| 2026 | STOC | Generalized Samorodnitsky Noisy Function Inequalities, with Applications to Error-Correcting Codes. | Olakunle Sunday Abawonse, Jan Hazla, Ryan O'Donnell |
| 2025 | ICLR | Learning High-Degree Parities: The Crucial Role of the Initialization. | Emmanuel Abbe, Elisabetta Cornacchia, Jan Hazla, Donald Kougang-Yombi |
| 2024 | ISIT | A Quantitative Version of More Capable Channel Comparison. | Donald Kougang-Yombi, Jan Hazla |
| 2023 | ISIT | Optimal List Decoding from Noisy Entropy Inequality. | Jan Hazla |
| 2022 | ICLR | A Johnson-Lindenstrauss Framework for Randomly Initialized CNNs. | Ido Nachum, Jan Hazla, Michael Gastpar, Anatoly Khina |
| 2022 | ICML | An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn. | Emmanuel Abbe, Elisabetta Cornacchia, Jan Hazla, Christopher Marquis |
| 2021 | STOC | On codes decoding a constant fraction of errors on the BSC. | Jan Hazla, Alex Samorodnitsky, Ori Sberlo |
| 2019 | COLT | Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard. | Jan Hazla, Ali Jadbabaie, Elchanan Mossel, M. Amin Rahimian |
| 2015 | STACS | Upper Tail Estimates with Combinatorial Proofs. | Jan Hazla, Thomas Holenstein |