Kate Donahue
I'm a final year computer science PhD candidate at Cornell. I work on algorithmic problems relating to the societal impact of AI such as fairness, human/AI collaboration and game-theoretic models of distributed learning. I'm extremely fortunate to be advised by Jon Kleinberg.
I'm on the 2023-2024 academic job market.
During my PhD, I've 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.
Recent news:
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)!
I'll be giving an invited talk at the Young Scholars Conference on Machine Learning in Economics and Finance (Dec '23).
I'm giving an invited talk at the Chicago Junior Theorists Workshop (Dec '23).
I'll be giving a poster at the SLMath (MSRI) workshop on Market and Mechanism Design (Nov '23).
Presenting our "Private Blotto" work at EAAMO and participating at the Doctoral Consortium. (Oct '23)
Presenting our "Model-sharing games" papers at INFORMS (in "Social Computing in OR", organized by Chara Podimata) (Oct '23)
Talking about human-algorithm collaboration on a panel at Estelle Smith's class on Social & Collaborative Computing! (Oct '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)
I'll be talking at UPenn's Theory Seminar on "Model-sharing Games" (Sept '23)
Spotlight talk at the Simons Institute workshop on Federated and Collaborative Learning (July '23)
Co-organizing the inaugural Gender Inclusion Workshop at EC '23 - come by! (July '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.
"How to Hire a Superstar: Optimal Selection Using Algorithmic Rankings with Side Information"
Kate Donahue, Nicole Immorlica, Brendan Lucier (alphabetical order). In progress (2024)
"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.
Impact of Decentralized Learning on Player Utilities in Stackelberg Games
Kate Donahue, Nicole Immorlica, Meena Jagadeesan, Brendan Lucier, Aleksandrs Slivkins (alphabetical order). Under review (2024).
"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.
"Private Blotto: Viewpoint Competition with Polarized Agents"
Kate Donahue and Jon Kleinberg. Preliminary version accepted at EAAMO 2023.
"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.
“Analysis and simulation of the operation of a Kelvin probe”
Robert D. Reasenberg, Kathleen P. Donahue, James D. Phillips, 2013. Classical Quantum Gravity
Contact
Please email me at kdonahue [at] cs [dot] cornell [dot] edu.
Photo by Greg Yauney