Embedded Files
About
About
My research focuses on designing algorithmic and AI systems that work well with people to improve joint human-algorithm performance. I study human-algorithm interaction in decision-making settings -- from online markets and decision-support systems to interactive AI assistants. I ask how these systems should be designed to account for human behavior and to support users who learn and adapt through repeated interactions with the algorithm. My goal is to improve not only immediate performance, but also human learning and longer-term outcomes. My work combines behavioral data and experiments, theoretical models, and machine learning, drawing on computer science, economics, and psychology.
I am a Postdoctoral Associate in Computer Science at Cornell University, hosted by Jon Kleinberg and Éva Tardos, where I am also a member of the AI, Policy and Practice (AIPP) group. Previously, I was a Postdoctoral Fellow at Harvard’s School of Engineering and Applied Sciences (SEAS), working (remotely, from Israel) with Yiling Chen and David Parkes. I earned my Ph.D. in Computer Science at the Hebrew University under the supervision of Noam Nisan, with a specialization through the Center for the Study of Rationality. During my Ph.D., I was an Adams Fellow of the Israel Academy of Sciences and Humanities. I hold a B.Sc. in Computer Science and Cognitive Sciences, as well as an M.Sc. in Computer Science, both from the Hebrew University of Jerusalem.
Contact
Contact
Office: 322 Gates Hall, Cornell University, Ithaca, NY, 14853.
Email: gn242 at cornell dot edu
Research
Research
Papers:
Papers:
AI-Assisted Decision Making with Human Learning (EC 2025)
Gali Noti, Kate Donahue, Jon Kleinberg, and Sigal Oren [link]Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces (ICLR 2024)
Omer Nahum, Gali Noti, David C. Parkes, and Nir Rosenfeld [link]Learning When to Advise Human Decision Makers (IJCAI 2023)
Gali Noti and Yiling Chen [full version on ArXiv] [dataset]
[talk at the ACM SIGecom Winter Meeting 2024]Bid Prediction in Repeated Auctions with Learning (WWW 2021)
Gali Noti and Vasilis Syrgkanis [link]From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions (AAAI 2021)
Gali Noti [link]Neural Networks for Predicting Human Interactions in Repeated Games (IJCAI 2019)
Yoav Kolumbus and Gali Noti [link]Do Humans Play Equilibrium? Modeling Human Behavior in Computational Strategic Systems (XRDS 2017)
Gali Noti [link]A "Quantal Regret" Method for Structural Econometrics in Repeated Games (EC 2017)
Noam Nisan and Gali Noti [link] [Full Version on Arxiv]An Experimental Evaluation of Regret-Based Econometrics (WWW 2017)
Noam Nisan and Gali Noti [link]ERA: A Framework for Economic Resource Allocation for the Cloud (WWW 2017, invited by the industry track)
Moshe Babaioff, Yishay Mansour, Noam Nisan, Gali Noti, Carlo Curino, Nar Ganapathy, Ishai Menache, Omer Reingold, Moshe Tennenholtz, and Erez Timnat [link]An experimental evaluation of bidders' behavior in ad auctions (WWW 2014)
Gali Noti, Noam Nisan, and Ilan Yaniv [link]
Technical Reports:
Technical Reports:
Behavior-Based Machine-Learning: A Hybrid Approach for Predicting Human Decision Making
Gali Noti, Effi Levi, Yoav Kolumbus, Amit Daniely [link]
Page updated
Google Sites
Report abuse