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.
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!
