Welcome!


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

I am an Apple PhD Fellow in AI/ML and a recipient of the Charles Clore Foundation PhD Fellowship.

Updates:
[Oct-15-2020] Added slides for "Metric-Free Individual Fairness in Online Learning".
[Sep-29-2020] 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

Causal Feature Discovery through Strategic Modification
[arXiv] [Video]
Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani


Publications

Metric-Free Individual Fairness in Online Learning
[arXiv] [Video] [Slides]
Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu
Conference on Neural Information Processing Systems (NeurIPS) 2020
Selected for oral presentation (105/9454 submissions)


Equal Opportunity in Online Classification with Partial Feedback
[arXiv] [Conference Version] [Talk From 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]
Yahav Bechavod, Katrina Ligett
Fairness, Accountability and Transparency in Machine Learning (FAT/ML) 2017

About Me


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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

Phone: +972-2-549-4597

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