Shalmali Joshi

63 papers A* 5A 3C 2Journal 38Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A pipeline for enabling path-specific causal fairness in observational health data. CoRR Aparajita Kashyap, Sara Matijevic, Noémie Elhadad, Steven A. Kushner, Shalmali Joshi
2026	J	`jnl`	One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models. CoRR Zilin Jing, Vincent Jeanselme, Yuta Kobayashi, Simon A. Lee, Chao Pang, Aparajita Kashyap, Yanwei Li, Xinzhuo Jiang, Shalmali Joshi
2025	J	`jnl`	A Planning Framework for Adaptive Labeling. CoRR Daksh Mittal, Yuanzhe Ma, Shalmali Joshi, Hongseok Namkoong
2025	—	`conf`	ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression. MLHC Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad
2025	J	`jnl`	ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression. CoRR Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad
2025	J	`jnl`	AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. J. Am. Medical Informatics Assoc. Shalmali Joshi, Iñigo Urteaga, Wouter A. C. van Amsterdam, George Hripcsak, Pierre A. Elias, Benjamin R. C. Amor, Noémie Elhadad, James C. Fackler, Mark P. Sendak, Jenna Wiens, Kaivalya Deshpande, Yoav Wald, Madalina Fiterau, Zachary C. Lipton, Daniel Malinsky, Madhur Nayan, Hongseok Namkoong, Soojin Park, Julia E. Vogt, Rajesh Ranganath
2025	J	`jnl`	CEHR-XGPT: A Scalable Multi-Task Foundation Model for Electronic Health Records. CoRR Chao Pang, Jiheum Park, Xinzhuo Jiang, Nishanth Parameshwar Pavinkurve, Krishna S. Kalluri, Shalmali Joshi, Noémie Elhadad, Karthik Natarajan
2025	J	`jnl`	Explainable AI: definition and attributes of a good explanation for health AI. AI Ethics Evangelia Kyrimi, Scott McLachlan, Jared M. Wohlgemut, Zane B. Perkins, David A. Lagnado, William Marsh, Alexander Gimson, Ali Shafti, Ari Ercole, Amitava Banerjee, Ben Glocker, Burkhard Schafer, Constantine Gatsonis, Crina Grosan, Danielle Sent, David S. Berman, David Glass, Declan P. O'Regan, Dimitrios Letsios, Dylan Morrissey, Erhan Pisirir, Francesco Leofante, Hamit Soyel, Jon Williamson, Keri Grieman, Kudakwashe Dube, Max Marsden, Myura Nagendran, Nigel Tai, Olga Kostopoulou, Owain Jones, Paul Curzon, Rebecca S. Stoner, Sankalp Tandle, Shalmali Joshi, Somayyeh Mossadegh, Stefan Buijsman, Tim Miller, Vince Istvan Madai
2025	J	`jnl`	FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records. CoRR Chao Pang, Vincent Jeanselme, Young Sang Choi, Xinzhuo Jiang, Zilin Jing, Aparajita Kashyap, Yuta Kobayashi, Yanwei Li, Florent Pollet, Karthik Natarajan, Shalmali Joshi
2025	J	`jnl`	ICYM2I: The illusion of multimodal informativeness under missingness. CoRR Young Sang Choi, Vincent Jeanselme, Pierre A. Elias, Shalmali Joshi
2025	J	`jnl`	Learning-To-Measure: In-context Active Feature Acquisition. CoRR Yuta Kobayashi, Zilin Jing, Jiayu Yao, Hongseok Namkoong, Shalmali Joshi
2025	J	`jnl`	Mind the data gap: Missingness Still Shapes Large Language Model Prognoses. CoRR Yuta Kobayashi, Vincent Jeanselme, Shalmali Joshi
2025	J	`jnl`	Path-specific effects for pulse-oximetry guided decisions in critical care. CoRR Kevin Zhang, Yonghan Jung, Divyat Mahajan, Karthikeyan Shanmugam, Shalmali Joshi
2025	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 15-16 August 2025, Mayo Clinic, Rochester, MN, USA MLHC Monica Agrawal, Kaivalya Deshpande, Matthew Engelhard, Shalmali Joshi, Shengpu Tang, Iñigo Urteaga
2025	J	`jnl`	The evaluation illusion of large language models in medicine. npj Digit. Medicine Monica Agrawal, Irene Y. Chen, Freya Gulamali, Shalmali Joshi
2024	A*	`conf`	Adaptive Labeling for Efficient Out-of-distribution Model Evaluation. NeurIPS Daksh Mittal, Yuanzhe Ma, Shalmali Joshi, Hongseok Namkoong
2024	—	`ed.`	Machine Learning for Healthcare Conference, 16-17 August 2024, Toronto, Canada. MLHC Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga
2024	A*	`conf`	Towards Safe Policy Learning under Partial Identifiability: A Causal Approach. AAAI Shalmali Joshi, Junzhe Zhang, Elias Bareinboim
2023	A*	`conf`	"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
2023	J	`jnl`	A normative framework for artificial intelligence as a sociotechnical system in healthcare. Patterns Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London
2023	J	`jnl`	Learning-to-defer for sequential medical decision-making under uncertainty. Trans. Mach. Learn. Res. Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
2023	—	`ed.`	Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. MLHC Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung
2023	J	`jnl`	Making machine learning matter to clinicians: model actionability in medical decision-making. npj Digit. Medicine Daniel Ehrmann, Shalmali Joshi, Sebastian D. Goodfellow, Mjaye Mazwi, Danny Eytan
2023	—	`conf`	What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB. FAccT Melissa D. McCradden, Oluwadara Odusi, Shalmali Joshi, Ismail Akrout, Kagiso Ndlovu, Ben Glocker, Gabriel Maicas, Xiaoxuan Liu, Mjaye Mazwi, Tee Garnett, Lauren Oakden-Rayner, Myrtede Alfred, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg
2022	J	`jnl`	"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
