| The Unreasonable Fairness of Maximum Nash Welfare I Caragiannis, D Kurokawa, H Moulin, AD Procaccia, N Shah, J Wang ACM Transactions on Economics and Computation (TEAC) 7 (3), 1-32, 2019 | 933 | 2019 |
| Beyond dominant resource fairness: Extensions, limitations, and indivisibilities DC Parkes, AD Procaccia, N Shah ACM Transactions on Economics and Computation (TEAC) 3 (1), 1-22, 2015 | 297 | 2015 |
| No agent left behind: Dynamic fair division of multiple resources I Kash, AD Procaccia, N Shah Journal of Artificial Intelligence Research 51, 579-603, 2014 | 239 | 2014 |
| Participatory Budgeting: Models and Approaches H Aziz, N Shah Pathways Between Social Science and Computational Social Science, 215-236, 2021 | 234 | 2021 |
| Fair Public Decision Making V Conitzer, R Freeman, N Shah Proceedings of the 18th ACM Conference on Electronic Commerce, 629-646, 2017 | 228 | 2017 |
| Preference Elicitation for Participatory Budgeting G Benade, S Nath, AD Procaccia, N Shah Management Science 67 (5), 2813-2827, 2021 | 200 | 2021 |
| When do noisy votes reveal the truth? I Caragiannis, AD Procaccia, N Shah ACM Transactions on Economics and Computation (TEAC) 4 (3), 1-30, 2016 | 178 | 2016 |
| Fair Allocation of Indivisible Public Goods B Fain, K Munagala, N Shah Proceedings of the 2018 ACM Conference on Economics and Computation, 575-592, 2018 | 154 | 2018 |
| Subset selection via implicit utilitarian voting I Caragiannis, S Nath, AD Procaccia, N Shah Journal of Artificial Intelligence Research 58, 123-152, 2017 | 136 | 2017 |
| Fair division with binary valuations: One rule to rule them all D Halpern, AD Procaccia, A Psomas, N Shah International Conference on Web and Internet Economics, 370-383, 2020 | 124 | 2020 |
| Distortion in social choice problems: The first 15 years and beyond E Anshelevich, A Filos-Ratsikas, N Shah, AA Voudouris arXiv preprint arXiv:2103.00911, 2021 | 121 | 2021 |
| Resolving the optimal metric distortion conjecture V Gkatzelis, D Halpern, N Shah 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 101 | 2020 |
| Group Fairness for the Allocation of Indivisible Goods V Conitzer, R Freeman, N Shah, JW Vaughan Proceedings of the AAAI Conference on Artificial Intelligence 33, 1853-1860, 2019 | 98 | 2019 |
| Multi-agent risks from advanced ai L Hammond, A Chan, J Clifton, J Hoelscher-Obermaier, A Khan, ... arXiv preprint arXiv:2502.14143, 2025 | 97 | 2025 |
| A Maximum Likelihood Approach For Selecting Sets of Alternatives AD Procaccia, S Reddy, N Shah Conference on Uncertainty in Artificial Intelligence, 695-704, 2012 | 93 | 2012 |
| Leximin Allocations in the Real World D Kurokawa, AD Procaccia, N Shah ACM Transactions on Economics and Computation (TEAC) 6 (3-4), 1-24, 2018 | 92 | 2018 |
| Strategyproof Linear Regression in High Dimensions Y Chen, C Podimata, AD Procaccia, N Shah Proceedings of the 2018 ACM Conference on Economics and Computation, 9-26, 2018 | 92 | 2018 |
| Best of both worlds: Ex-ante and ex-post fairness in resource allocation R Freeman, N Shah, R Vaish Proceedings of the 21st ACM Conference on Economics and Computation, 21-22, 2020 | 80 | 2020 |
| Fair algorithms for multi-agent multi-armed bandits S Hossain, E Micha, N Shah Advances in Neural Information Processing Systems 34, 24005-24017, 2021 | 72 | 2021 |
| Optimal bounds on the price of fairness for indivisible goods S Barman, U Bhaskar, N Shah International Conference on Web and Internet Economics, 356-369, 2020 | 70 | 2020 |
Ariel ProcacciaAlfred and Rebecca Lin Professor of Computer Science, Harvard UniversityVerified email at seas.harvard.edu
