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McKelvey School of Engineering

Closing the Loop: Bringing Humans into Empirical Computational Social Choice and Preference Reasoning

Friday, September 17 | 11:00 AM - 12:00 PM

Stephen F. & Camilla T. Brauer Hall, Brauer 12
6548 Forest Park Pkwy, St. Louis, MO 63112, USA

Dr. Nicholas Mattei

Research in both computational social choice and preference reasoning uses tools and techniques from computer science, generally algorithms and complexity analysis, to examine topics in group decision making. This has brought tremendous progress in the last decades, creating new avenues for research and results in areas including voting and resource allocation. I argue that of equal importance to the theoretical results are the impacts in research and development from the empirical part of the computer scientists toolkit: data, system building, and human interaction. I detail some recent work that aims to establish streams of data and application driven research in the computational social choice and preference reasoning areas. Along the way, I highlight interesting application domains and important results from the community in driving this area to make concrete, real-world impact as well as important intersections with the larger discussion around artificial intelligence technology and its impact on society.

Please note that for all in-person events, attendees must adhere to Washington University’s public health requirements, including the latest events and meetings protocol. Guests will be required to show a successful self-screening result and wear a mask at all times. 

Event Type



McKelvey School of Engineering


Science & Technology

Computer Science & Engineering
Event Contact


Speaker Information

Nicholas Mattei is an assistant professor of computer science at Tulane University. His research focuses on the theory and practice of artificial intelligence, machine learning, data science, and the impact of these technologies on society.  He is motivated by both creating new systems and technologies and by educating others about the possibilities and opportunities of computer science.  His research leverages theory, data, and experiments to create novel algorithms, mechanisms, and systems that enable and support autonomous agents and/or humans to make better decisions both individually and in groups. His work has been funded by the National Science Foundation, an IBM Faculty Research Award, a Google Research Scholar Award, and the Department of Education. Before joining Tulane he was a research staff member at IBM Research in Yorktown Heights, New York; a senior researcher at the Commonwealth Scientific and Industrial Research Organization (CSIRO) / Data61 (formerly NICTA) and the University of New South Wales in Sydney, Australia; and an Aerospace Technology Engineer at NASA Ames Research Center in Mountain View, California. He received his PhD in 2012 from the University of Kentucky.

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