Srinivasan, Aravind

23 publications

NeurIPS 2025 Controlling the Spread of Epidemics on Networks with Differential Privacy Dung Nguyen, Aravind Srinivasan, Renata Valieva, Anil Vullikanti, Jiayi Wu

AAAI 2025 Proportionally Fair Matching via Randomized Rounding Sharmila Duppala, Nathaniel Grammel, Juan Luque, Calum MacRury, Aravind Srinivasan

ICML 2024 Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu

IJCAI 2023 Efficient and Equitable Deployment of Mobile Vaccine Distribution Centers Da Qi Chen, Ann Li, George Z. Li, Madhav V. Marathe, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

IJCAI 2023 Group Fairness in Set Packing Problems Sharmila Duppala, Juan Luque, John P. Dickerson, Aravind Srinivasan

AAAI 2023 Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual Seyed A. Esmaeili, Sharmila Duppala, Davidson Cheng, Vedant Nanda, Aravind Srinivasan, John P. Dickerson

AISTATS 2022 A New Notion of Individually Fair Clustering: $α$-Equitable $k$-Center Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas

AISTATS 2022 Controlling Epidemic Spread Using Probabilistic Diffusion Models on Networks Amy E. Babay, Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

AISTATS 2022 Fair Disaster Containment via Graph-Cut Problems Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

JMLR 2022 Dependent Randomized Rounding for Clustering and Partition Systems with Knapsack Constraints David G. Harris, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh

IJCAI 2022 Forecasting Patient Outcomes in Kidney Exchange Naveen Durvasula, Aravind Srinivasan, John P. Dickerson

AISTATS 2021 Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan

NeurIPS 2021 Fair Clustering Under a Bounded Cost Seyed Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson

AAAI 2021 Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas

NeurIPS 2021 Improved Guarantees for Offline Stochastic Matching via New Ordered Contention Resolution Schemes Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan

ICML 2020 A Pairwise Fair and Community-Preserving Approach to K-Center Clustering Brian Brubach, Darshan Chakrabarti, John Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas

AAAI 2020 Balancing the Tradeoff Between Profit and Fairness in Rideshare Platforms During High-Demand Hours Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan

AISTATS 2020 Dependent Randomized Rounding for Clustering and Partition Systems with Knapsack Constraints David Harris, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh

AAAI 2019 A Unified Approach to Online Matching with Conflict-Aware Constraints Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas

JMLR 2019 Approximation Algorithms for Stochastic Clustering David G. Harris, Shi Li, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh

AAAI 2019 Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu

AAAI 2018 Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu

NeurIPS 2018 Approximation Algorithms for Stochastic Clustering David Harris, Shi Li, Aravind Srinivasan, Khoa Trinh, Thomas Pensyl