Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series. - Jeeheh Oh; Jiaxuan Wang; Shengpu Tang; Michael W. Sjoding; Jenna Wiens (MLHC, 2019)

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies. - Shengpu Tang; Aditya Modi 002; Michael W. Sjoding; Jenna Wiens (ICML, 2020)

Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data. - Shengpu Tang; Parmida Davarmanesh; Yanmeng Song; Danai Koutra; Michael W. Sjoding; Jenna Wiens (J. Am. Medical Informatics Assoc., 2020)

Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings. - Shengpu Tang; Jenna Wiens (MLHC, 2021)

Machine Learning for Health (ML4H) 2022. - Antonio Parziale; Monica Agrawal; Shengpu Tang; Kristen Severson 001; Luis Oala; Adarsh Subbaswamy; Sayantan Kumar; Elora D. M. Schörverth; Stefan Hegselmann; Helen Zhou; Ghada Zamzmi; Purity Mugambi; et al. (ML4H@NeurIPS, 2022)

Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. - Shengpu Tang; Maggie Makar; Michael W. Sjoding; Finale Doshi-Velez; Jenna Wiens (NeurIPS, 2022)

Towards Data-Driven Offline Simulations for Online Reinforcement Learning. - Shengpu Tang; Felipe Vieira Frujeri; Dipendra Misra; Alex Lamb; John Langford 001; Paul Mineiro; Sebastian Kochman (CoRR, 2022)

Machine Learning for Health symposium 2022 - Extended Abstract track. - Antonio Parziale; Monica Agrawal; Shalmali Joshi; Irene Y. Chen; Shengpu Tang; Luis Oala; Adarsh Subbaswamy (CoRR, 2022)

Machine Learning for Health (ML4H) 2023. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Kristen Severson 001; Mercy Nyamewaa Asiedu; Serina Chang; Bonaventure F. P. Dossou; Qian Huang; Fahad Kamran; Haoran Zhang 003; Sujay Nagaraj; et al. (ML4H@NeurIPS, 2023)

Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation. - Shengpu Tang; Jenna Wiens (NeurIPS, 2023)

Leveraging Factored Action Spaces for Off-Policy Evaluation. - Aaman Rebello; Shengpu Tang; Jenna Wiens; Sonali Parbhoo (CoRR, 2023)

Machine Learning for Health symposium 2023 - Findings track. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Mercy Nyamewaa Asiedu; Serina Chang; Thomas Hartvigsen; Harvineet Singh (CoRR, 2023)

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation. - Aishwarya Mandyam; Shengpu Tang; Jiayu Yao; Jenna Wiens; Barbara E. Engelhardt (CoRR, 2024)

Towards Clinically Applicable Reinforcement Learning - Shengpu Tang (2024)

Transforming Healthcare Decision Making Using Artificial Intelligence. - Shengpu Tang (AAAI, 2025)