| 2026 | SODA | On the Structure of Replicable Hypothesis Testers. | Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal |
| 2025 | COLT | Improved algorithms for learning quantum Hamiltonians, via flat polynomials. | Shyam Narayanan |
| 2025 | ICALP | Near-Optimal Trace Reconstruction for Mildly Separated Strings. | Anders Aamand, Allen Liu, Shyam Narayanan |
| 2025 | ISCAS | Live Demonstration: A real-time event encoder for seizure monitoring on Neuromorphic Hardware. | Saptarshi Ghosh, Olympia Gallou, Shyam Narayanan, Jim Bartels, Giacomo Indiveri |
| 2024 | COLT | A faster and simpler algorithm for learning shallow networks. | Sitan Chen, Shyam Narayanan |
| 2024 | FOCS | Instance-Optimality in I/O-Efficient Sampling and Sequential Estimation. | Shyam Narayanan, Vclav Rozhon, Jakub Tetek, Mikkel Thorup |
| 2024 | SODA | Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. | Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong |
| 2023 | FOCS | Krylov Methods are (nearly) Optimal for Low-Rank Approximation. | Ainesh Bakshi, Shyam Narayanan |
| 2023 | FOCS | The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. | Clment L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan |
| 2023 | FOCS | Query lower bounds for log-concave sampling. | Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan |
| 2023 | ICML | Data Structures for Density Estimation. | Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal |
| 2023 | SODA | Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. | Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu |
| 2023 | STOC | Robustness Implies Privacy in Statistical Estimation. | Samuel B. Hopkins, Gautam Kamath, Mahbod Majid, Shyam Narayanan |
| 2022 | COLT | Private High-Dimensional Hypothesis Testing. | Shyam Narayanan |
| 2022 | ICALP | Optimal Time-Backlog Tradeoffs for the Variable-Processor Cup Game. | William Kuszmaul, Shyam Narayanan |
| 2022 | ICLR | Triangle and Four Cycle Counting with Predictions in Graph Streams. | Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang |
| 2022 | ICML | Tight and Robust Private Mean Estimation with Few Users. | Shyam Narayanan, Vahab S. Mirrokni, Hossein Esfandiari |
| 2022 | ISCAS | Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. | Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand |
| 2022 | ISCAS | A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices. | Shyam Narayanan, Erika Covi, Viktor Havel, Charlotte Frenkel, Suzanne Lancaster, Quang T. Duong, Stefan Slesazeck, Thomas Mikolajick, Melika Payvand, Giacomo Indiveri |
| 2022 | SODA | Almost Tight Approximation Algorithms for Explainable Clustering. | Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan |
| 2022 | SODA | Frequency Estimation with One-Sided Error. | Piotr Indyk, Shyam Narayanan, David P. Woodruff |
| 2022 | STOC | Improved approximations for Euclidean | Vincent Cohen-Addad, Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan |
| 2021 | FOCS | Stochastic and Worst-Case Generalized Sorting Revisited. | William Kuszmaul, Shyam Narayanan |
| 2021 | ICLR | Learning-based Support Estimation in Sublinear Time. | Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner |
| 2021 | ICML | Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. | Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir |
| 2021 | SODA | On Tolerant Distribution Testing in the Conditional Sampling Model. | Shyam Narayanan |
| 2021 | SODA | Improved Algorithms for Population Recovery from the Deletion Channel. | Shyam Narayanan |
| 2019 | STOC | Optimal terminal dimensionality reduction in Euclidean space. | Shyam Narayanan, Jelani Nelson |