CMU Econ-CS Seminar Series

Archive: Spring 2026
Back to Fall 2026 (Current)

About the Econ-CS Seminar Series

This is the home page for the Econ-CS Seminar Series at the School of Computer Science of Carnegie Mellon University. The faculty coordinator is Vincent Conitzer and the student coordinator is Emin Berker. The mailing list for upcoming EconCS Seminar talk announcements is on the SCS mailman server and available here. Unless otherwise noted, the meetings are on Tuesdays at 2:00 PM Eastern Time (always available virtually, and usually in person in GHC 8102).

This seminar aims to cover a wide variety of topics at the intersection of economics and computer science, such as game theory, learning theory, mechanism design, societal/economic etc. Please contact Emin for arrangements or questions about this page.

Schedule - Spring 2026

Date & Time Location Speaker Affiliation Title
January 22, 2026
1:00 PM		 GHC 4405
Zoom		 Fabian Pieroth Technical University of Munich Equilibrium Learning – Towards Understanding Algorithmic Markets
February 11, 2026
2:00 PM		 GHC 8102
Zoom		 Ratip Emin Berker and Emanuel Tewolde Carnegie Mellon University On the Edge of Core (Non-)Emptiness: An Automated Reasoning Approach to Approval-Based Multi-Winner Voting
February 25, 2026
2:00 PM		 GHC 8102
Zoom		 Yanru Guan Peking University Ex-Ante Truthful Distribution-Reporting Mechanisms
March 18, 2026
2:00 PM		 GHC 8102
Zoom		 Emily Diana Carnegie Mellon University Minimax Group Fairness in Strategic Classification
March 25, 2026
2:00 PM		 GHC 8102
Zoom		 Madeline Kitch Carnegie Mellon University Learning What Evaluators' Value: A Reliable Approach to Modeling Evaluator Preferences
April 8, 2026
2:00 PM		 GHC 8102
Zoom		 Mario Günther Panthéon Sorbonne Equal Say as Sum Normalization
April 15, 2026
2:00 PM		 GHC 8102
Zoom		 Itai Zilberstein Carnegie Mellon University Near-Optimal Dynamic Matching via Coarsening with Application to Heart Transplantation
June 24, 2026
2:30 PM		 GHC 9115
Zoom		 Tao Lin Microsoft Research Information Design with Large Language Models

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