Stephen R. Pfohl

22 papers A 2Misc 1Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity. Trans. Mach. Learn. Res. Pushkar Mishra, Charvi Rastogi, Stephen R. Pfohl, Alicia Parrish, Tian Huey Teh, Roma Patel, Mark Diaz, Ding Wang, Michela Paganini, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser
2025	J	`jnl`	Nuanced Safety for Generative AI: How Demographics Shape Responsiveness to Severity. CoRR Pushkar Mishra, Charvi Rastogi, Stephen R. Pfohl, Alicia Parrish, Roma Patel, Mark Diaz, Ding Wang, Michela Paganini, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser
2025	J	`jnl`	Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness. CoRR Stephen R. Pfohl, Natalie Harris, Chirag Nagpal, David Madras, Vishwali Mhasawade, Olawale Salaudeen, Awa Dieng, Shannon Sequeira, Santiago Eduardo Arciniegas, Lillian Sung, Nnamdi Ezeanochie, Heather Cole-Lewis, Katherine A. Heller, Sanmi Koyejo, Alexander D'Amour
2024	—	`conf`	A Causal Perspective on Label Bias. FAccT Vishwali Mhasawade, Alexander D'Amour, Stephen R. Pfohl
2024	J	`jnl`	A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. CoRR Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Nyamewaa Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah DeWitt, Philip Andrew Mansfield, Sushant Prakash, Katherine A. Heller, Alan Karthikesalingam, Christopher Semturs, Joelle K. Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal
2024	A	`conf`	Proxy Methods for Domain Adaptation. AISTATS Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton
2024	J	`jnl`	Proxy Methods for Domain Adaptation. CoRR Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton
2023	A	`conf`	Adapting to Latent Subgroup Shifts via Concepts and Proxies. AISTATS Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai
2023	J	`jnl`	Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks. J. Am. Medical Informatics Assoc. Joshua Lemmon, Lin Lawrence Guo, Ethan Steinberg, Keith E. Morse, Scott Lanyon Fleming, Catherine Aftandilian, Stephen R. Pfohl, José D. Posada, Nigam Shah, Jason Alan Fries, Lillian Sung
2022	J	`jnl`	Adapting to Latent Subgroup Shifts via Concepts and Proxies. CoRR Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai
2022	J	`jnl`	Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare. CoRR Stephen R. Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam H. Shah
2021	J	`jnl`	A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah
2021	J	`jnl`	An empirical characterization of fair machine learning for clinical risk prediction. J. Biomed. Informatics Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah
2021	J	`jnl`	Language models are an effective representation learning technique for electronic health record data. J. Biomed. Informatics Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah
2021	J	`jnl`	Learning decision thresholds for risk stratification models from aggregate clinician behavior. J. Am. Medical Informatics Assoc. Birju S. Patel, Ethan Steinberg, Stephen R. Pfohl, Nigam H. Shah
2021	J	`jnl`	Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine. Appl. Clin. Inform. Lin Lawrence Guo, Stephen R. Pfohl, Jason Alan Fries, José D. Posada, Scott L. Fleming, Catherine Aftandilian, Nigam Shah, Lillian Sung
2020	J	`jnl`	An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction. CoRR Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah
2020	J	`jnl`	Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. CoRR Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah
2019	—	`conf`	Counterfactual Reasoning for Fair Clinical Risk Prediction. MLHC Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah
2019	J	`jnl`	Federated and Differentially Private Learning for Electronic Health Records. CoRR Stephen R. Pfohl, Andrew M. Dai, Katherine A. Heller
2018	Misc	`conf`	Transfer learning to adapt predictive models for pediatric patients in the EHR. AMIA Stephen R. Pfohl, Nigam Shah
2018	J	`jnl`	Unraveling the Complexity of Amyotrophic Lateral Sclerosis Survival Prediction. Frontiers Neuroinformatics Stephen R. Pfohl, Renaid B. Kim, Grant S. Coan, Cassie S. Mitchell