| 2026 | SODA | Online Learning with Limited Information in the Sliding Window Model. | Vladimir Braverman, Sumegha Garg, Chen Wang, David P. Woodruff, Samson Zhou |
| 2026 | STOC | A Unified Approach to Memory-Sample Tradeoffs for Detecting Planted Structures. | Sumegha Garg, Jabari Hastings, Chirag Pabbaraju, Vatsal Sharan |
| 2025 | FOCS | Robust Local Testability of Tensor Products of Constant-Rate Algebraic Geometry Codes. | Sumegha Garg, Akash Kumar Sengupta |
| 2024 | SODA | Oracle Efficient Online Multicalibration and Omniprediction. | Sumegha Garg, Christopher Jung, Omer Reingold, Aaron Roth |
| 2024 | STOC | A New Information Complexity Measure for Multi-pass Streaming with Applications. | Mark Braverman, Sumegha Garg, Qian Li, Shuo Wang, David P. Woodruff, Jiapeng Zhang |
| 2021 | FOCS | Tight Space Complexity of the Coin Problem. | Mark Braverman, Sumegha Garg, Or Zamir |
| 2020 | FOCS | The Coin Problem with Applications to Data Streams. | Mark Braverman, Sumegha Garg, David P. Woodruff |
| 2019 | EC | Tracking and Improving Information in the Service of Fairness. | Sumegha Garg, Michael P. Kim, Omer Reingold |
| 2018 | STOC | Hitting sets with near-optimal error for read-once branching programs. | Mark Braverman, Gil Cohen, Sumegha Garg |
| 2018 | STOC | Extractor-based time-space lower bounds for learning. | Sumegha Garg, Ran Raz, Avishay Tal |
| 2017 | CRYPTO | New Security Notions and Feasibility Results for Authentication of Quantum Data. | Sumegha Garg, Henry Yuen, Mark Zhandry |