Rediet Abebe

Assistant Professor
Department of Electrical Engineering and Computer Sciences
University of California, Berkeley
Berkeley, CA 94720

Junior Fellow (on leave)
Society of Fellows
Harvard University
Cambridge, MA 02138

I am a 2022 Andrew Carnegie Fellow and an assistant professor in EECS at the University of California, Berkeley. I am also on leave as a Junior Fellow at Harvard University. My research examines the interaction of algorithms and inequality, with a focus on contributing to the scientific foundations of this area. I am serving on the Executive Committee for the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) and was a Program Co-Chair for the inaugural conference.

Selected Publications

  • Abebe, Rediet, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, and Rebecca Wexler. "Adversarial scrutiny of evidentiary statistical software." In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022.

  • Abebe, Rediet, Nicole Immorlica, Jon Kleinberg, Brendan Lucier, and Ali Shirali. "On the effect of triadic closure on network segregation." In Proceedings of the ACM Conference on Economics and Computation (EC), 2022. (Link)

  • Abebe, Rediet, Adam Eck, Christian Ikeokwu, and Samuel Taggart. "An algorithmic introduction to saving circles." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022. (Link)

  • Kasy, Maximilian, and Rediet Abebe. "Fairness, equality, and power in algorithmic decision-making." In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021. (Link)
    Accompanying piece: Abebe, Rediet and Maximilian Kasy. "The means of prediction."
    Boston Review (2021). (Link)

All Publications

  • Abebe, Rediet, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, and Rebecca Wexler. "Adversarial scrutiny of evidentiary statistical software." In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022.

  • Abebe, Rediet, Nicole Immorlica, Jon Kleinberg, Brendan Lucier, and Ali Shirali. "On the effects of triadic closure on network integration." In Proceedings of the ACM Conference on Economics and Computation (EC), 2022.

  • Abebe, Rediet, Adam Eck, Christian Ikeokwu, and Samuel Taggart. "An algorithmic introduction to saving circles." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022. (Link)

  • Kasy, Maximilian, and Rediet Abebe. "Fairness, equality, and power in algorithmic decision-making." In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021.
    Accompanying piece: Abebe, Rediet and Maximilian Kasy. "The means of prediction."
    Boston Review (2021). (Link)

  • Abebe, Rediet, Kehinde Aruleba, Abeba Birhane, Sara Kingsley, George Obaido, Sekou L. Remy, and Swathi Sadagopan. "Narratives and counternarratives on data sharing in Africa." In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021. (Project page)
    Preliminary version in the
    Privacy Law Scholars Conference (PLSC), 2020.

  • Satinsky, Emily N., Tomoki Kimura, Mathew V. Kiang, Rediet Abebe, Scott Cunningham, Hedwig Lee, Xiaofei Lin et al. "Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph. D. students." Scientific Reports 11, no. 1 (2021): 1-12.

  • Abebe, Rediet, Richard Cole, Vasilis Gkatzelis, and Jason D. Hartline. "A truthful cardinal mechanism for one-sided matching." In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2020.

  • Abebe, Rediet, Solon Barocas, Jon Kleinberg, Karen Levy, Manish Raghavan, and David G. Robinson. "Roles for computing in social change." In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT*), 2020.
    Preliminary version in the
    Privacy Law Scholars Conference (PLSC), 2019.

  • Abebe, Rediet, Salvatore Giorgi, Anna Tedijanto, Anneke Buffone, and H. Andrew Andrew Schwartz. "Quantifying community characteristics of maternal mortality using social media." In Proceedings of The Web Conference 2020 (TheWebConf), 2020.

  • Abebe, Rediet, Jon Kleinberg, and S. Matthew Weinberg. "Subsidy allocations in the presence of income shocks." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020.

  • Prins, Aviva, Aditya Mate, Jackson A. Killian, Rediet Abebe, and Milind Tambe. "Incorporating healthcare motivated constraints in restless bandit based resource allocation." In Challenges of Real-World Reinforcement Learning Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020.

  • Abebe, Rediet, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, and H. Andrew Schwartz. "Using search queries to understand health information needs in Africa." In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2019.

  • Broussard, Meredith, Nicholas Diakopoulos, Andrea L. Guzman, Rediet Abebe, Michel Dupagne, and Ching-Hua Chuan. "Artificial intelligence and journalism." Journalism & Mass Communication Quarterly 96, no. 3 (2019).

