Shengpu Tang

According to our database, Shengpu Tang authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Off by a beat: the effects of temporal misalignment in reinforcement learning for sepsis treatment.

Shengpu Tang, Jiayu Yao, Jenna Wiens, Sonali Parbhoo

npj Digit. Medicine, 2026

2025

Exploring Time-Step Size in Reinforcement Learning for Sepsis Treatment.

Yingchuan Sun, Shengpu Tang

CoRR, November, 2025

An Adaptive Machine Learning Triage Framework for Predicting Alzheimer's Disease Progression.

Richard Hou, Shengpu Tang, Wei Jin

CoRR, November, 2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025.

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen, Niharika D'Souza, Jason A. Fries, Yixing Jiang, Aparajita Kashyap, Chanwoo Kim, Simon A. Lee, Aishwarya Mandyam, Ashery Christopher Mbilinyi, Nikita Mehandru, Nitish Nagesh, Brighton Nuwagira, Emma Pierson, Arvind Pillai, Akane Sano, Tanveer F. Syeda-Mahmood, Shashank Yadav, Elias Adhanom, Muhammad Umar Afza, Amelia Archer, Suhana Bedi, Vasiliki Bikia, Trenton Chang, George H. Chen, Winston Chen, Erica Chiang, Edward Choi, Octavia Ciora, Paz Dozie-Nnamah, Shaza Elsharief, Matthew Engelhard, Ali Eshragh, Jean Feng, Josh Fessel, Scott L. Fleming, Kei Sen Fong, Thomas Frost, Soham Gadgil, Judy Gichoya, Leeor Hershkovich, Sujeong Im, Bhavya Jain, Vincent Jeanselme, Furong Jia, Qixuan Jin, Yuxuan Jin, Daniel Kapash, Geetika Kapoor, Behdokht Kiafar, Matthias Kleiner, Stefan Kraft, Annika Kumar, Daeun Kyung, Zhongyuan Liang, Joanna Lin, Qianchu Liu, Chang Liu, Hongzhou Luan, Chris Lunt, Leopoldo Julian Lechuga López, Matthew B. A. McDermott, Shahriar Noroozizadeh, Connor O'Brien, YongKyung Oh, Mixail Ota, Stephen Pfohl, Meagan Pi, Tanmoy Sarkar Pias, Emma Rocheteau, Avishaan Sethi, Toru Shirakawa, Anita Silver, Neha Simha, Kamile Stankeviciute, Max Sunog, Peter Szolovits, Shengpu Tang, Jialu Tang, Aaron Tierney, John Valdovinos, Byron Wallace, Will Ke Wang, Peter Washington, Jeremy C. Weiss, Daniel Wolfe, Emily Wong, Hye Sun Yun, Xiaoman Zhang, Xiao Yu Cindy Zhang, Hayoung Jeong, Kaveri A. Thakoor

CoRR, October, 2025

Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning.

Ziyan Wang, Zheng Wang, Jie Fu, Xingwei Qu, Qi Cheng, Shengpu Tang, Minjia Zhang, Xiaoming Huo

CoRR, October, 2025

PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation.

Juntong Ni, Saurabh Kataria, Shengpu Tang, Carl Yang, Xiao Hu, Wei Jin

CoRR, September, 2025

Transforming Healthcare Decision Making Using Artificial Intelligence.

Shengpu Tang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Towards Clinically Applicable Reinforcement Learning

Shengpu Tang

PhD thesis, 2024

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation.

Aishwarya Mandyam, Shengpu Tang, Jiayu Yao, Jenna Wiens, Barbara E. Engelhardt

CoRR, 2024

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

Leveraging Factored Action Spaces for Off-Policy Evaluation.

Aaman Rebello, Shengpu Tang, Jenna Wiens, Sonali Parbhoo

CoRR, 2023

Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation.

Shengpu Tang, Jenna Wiens

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Machine Learning for Health (ML4H) 2023.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel N. Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen

Proceedings of the Machine Learning for Health, 2023

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

Towards Data-Driven Offline Simulations for Online Reinforcement Learning.

Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman

CoRR, 2022

Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare.

Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Machine Learning for Health (ML4H) 2022.

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

Proceedings of the Machine Learning for Health, 2022

2021

Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings.

Shengpu Tang, Jenna Wiens

Proceedings of the Machine Learning for Healthcare Conference, 2021

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

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies.

Shengpu Tang, Aditya Modi, Michael W. Sjoding, Jenna Wiens

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series.

Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael W. Sjoding, Jenna Wiens

Proceedings of the Machine Learning for Healthcare Conference, 2019