Kate Donahue
I'm a METEOR postdoc at MIT, working with Manish Raghavan. I'm a member of the AI for Society working group. Starting in fall 2025, I will be an assistant professor of computer science at University of Illinois Urbana-Champaign (UIUC). I work on algorithmic problems relating to the societal impact of AI such as fairness, human/AI collaboration and game-theoretic models of federated/collaborative learning.
I'm recruiting PhD students at UIUC - if you're interested, please list me as a potential faculty advisor when you apply and describe how your research interests relate to mine.
I'm also recruiting undergrad/MS students to work with me in '24-'25 academic year at MIT- reach out if you're interested in my work!
I did my PhD in computer Science at Cornell, where I was extremely fortunate to be advised by Jon Kleinberg. During my PhD, I interned at Google (with Kostas Kollias and Sreenivas Gollapudi), at Amazon (with Krishnaram Kenthapadi and Alexandra Chouldechova) and at Microsoft Research (with Solon Barocas, in the NYC FATE group, and with Nicole Immorlica and Brendan Lucier in the NE EconCS group).
Previously, I have been a data scientist working at Booz Allen Hamilton as well as a researcher in evolutionary game theory at the Program of Evolutionary Dynamics at Harvard. My undergraduate degree was at Harvard, a major in math with a minor in statistics. My real world interests include hiking in gorges, baking desserts, and hosting murder mystery parties.
My CV is available here. My pronouns are she/her/hers.
The best email is kpd@illinois.edu or kpd46@cornell.edu.
Recent news:
I'll be giving invited talks at the CMU FEAT reading group (9/25), CMU workshop on Human-AI Teaming (9/26), INFORMS (10/20), UMass Amherst Theory Seminar (10/24), Boston College department seminar (11/1).
I'm visiting Simons this fall for the semesters on Generalization and LLMs (the weeks of 9/24 and 10/14).
September 2024: I've moved to Boston! Come say hi if you're in the area.
Summer 2024 travel: I'll be at: FORC (presenting our "When are two lists better than one?" paper), WALE (co-organizing the Trustworthy AI day), MPI-Tübingen (giving a talk in Moritz Hardt's group meeting), EC (co-organizing the Gender Inclusion workshop), ICML (co-presenting our "Impact of Decentralized Learning on Player Utilities in Stackelberg Games" work and co-organizing a Data and Learning Economics social), (virtually) giving a talk the workshop on Tech for Good!, ESIF (co-presenting the "Decentralized Stackelberg" paper), and EEA-ESESM (presenting the "When are two lists better than one?" paper).
Our paper (joint with Nicole Immorlica, Meena Jagadeesan, Brendan Lucier, Aleksandrs Slivkins) on the "Impact of Decentralized Learning on Player Utilities in Stackelberg Games" was accepted at ICML 2024!
I'm co-organizing the EC Gender Inclusion workshop again in 2024 - apply to give a spotlight talk, poster, or sign up for the interest form.
New paper accepted at the prestigious SIGBOVIK conference, with joint authors Katy, Katie, Kate, Katherine, Katie, Cathy, & Katie!
"When are two lists better than one" (joint work with Kostas Kollias and Sreenivas Gollapudi, on a model of human-algorithm collaboration) was accepted to AAAI '24 (oral presentation)!
Fall 2023 travel: I'll be speaking at UPenn's Theory Seminar on "Model-sharing Games" (Sept '23), visiting Max Planck Institutes-SWS part of their "Next 10 in AI" series and MPI-EB to speak at Christian Hilbe's lab meeting (Sept '23), speaking on human-algorithm collaboration on a panel at Estelle Smith's class on Social & Collaborative Computing! (Oct '23), presenting our "Model-sharing games" papers at INFORMS (in "Social Computing in OR", organized by Chara Podimata) (Oct '23), presenting "Private Blotto" at EAAMO (Oct '23), presenting a poster at the SLMath (MSRI) workshop on Market and Mechanism Design (Nov '23), giving an invited talk at the Young Scholars Conference on Machine Learning in Economics and Finance (Dec '23), and giving an invited talk at the Chicago Junior Theorists Workshop (Dec '23).
Publications and Honors
In Fall 2021, I was selected as a "Rising Star in EECS" for MIT Rising Stars EECS 2021 workshop. My PhD research has been supported by an NSF Graduate Research Fellowship.
"AI as a Resource: Strategy, Uncertainty, and Societal Welfare"
Kate Donahue (PhD dissertation). August '24.
"Optimal Selection Using Algorithmic Rankings with Side Information"
Kate Donahue, Nicole Immorlica, Brendan Lucier (alphabetical order). Preliminary versions to appear at Neurips '24 workshops on Regulatable ML and Algorithmic Fairness through the Lens of Time.
"Private Blotto: Viewpoint Competition with Polarized Agents"
Kate Donahue and Jon Kleinberg. Preliminary version accepted at EAAMO 2023. Full version accepted at AAAI 2025.
"Impact of Decentralized Learning on Player Utilities in Stackelberg Games"
Kate Donahue, Nicole Immorlica, Meena Jagadeesan, Brendan Lucier, Aleksandrs Slivkins (alphabetical order). Accepted at ICML 2024. Presented at ESIF '24 (oral) and EC '24 (contributed poster).
"An Abundance of Katherines: The Game Theory of Baby Naming"
Katy Blumer, Kate Donahue, Katie Fritz, Kate Ivanovich, Katherine Lee, Katie Luo, Cathy Meng, Katie Van Koevering (alphabetical order). SIGBOVIK 2024. [Note: this is an April Fool's day paper]
"When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-making"
Kate Donahue, Sreenivas Gollapudi, Kostas Kollias. AAAI 2024 (oral presentation). Summary in the Montreal AI Ethics blog.
"Models of fairness in federated learning (Model-Sharing Games III)"
Kate Donahue and Jon Kleinberg, 2022. Oral presentation at Neurips workshop on Learning and Decision-making with Strategic Feedback and poster at EAAMO 2022. Accepted at The Web Conference 2023.
"Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness"
Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi, 2021. Panel presentation at Neurips workshop on Human-Centered AI. Full version accepted at FAccT 2022. Summary in the Montreal AI Ethics blog.
"Optimality and Stability in Federated Learning: A Game-theoretic Approach (Model-Sharing Games II)"
Kate Donahue and Jon Kleinberg, 2021. Accepted at Neurips 2021.
Kate Donahue and Jon Kleinberg, 2021. Github repository here. Accepted at AAAI 2021.
Kate Donahue and Solon Barocas, 2021. NeurIPS Workshop on Consequential Decision Making in Dynamic Environments, contributed talk. Accepted at FAccT 2021.
"Fairness and Utilization In Allocating Resources With Uncertain Demand"
Kate Donahue and Jon Kleinberg, 2020. Mechanism Design for Social Good, 2019, FAccT 2020, where it won Best Paper in the CS category.
"Evolving cooperation in multichannel games"
Kate Donahue, Oliver P. Hauser, Martin A. Nowak, Christian Hilbe. Published in Nature Communications, August 2020.
Thesis by Kate Donahue, 2016. My thesis received a Hoopes Prize given for “excellence in undergraduate research”. My undergraduate work in general earned the Herb Alexander Award for “outstanding undergraduate” in mathematics.