Yahav Bechavod
yahav [at] seas [dot] upenn [dot] edu

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I am a Postdoctoral Researcher at the School of Engineering and Applied Science at the University of Pennsylvania, working with Prof. Aaron Roth and Prof. Michael Kearns. I am also part of the Penn CS Theory Group. Prior to joining Penn, I earned my PhD from the School of Computer Science and Engineering at the Hebrew University of Jerusalem, during which I was also an Apple Scholar in AI/ML. My research interests are primarily in algorithms, machine learning, and game theory, and specifically in the areas of fairness in machine learning, online learning, and learning in the presence of strategic behavior. I am honored to be the recipient of several awards and fellowships, including the Israeli Council for Higher Education Postdoctoral Fellowship, the Apple Scholars in AI/ML PhD Fellowship, and the Charles Clore Foundation PhD Fellowship. At Penn, I am also an AI x Science Fellow at the School of Arts & Sciences.

• Individual Fairness in Online Classification
• • UPenn CS Theory Seminar. February 2023.
  • Theory of Computation for Fairness (A Simons Foundation Collaboration) Online Seminar. February 2023. Video here.
• Individually Fair Learning with One-Sided Feedback
• • ICML Workshop: Responsible Decision Making in Dynamic Environments. Contributed Talk. July 2022. Video here.
• Information Discrepancy in Strategic Learning
• • ICML Spotlight Presentation. July 2022. Video here.
• Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
• • AISTATS Poster Presentation. April 2021.
• Metric-Free Individual Fairness in Online Learning
• • KLA PhD Awards Ceremony. July 2021.
  • Apple Machine Learning Speaker Series. June 2021.
  • Symposium on the Foundations of Responsible Computing (FORC). June 2021. Video here.
  • Machine & Deep Learning Israel. December 2020.
  • NeurIPS Oral Presentation. December 2020. Video here.
  • NeurIPS Poster Presentation. December 2020.
  • Hebrew University Avdanced Seminar in Machine Learning. November 2020. Video here.
• A Brief Introduction to Algorithmic Fairness
• • Hebrew University Federmann Center for the Study of Rationality. February 2020.
  • Special Presentation for Google’s APM Program. June 2018.
• Equal Opportunity in Online Classification with Partial Feedback
• • NeurIPS Poster Presentation. December 2019.
  • Simons Institute Workshop on Developments in Research on Fairness. July 2019. Video here.
• Adversarial Bandits - Regret Bounds and Analysis
• • Hebrew University Advanced Topics in Machine Learning Seminar. May 2018.

Workshops & Panels

• NeurIPS 2021 Workshop: Learning and Decision-Making with Strategic Feedback (StratML)
  Virtual. December 2021. Video here.
• FORC 2021 Panel: Translation of Fair Learning to Practice
  Virtual. June 2021. Link here.

• Journal Refereeing
• • Journal of Machine Learning Research (JMLR)
• Conference Program Committee
• • International Conference on Machine Learning (ICML): 2022, 2023, 2024
  • Conference on Neural Information Processing Systems (NeurIPS): 2021, 2022, 2023
  • ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT): 2021
• Conference Auxilary Reviewer
• • Innovations in Theoretical Computer Science (ITCS): 2023
  • AAAI Conference on Artificial Intelligence, Ethics and Social Intelligence (AIES): 2019
• Ethical Reviewer
• • Conference on Neural Information Processing Systems (NeurIPS): 2021, 2022, 2023
• Workshop Organizing
• • NeurIPS 2021 Workshop on Learning and Decision-Making with Strategic Feedback. View here.

2024-2025: Penn Arts & Sciences AI x Science Fellow
2023-2025: Israeli Council for Higher Education Postdoctoral Fellowship in Data Science
2020-2022: Apple Scholars in AI/ML PhD Fellowship
2020-2023: Charles Clore Foundation PhD Fellowship
2022: KLA Award for Excellent PhD Students