ROBUS: Fair Cache Allocation for Multi-tenant Data-parallel Workloads. - Mayuresh Kunjir; Brandon Fain; Kamesh Munagala; Shivnath Babu (CoRR, 2015)

The Core of the Participatory Budgeting Problem. - Brandon Fain; Ashish Goel; Kamesh Munagala (WINE, 2016)

ROBUS: Fair Cache Allocation for Data-parallel Workloads. - Mayuresh Kunjir; Brandon Fain; Kamesh Munagala; Shivnath Babu (SIGMOD Conference, 2017)

Sequential Deliberation for Social Choice. - Brandon Fain; Ashish Goel; Kamesh Munagala; Sukolsak Sakshuwong (WINE, 2017)

Fair Allocation of Indivisible Public Goods. - Brandon Fain; Kamesh Munagala; Nisarg Shah 001 (EC, 2018)

Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choice. - Brandon Fain; Ashish Goel; Kamesh Munagala; Nina Prabhu (AAAI, 2019)

Proportionally Fair Clustering. - Xingyu Chen; Brandon Fain; Liang Lyu; Kamesh Munagala (ICML, 2019)

Proportionally Fair Clustering. - Xingyu Chen; Brandon Fain; Charles Lyu; Kamesh Munagala (CoRR, 2019)

Building and expanding a successful undergraduate research program. - Sarah Heckman; Brandon Fain; Manuel A. Pérez-Quiñones (J. Comput. Sci. Coll., 2019)

Concentration of Distortion: The Value of Extra Voters in Randomized Social Choice. - Brandon Fain; William Fan; Kamesh Munagala (IJCAI, 2020)

Centrality with Diversity. - Liang Lyu; Brandon Fain; Kamesh Munagala; Kangning Wang 001 (WSDM, 2021)

Budget Sharing for Multi-Analyst Differential Privacy. - David Pujol; Yikai Wu 001; Brandon Fain; Ashwin Machanavajjhala (Proc. VLDB Endow., 2021)

Auditing for Gerrymandering by Identifying Disenfranchised Individuals. - Jerry Lin; Carolyn Chen; Marc Chmielewski; Samia Zaman; Brandon Fain (FAccT, 2022)

Multi-Analyst Differential Privacy for Online Query Answering. - David Pujol; Albert Sun; Brandon Fain; Ashwin Machanavajjhala (Proc. VLDB Endow., 2022)

Fairness in the Assignment Problem with Uncertain Priorities. - Zeyu Shen 001; Zhiyi Wang; Xingyu Zhu 003; Brandon Fain; Kamesh Munagala (AAMAS, 2023)

Welfare and Fairness in Multi-objective Reinforcement Learning. - Zimeng Fan 002; Nianli Peng; Muhang Tian; Brandon Fain (AAMAS, 2023)

Do Not Harm Protected Groups in Debiasing Language Representation Models. - Chloe Qinyu Zhu; Rickard Stureborg; Brandon Fain (CoRR, 2023)

Nonlinear Multi-objective Reinforcement Learning with Provable Guarantees. - Nianli Peng; Brandon Fain (CoRR, 2023)

Multi-objective Reinforcement Learning with Nonlinear Preferences: Provable Approximation for Maximizing Expected Scalarized Return. - Nianli Peng; Muhang Tian; Brandon Fain (AAMAS, 2025)