2022	—	`conf`	Counterfactually Guided Policy Transfer in Clinical Settings. CHIL Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi
2022	A	`conf`	Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. AISTATS Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju
2022	J	`jnl`	Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. CoRR Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez
2022	—	`conf`	Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi
2022	J	`jnl`	Machine Learning for Health symposium 2022 - Extended Abstract track. CoRR Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
2022	—	`ed.`	Machine Learning for Health, ML4H 2022, 28 November 2022, New Orleans, Lousiana, USA & Virtual. ML4H@NeurIPS Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
2022	C	`conf`	Towards Robust Off-Policy Evaluation via Human Inputs. AIES Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2022	J	`jnl`	Towards Robust Off-Policy Evaluation via Human Inputs. CoRR Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2021	J	`jnl`	An Empirical Framework for Domain Generalization in Clinical Settings. CoRR Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
2021	—	`conf`	An empirical framework for domain generalization in clinical settings. CHIL Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
2021	—	`conf`	Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. FAccT Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi
2021	J	`jnl`	Learning Under Adversarial and Interventional Shifts. CoRR Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2021	J	`jnl`	On the Connections between Counterfactual Explanations and Adversarial Examples. CoRR Martin Pawelczyk, Shalmali Joshi, Chirag Agarwal, Sohini Upadhyay, Himabindu Lakkaraju
2021	J	`jnl`	Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. CoRR Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
2021	A	`conf`	Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CIKM Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
2021	J	`jnl`	Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CoRR Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
2021	A*	`conf`	Towards Robust and Reliable Algorithmic Recourse. NeurIPS Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
2021	J	`jnl`	Towards Robust and Reliable Algorithmic Recourse. CoRR Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
2020	—	`conf`	Confounding Feature Acquisition for Causal Effect Estimation. ML4H@NeurIPS Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
2020	J	`jnl`	Confounding Feature Acquisition for Causal Effect Estimation. CoRR Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
2020	J	`jnl`	Counterfactually Guided Policy Transfer in Clinical Settings. CoRR Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi
2020	J	`jnl`	Ethical Machine Learning in Health Care. CoRR Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
2020	J	`jnl`	Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. J. Am. Medical Informatics Assoc. Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul
2020	J	`jnl`	Probabilistic Machine Learning for Healthcare. CoRR Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath
2020	J	`jnl`	Sequential Explanations with Mental Model-Based Policies. CoRR Arnold Y. S. Yeung, Shalmali Joshi, Joseph Jay Williams, Frank Rudzicz
2020	J	`jnl`	What went wrong and when? Instance-wise Feature Importance for Time-series Models. CoRR Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg
2020	A*	`conf`	What went wrong and when? Instance-wise feature importance for time-series black-box models. NeurIPS Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg
2020	C	`conf`	When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning. AIES Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson
2019	J	`jnl`	Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. CoRR Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk, Been Kim, Joydeep Ghosh
2019	—	`conf`	What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
2019	J	`jnl`	What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. CoRR Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
2018	A	`conf`	Co-regularized Monotone Retargeting for Semi-supervised LeTOR. SDM Shalmali Joshi, Rajiv Khanna, Joydeep Ghosh
2018	J	`jnl`	xGEMs: Generating Examplars to Explain Black-Box Models. CoRR Shalmali Joshi, Oluwasanmi Koyejo, Been Kim, Joydeep Ghosh
2016	—	`conf`	Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. MLHC Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh
2016	J	`jnl`	Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. CoRR Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh
2016	J	`jnl`	Rényi divergence minimization based co-regularized multiview clustering. Mach. Learn. Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo
2015	—	`conf`	Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes. ICHI Shalmali Joshi, Oluwasanmi Koyejo, Kristine Resurreccion, Joydeep Ghosh
2015	—	`conf`	Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. ICHI Shalmali Joshi, Oluwasanmi Koyejo, Joydeep Ghosh