Welcome!
Joshua is an Associate Information Scientist at RAND. His research interests include computational social choice, multi-agent systems, and AI ethics. Joshua completed his Ph.D. in computer science from Rensselaer Polytechnic Institute in 2024 under the advisement of Lirong Xia. He earned his B.S. in data science from the University of Michigan in 2020. Ongoing work:
Bridging Theory and Perception in Fair Division:A Study on Comparative and Fair Share Notions Hadi Hosseini, Joshua Kavner, Samarth Khanna, Sujoy Sikdar, and Lirong Xia. In Submission.
Average-Case Analysis of Iterative Voting Joshua Kavner and Lirong Xia In Submission.
Epistemic vs. Counterfactual Fairness in Allocation of Resources Hadi Hosseini, Joshua Kavner, Sujoy Sikdar, Rohit Vaish, and Lirong Xia Presented at the Computational Fair Division workshop at IJCAI-23. Publications: Distribution of Chores with Information Asymmetry Hadi Hosseini, Joshua Kavner, Tomasz Wąs, and Lirong Xia In Proceedings of ECAI'24. Convergence of Multi-Issue Iterative Voting under Uncertainty Joshua Kavner, Reshef Meir, Francesca Rossi, and Lirong Xia In Proceedings of IJCAI'23. Strategic Behavior is Bliss: Iterative Voting Improves Social Welfare Joshua Kavner and Lirong Xia In Proceedings of NeurIPS'21. Philosophy of Science, Network Theory, and Conceptual Change: Paradigm Shifts as Information Cascades Patrick Grim, Joshua Kavner, Lloyd Shatkin, and Manjari Trivedi In Complex Systems in the Social and Behavioral Sciences: Theory, Method, and Application by Euell Elliot and J Douglas Kiel, University of Michigan Press. June, 2021.Informal Corner
In my free time, I dance Lindy Hop, play the piano, read, and photograph. Check out my photos below!
