Kate Donahue

I'm a fifth 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

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). 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 with friends, and reading. 

My CV is available here. My pronouns are she/her/hers.

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. 

"Private Blotto: Viewpoint Competition with Polarized Agents"

Kate Donahue and Jon Kleinberg. Under review. 

"'I pick you choose': Joint human-algorithm decision making in multi-armed bandits"

 Kate Donahue, Sreenivas Gollapudi, Kostas Kollias. NeurIPS 2022 Workshop on Human in the Loop Learning

"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.  

"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. 

"Optimality and Stability in Federated Learning: A Game-theoretic Approach (Model-Sharing Games II)

Kate Donahue and Jon Kleinberg, 2021. Accepted at Neurips 2021. 

"Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation (Model-Sharing Games I).

Kate Donahue and Jon Kleinberg, 2021. Github repository here. Accepted at AAAI 2021. 

"Better Together? How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness". 

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. 

“’All Together Now’: Linking the Public Goods Game and Prisoner’s Dilemma For Robustness Against Free-Riders” 

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


Please email me at kdonahue [at] cs [dot] cornell [dot] edu. 

Photo by Greg Yauney