Aishwarya Mandyam

According to our database, Aishwarya Mandyam authored at least 11 papers between 2021 and 2025.

Collaborative distances:

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

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 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 Weiss, Daniel Wolfe, Emily Wong, Hye Sun Yun, Xiaoman Zhang, Xiao Yu Cindy Zhang, Hayoung Jeong, Kaveri A. Thakoor

CoRR, October, 2025

PERRY: Policy Evaluation with Confidence Intervals using Auxiliary Data.

Aishwarya Mandyam, Jason Meng, Ge Gao, Jiankai Sun, Mac Schwager, Barbara E. Engelhardt, Emma Brunskill

CoRR, July, 2025

2024

KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning.

Aishwarya Mandyam, Didong Li, Andrew Jones, Diana Cai, Barbara E. Engelhardt

Trans. Mach. Learn. Res., 2024

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation.

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

CoRR, 2024

Machine Learning for Health (ML4H) 2024.

Helen Zhou, Stefan Hegselmann, Elizabeth Healey, Trenton Chang, Caleb Ellington, Michael Leone, Vishwali Mhasawade, Sana Tonekaboni, Winston Chen, Hyewon Jeong, Xiaoxiao Li, Juyeon Heo, Payal Chandak, Ayush Noori, Sarah Jabbour, Jessica Dafflon, Jerry Ji, Jivat Neet Kaur, Amin Adibi, Xu Cao, Meera Krishnamoorthy, Yidi Huang, Fabian Gröger, Aishwarya Mandyam, Niloufar Saharhkhiz, Teya S. Bergamaschi, William Boag, Jeroen Berrevoets, Matthew Lee, Kyle Heuton, Peniel N. Argaw, Haoran Zhang

Proceedings of the Machine Learning for Health, 2024

Adaptive Interventions with User-Defined Goals for Health Behavior Change.

Aishwarya Mandyam, Matthew Jörke, William Denton, Barbara E. Engelhardt, Emma Brunskill

Proceedings of the Conference on Health, 2024

2023

Adaptive Interventions with User-Defined Goals for Health Behavior Change.

Aishwarya Mandyam, Matthew Jörke, Barbara E. Engelhardt, Emma Brunskill

CoRR, 2023

Kernel Density Bayesian Inverse Reinforcement Learning.

Aishwarya Mandyam, Didong Li, Diana Cai, Andrew Jones, Barbara E. Engelhardt

CoRR, 2023

Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations.

Aishwarya Mandyam, Andrew Jones, Jiayu Yao, Krzysztof Laudanski, Barbara E. Engelhardt

Proceedings of the Machine Learning for Health, 2023

2021

Nested Policy Reinforcement Learning.

Aishwarya Mandyam, Andrew Jones, Krzysztof Laudanski, Barbara E. Engelhardt

CoRR, 2021

COP-E-CAT: cleaning and organization pipeline for EHR computational and analytic tasks.

Aishwarya Mandyam, Elizabeth C. Yoo, Jeff Soules, Krzysztof Laudanski, Barbara E. Engelhardt

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021