Welcome!

Yahav Bechavod, The Hebrew University

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I am a PhD student at the School of Computer Science and Engineering at the Hebrew University of Jerusalem, advised by Amit Daniely and Katrina Ligett.

My research explores foundational questions in Algorithmic Fairness, Differential Privacy and Learning Theory. I have also worked on and have an ongoing interest in learning in the presence of strategic behavior.

My research is generously supported by the Apple Scholars in AI/ML PhD Fellowship.

I am involved with "TOC4Fairness", a research collaboration on the theory of Algorithmic Fairness, funded by The Simons Foundation, where I also co-manage a blog about Algorithmic Fairness, under the direction of Omer Reingold.

Updates:
[Feb-11-2021] I have been named a recipient of the KLA Outstanding Doctoral Research Award.
[Jan-24-2021] Our new work "Gaming Helps! Learning from Strategic Interactions in Natural Dynamics" will be presented at AISTATS 2021!
[Jan-18-2021] Check out our new "TOC4Fairness" research collaboration seminar series and blog, starting this week!
[Nov-26-2020] I gave a talk about our new paper, "Metric-Free Individual Fairness in Online Learning", at The Hebrew University Advanced Seminar in Machine Learning. The video is here.
[Oct-15-2020] Our work "Metric-Free Individual Fairness in Online Learning" has been selected for oral presentation at NeurIPS 2020!
[Jul-02-2020] Our new paper "Metric-Free Individual Fairness in Online Learning" will be featured at the Participatory Approaches to Machine Learning and Human in the Loop Learning workshops at ICML 2020, and at the Workshop on Mechanism Design for Social Good.
[Jun-30-2020] Check out our new paper "Causal Feature Discovery through Strategic Modification" featured at the Incentives in Machine Learning workshop at ICML 2020!
[Sep-03-2019] Our new work "Equal Opportunity in Online Classification with Partial Feedback" has been accepted to NeurIPS 2019!
[Aug-01-2019] I will be visiting Microsoft Research New England August 5-9, 2019.
[Jul-06-2019] I will be presenting our new paper "Equal Opportunity in Online Classification with Partial Feedback" as part of the Recent Developments in Research on Fairness workshop at Simons Institute. Slides are available here.
[May-10-2019] Excited to take part in the Summer Cluster: Algorithmic Fairness program at Simons Institute!

Publications




Preprints

Information Discrepancy in Strategic Learning
[arXiv]
Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, Juba Ziani
In Submission


Publications

Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
[arXiv] [Conference Version] [Video] [Slides]
Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani
To Appear in Conference on Artificial Intelligence and Statistics (AISTATS 2021)


Metric-Free Individual Fairness in Online Learning
[arXiv] [Conference Version] [Talk at HUJI ML Seminar] [Slides]
Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu
Conference on Neural Information Processing Systems (NeurIPS 2020)
Selected for Oral Presentation (1.1% Selection rate, 105/9467 submissions.)


Equal Opportunity in Online Classification with Partial Feedback
[arXiv] [Conference Version] [Talk at Simons] [Slides]
Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
Conference on Neural Information Processing Systems (NeurIPS 2019)


Penalizing Unfairness in Binary Classification
[arXiv] [Slides] [Code]
Yahav Bechavod, Katrina Ligett
Fairness, Accountability and Transparency in Machine Learning (FAT/ML 2017)

Talks





  • Metric-Free Individual Fairness in Online Learning
    • Machine & Deep Learning Israel. December 2020. Video here.
    • NeurIPS Oral Presentation. December 2020. Video here.
    • Hebrew University Avdanced Seminar in Machine Learning. November 2020. Video here.
  • An Introduction to Algorithmic Fairness
    • Hebrew University Federmann Center for the Study of Rationality. February 2020.
  • Equal Opportunity in Online Classification with Partial Feedback
    • Simons Institute Workshop on Recent Developments in Research on Fairness. July 2019. Video here.

About Me

Yahav Bechavod, The Hebrew University

Yahav Bechavod, The Hebrew University

Yahav Bechavod, The Hebrew University




My research explores foundational questions in the fields of Algorithmic Fairness, Differential Privacy and Learning Theory. I have also worked on and have ongoing interest in settings where machine learning algorithms interact with strategic behavior.

In 2019, I had the privilege of spending an amazing summer at Berkeley, California, visiting the Simons Institute as a participant in the Summer Cluster: Algorithmic Fairness program.

In the Fall of 2017, I was fortunate to visit the University of Pennsylvania at the invitation of Aaron Roth and Michael Kearns.

I received both my MSc (Computer Science, Summa Cum Laude) and BSc (Computer Science and Mathematics) from the Hebrew University.

In my spare time, I shoot select 3-pointers on select basketball courts, speak fluent Arabic and not-so-fluent Japanese, blog about CS and non-CS stuff, and travel to cool places on pandemic-less times.

Contact Me

Rothberg Family Bulidings A-435, Givat Ram Campus, Jerusalem, Israel

Office: +972-2-549-4597

Email: yahav [dot] bechavod [at] cs.huji.ac.il