  • Abebe, Rediet, and Kira Goldner. "A report on the workshop on mechanism design for social good." ACM SIGecom Exchanges 16, no. 2 (2019).

  • Abebe, Rediet. "A conjectural Brouwer inequality for higher-dimensional Laplacian spectra." arXiv preprint arXiv:1907.07541 (2019).

  • Abebe, Rediet, and Kira Goldner. "Mechanism design for social good." AI Matters 4, no. 3 (2018).

  • Benson, Austin R., Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. "Simplicial closure and higher-order link prediction." Proceedings of the National Academy of Sciences (PNAS) 115, no. 48 (2018).

  • Abebe, Rediet, Lada Adamic, and Jon Kleinberg. "Mitigating overexposure in viral marketing." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2018.

  • Abebe, Rediet. "Computational perspectives on social good and access to opportunity." In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2018.

  • Abebe, Rediet, Jon Kleinberg, David Parkes, and Charalampos E. Tsourakakis. "Opinion dynamics with varying susceptibility to persuasion." In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2018.

  • Abebe, Rediet, Jon Kleinberg, and David Parkes. "Fair division via social comparison." In the Proceedings of the 16th Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.

  • Harding, Charles, Francesco Pompei, Dmitriy Burmistrov, H. Gilbert Welch, Rediet Abebe, and Richard Wilson. "Breast cancer screening, incidence, and mortality across US counties." JAMA internal medicine 175, no. 9 (2015).

  • Trifunovic, Luka, Oliver Dial, Mircea Trif, James R. Wootton, Rediet Abebe, Amir Yacoby, and Daniel Loss. "Long-distance spin-spin coupling via floating gates." Physical review X 2, no. 1 (2012).

Theses

  • Abebe, Rediet. "Designing Algorithms for Social Good." PhD dissertation (Cornell University, 2019).
    SIGKDD Dissertation Award
    Cornell University Department of Computer Science Dissertation Award
    SIGecom Dissertation Award (honorable mention)

  • Abebe, Rediet. "Equitable Simple Allocations of Heterogeneous Goods." Master's thesis (University of Cambridge, 2014).

  • Abebe, Rediet. "Plethysm of Schur functions and irreducible polynomial representations of the complex general linear group." Undergraduate thesis (Harvard University, 2013).

Selected Upcoming / Recent Talks

The International Conference on Computational Social Science (IC2S2 '22). Keynote
Algorithms on Trial: Interrogating Evidentiary Statistical Software

Symposium on Principles of Database Systems (PODS '22). Invited Tutorial
Algorithms on Trial: Interrogating Evidentiary Statistical Software

Electronic Frontiers Foundation (EFF). Podcast Interview
An AI Hammer in Search of a Nail (link)

Georgetown University, Department of Computer Science. Colloquium
What Can Algorithms Tell Us About Inequality?

Pomona College, Department of Computer Science. Colloquium
What Can Algorithms Tell Us About Inequality?

Canadian Mathematical Society, Winter Meeting. Plenary Lecture
What Can Algorithms Tell Us About Inequality?

Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS '21). Keynote
What Can Algorithms Tell Us About Inequality?

32nd Stony Brook International Conference on Game Theory (link). Invited Speaker
An Algorithmic Study of Saving Circles

International AAAI Conference on Web and Social Media (ICWSM '21). Keynote
Technical and Humanistic Perspectives on Data Inequality

Positions

Prospective Postdoctoral Fellows: I am not actively recruiting postdoctoral fellows. However, if there is an exceptionally good research fit and you are already a member of one of the below or related programs at Berkeley, feel free to reach out: BIDS Postdoctoral Fellowship Programs, Chancellor's Postdoctoral Fellowship Program, FODSI, Miller Institute, President's Postdoctoral Fellowship Program, and the Simons Institute.

Prospective Graduate Students: I may be recruiting PhD students applying during the 2022/23 academic cycle. If you are interested in my research, you can list me as a faculty of interest in your application. I will read all such applications and will conduct interviews in January 2023. I will not be holding any informational meetings ahead of the interview cycle. If you have any questions about admissions, please visit this page and send your questions to the contact information there.

Research Assistant, Visiting, or Intern Positions: I currently do not have any positions available.

Links

CV (link)
Google Scholar (link)
SSRN (link)
Twitter: @red_abebe