Photo by Kelly Sikkema on Unsplash

A few years ago, I posted annual reviews of what I did in the year; thought that this year I might bring that tradition back.

This year has been a year of some major achievements and changes. I earned tenure, published a major piece of integrative scholarship that I’ve been working on for a few years, and one of my Ph.D students successfully defended her proposal.

I’m also working on figuring out what the next phase of structure and operation looks like for my research lab, since Sole Pera moved to Delft. I’m thrilled she got this new position! It’s been a very good 6 years building the PIReTs and having other academic adventures with her, and we continue to work together remotely on various things. For now, she’s been continuing to meet with the research group while some of the current students finish and we figure out what the long-term future of the PIReT ship will be.

So here’s the list (possibly incomplete):

  • Earned tenure!

  • Taught our undergraduate ethics class, CS 230, for the first time.

  • Taught CS 533 for the third time in its current form (my 5th time overall), this time as a hybrid class with a few in-person synchronous sessions.

  • Published our monograph on fairness in information access (with Anubrata Das, Robin Burke, and Fernando Diaz) in Foundations and Trends on Information Retrieval. This has been a major effort for the last few years, and it is very satisfying to see it finally in print.

  • Served as Program Chair for RecSys 2022 with Bracha Shapira.

  • Published a chapter in the new edition of the RecSys Handbook also with Anubrata, Robin, and Fernando).

  • Published an article in AI Magazine with Nasim Sonboli and Robin Burke on the multisided aspects of fair recommendation.

  • Published our work on fair ranking metrics in SIGIR 2022, work led by Ph.D student Amifa Raj.

  • Published a new study on gender stereotypes in e-commerce search at SIGIR eCom 2022, also led and presented by Amifa.

  • Presented a fun short position paper with Sole about the complexity of consumer-side fairness at the FAccTRec workshop.

  • Carried out a new project with undergrad Christine Pinney in collaboration with Alex Hanna and Amifa on the use of gender in information retrieval; this has been accepted for publication at CHIIR 2023. Preprint coming in January.

  • Published a preprint on values in recommender systems (led by Jonathan Stray; my primary contribution was to draft the discussion of fairness and related metrics).

  • Unsuccessful paper submissions: SIGIR (1 perspectives paper), CIKM (1 short paper), CHIIR (2 full papers), FAccT (1 full paper), RecSys (1 demo), PERSPECTIVES workshop @ RecSys (1 paper), CSCW (1 paper).

  • Submitted a position paper to the Transactions on Recommender Systems special issue on Perspectives on Evaluation.

  • Amifa Raj successfully defended her Ph.D proposal.

  • Srabanti Guha successfully defended her M.S. project proposal.

  • Submitted 3 NSF proposals, including a small corner of an AI Institute proposal. One declined, two pending.

  • Serving as track chair for the new track on Fairness, Accountability, Transparency, and Ethics on the Web for TheWebConf 2023, with Alexandra Olteanu and Krishna Gummadi.

  • Co-organized the fourth Fair Ranking track at TREC.

  • Gave a keynote on fair info access at the Information-Based Induction Sciences workshop in Tsukuba, Japan.

  • Gave a seminar talk at Waseda University in Tokyo, Japan.

  • Gave a remote semianr talk for UMSI.

  • Gave an invited talk on RecSys fairness evaluation at the EvalRS Analyticup at CIKM 2022.

  • Served as a mentor and panelist at the CIKM Ph.D symposium.

  • Served as a mentor at the FAccT Ph.D symposium.

  • Continued to serve on the FAccT Executive Committee (now in my 3rd and final year of this term).

  • Served as FAccT 2022 Sponsorships Chair with Chelle Adamson.

  • Reviewed several journal papers.

  • Continued to serve on department and college undergrad curriculum committees.

  • Participating in a faculty learning community on teaching portfolios.

  • Talked with Reed Albergotti at the Washington Post about why open-sourcing the algorithm isn’t meaningful.

  • Talked with Carolyn Kuimelis at Chronicle of Higher Education about late work (also described my policy in detail in this blog post).

  • Refreshed my web site & presentation slide design. The slide design is all–new — see my recent talks for examples.


  • Spring — CS 230 (Ethics)
  • Fall — CS 533 (Intro to Data Science)

Active Grants



Christine Pinney, Amifa Raj, Alex Hanna, and Michael D. Ekstrand. 2023. Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access. In Proceedings of the 2023 Conference on Human Information Interaction and Retrieval (CHIIR ’23). Proc. CHIIR ’23. DOI 10.1145/3576840.3578316. arXiv:2301.04780. NSF PAR 10423693. Acceptance rate: 39.4%. Cited 3 times. Cited 4 times.


Michael D. Ekstrand and Maria Soledad Pera. 2022. Matching Consumer Fairness Objectives & Strategies for RecSys. Presented at the 5th FAccTrec Workshop on Responsible Recommendation (peer-reviewed but not archived). arXiv:2209.02662 [cs.IR].


Jonathan Stray, Alon Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Zhang, Mckane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, and Nina Vasan. 2023. Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. Transactions on Recommender Systems (to appear). DOI 10.1145/3632297. arXiv:2207.10192 [cs.IR]. Cited 19 times. Cited 16 times.


Michael D. Ekstrand, Anubrata Das, Robin Burke, and Fernando Diaz. 2022. Fairness in Information Access Systems. Foundations and Trends® in Information Retrieval 16(1–2) (July 11th, 2022), 1–177. FnT IR 16(1–2) (July 11th, 2022). DOI 10.1561/1500000079. arXiv:2105.05779 [cs.IR]. NSF PAR 10347630. Impact factor: 8. Cited 90 times. Cited 51 times.


Amifa Raj and Michael D. Ekstrand. 2022. Measuring Fairness in Ranked Results: An Analytical and Empirical Comparison. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22). pp. 726–736. Proc. SIGIR ’22. DOI 10.1145/3477495.3532018. NSF PAR 10329880. Acceptance rate: 20%. Cited 24 times. Cited 20 times.


Nasim Sonboli, Robin Burke, Michael Ekstrand, and Rishabh Mehrotra. 2022. The Multisided Complexity of Fairness in Recommender Systems. AI Magazine 43(2) (June 23rd, 2022), 164–176. DOI 10.1002/aaai.12054. NSF PAR 10334796. Cited 11 times. Cited 9 times.


Michael D. Ekstrand, Anubrata Das, Robin Burke, and Fernando Diaz. 2022. Fairness in Recommender Systems. In Recommender Systems Handbook (3rd edition). Francesco Ricci, Lior Roach, and Bracha Shapira, eds. Springer-Verlag. DOI 10.1007/978-1-0716-2197-4_18. ISBN 978-1-0716-2196-7. Cited 13 times. Cited 12 times.


Michael D. Ekstrand, Graham McDonald, Amifa Raj, and Isaac Johnson. 2022. Overview of the TREC 2021 Fair Ranking Track. In The Thirtieth Text REtrieval Conference (TREC 2021) Proceedings (TREC 2021). Proc. TREC 2021. https://trec.nist.gov/pubs/trec30/papers/Overview-F.pdf.