| 2026 | AAAI | When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospital. | Avni Kothari, Patrick Vossler, Jean Digitale, Mohammad Forouzannia, Elise Rosenberg, Michele Lee, Jennee Bryant, Melanie F. Molina, James Marks, Lucas Zier, Jean Feng |
| 2025 | ICML | "Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift. | Harvineet Singh, Fan Xia, Alexej Gossmann, Andrew Chuang, Julian C. Hong, Jean Feng |
| 2024 | AISTATS | Is this model reliable for everyone? Testing for strong calibration. | Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner |
| 2024 | AISTATS | Monitoring machine learning-based risk prediction algorithms in the presence of performativity. | Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio |
| 2022 | UAI | Sequential algorithmic modification with test data reuse. | Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann |
| 2020 | ICML | Efficient nonparametric statistical inference on population feature importance using Shapley values. | Brian D. Williamson, Jean Feng |
| 2018 | ICML | Nonparametric variable importance using an augmented neural network with multi-task learning. | Jean Feng, Brian D. Williamson, Marco Carone, Noah Simon |