| 2025 | ICML | WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales. | Drew Prinster, Xing Han, Anqi Liu, Suchi Saria |
| 2024 | ICML | Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). | Drew Prinster, Samuel Don Stanton, Anqi Liu, Suchi Saria |
| 2023 | ICML | JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift. | Drew Prinster, Suchi Saria, Anqi Liu |
| 2023 | UAI | Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection. | Yoav Wald, Suchi Saria |
| 2021 | AISTATS | Evaluating Model Robustness and Stability to Dataset Shift. | Adarsh Subbaswamy, Roy Adams, Suchi Saria |
| 2021 | AMIA | Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery. | Suchi Saria, Marzyeh Ghassemi, Ziad Obermeyer, Karandeep Singh, Pei-Yun S. Hsueh, Eric J. Topol |
| 2021 | UAI | Partial Identifiability in Discrete Data with Measurement Error. | Noam Finkelstein, Roy Adams, Suchi Saria, Ilya Shpitser |
| 2019 | AISTATS | Can You Trust This Prediction? Auditing Pointwise Reliability After Learning. | Peter Schulam, Suchi Saria |
| 2019 | AISTATS | Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport. | Adarsh Subbaswamy, Peter Schulam, Suchi Saria |
| 2019 | ICML | Learning Models from Data with Measurement Error: Tackling Underreporting. | Roy Adams, Yuelong Ji, Xiaobin Wang, Suchi Saria |
| 2019 | ICML | Active Learning for Decision-Making from Imbalanced Observational Data. | Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski |
| 2018 | UAI | Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms. | Adarsh Subbaswamy, Suchi Saria |
| 2017 | UAI | Learning Treatment-Response Models from Multivariate Longitudinal Data. | Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria |
| 2016 | IJCAI | Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. | Daniel P. Robinson, Suchi Saria |
| 2016 | MICCAI | Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor. | Austin Reiter, Andy J. Ma, Nishi Rawat, Christine Shrock, Suchi Saria |
| 2015 | AAAI | Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery. | Peter Schulam, Fredrick Wigley, Suchi Saria |
| 2015 | AMIA | Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons. | Kirill Dyagilev, Suchi Saria |
| 2015 | AMIA | A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases. | Peter Schulam, Colin Ligon, Robert Wise, Laura K. Hummers, Fredrick Wigley, Suchi Saria |
| 2014 | AMIA | Predictive Analytics in Healthcare (HPA): Considerations and Challenges. | Suchi Saria, Gabriel J. Escobar, Paul C. Tang, Lucila Ohno-Machado, Alex Dummett |
| 2013 | AMIA | Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls. | Chris Paxton, Suchi Saria, Alexandru Niculescu-Mizil |
| 2011 | IJCAI | Discovering Deformable Motifs in Continuous Time Series Data. | Suchi Saria, Andrew Duchi, Daphne Koller |
| 2007 | UAI | Reasoning at the Right Time Granularity. | Suchi Saria, Uri Nodelman, Daphne Koller |