and of the SIAM Journal of Computing, has been editor of several other journals, and was program committee member and chair for several ACM and IEEE conferences, including ACM EC in 2013.