Saved in:
Bibliographic Details
Main Authors: Alsentzer, Emily, Charpignon, Marie-Laure, Chen, Bill, D'Souza, Niharika, Fries, Jason, Jiang, Yixing, Kashyap, Aparajita, Kim, Chanwoo, Lee, Simon, Mandyam, Aishwarya, Mbilinyi, Ashery, Mehandru, Nikita, Nagesh, Nitish, Nuwagira, Brighton, Pierson, Emma, Pillai, Arvind, Sano, Akane, Syeda-Mahmood, Tanveer, Yadav, Shashank, Adhanom, Elias, Afza, Muhammad Umar, Archer, Amelia, Bedi, Suhana, Bikia, Vasiliki, Chang, Trenton, Chen, George H., Chen, Winston, Chiang, Erica, Choi, Edward, Ciora, Octavia, Dozie-Nnamah, Paz, Elsharief, Shaza, Engelhard, Matthew, Eshragh, Ali, Feng, Jean, Fessel, Josh, Fleming, Scott, Fong, Kei Sen, Frost, Thomas, Gadgil, Soham, Gichoya, Judy, Hershkovich, Leeor, Im, Sujeong, Jain, Bhavya, Jeanselme, Vincent, Jia, Furong, Jin, Qixuan, Jin, Yuxuan, Kapash, Daniel, Kapoor, Geetika, Kiafar, Behdokht, Kleiner, Matthias, Kraft, Stefan, Kumar, Annika, Kyung, Daeun, Liang, Zhongyuan, Lin, Joanna, Liu, Qianchu, Liu, Chang, Luan, Hongzhou, Lunt, Chris, López, Leopoldo Julían Lechuga, McDermott, Matthew B. A., Noroozizadeh, Shahriar, O'Brien, Connor, Oh, YongKyung, Ota, Mixail, Pfohl, Stephen, Pi, Meagan, Pias, Tanmoy Sarkar, Rocheteau, Emma, Sethi, Avishaan, Shirakawa, Toru, Silver, Anita, Simha, Neha, Stankeviciute, Kamile, Sunog, Max, Szolovits, Peter, Tang, Shengpu, Tang, Jialu, Tierney, Aaron, Valdovinos, John, Wallace, Byron, Wang, Will Ke, Washington, Peter, Weiss, Jeremy, Wolfe, Daniel, Wong, Emily, Yun, Hye Sun, Zhang, Xiaoman, Zhang, Xiao Yu Cindy, Jeong, Hayoung, Thakoor, Kaveri A.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.15217
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914133175173120
author Alsentzer, Emily
Charpignon, Marie-Laure
Chen, Bill
D'Souza, Niharika
Fries, Jason
Jiang, Yixing
Kashyap, Aparajita
Kim, Chanwoo
Lee, Simon
Mandyam, Aishwarya
Mbilinyi, Ashery
Mehandru, Nikita
Nagesh, Nitish
Nuwagira, Brighton
Pierson, Emma
Pillai, Arvind
Sano, Akane
Syeda-Mahmood, Tanveer
Yadav, Shashank
Adhanom, Elias
Afza, Muhammad Umar
Archer, Amelia
Bedi, Suhana
Bikia, Vasiliki
Chang, Trenton
Chen, George H.
Chen, Winston
Chiang, Erica
Choi, Edward
Ciora, Octavia
Dozie-Nnamah, Paz
Elsharief, Shaza
Engelhard, Matthew
Eshragh, Ali
Feng, Jean
Fessel, Josh
Fleming, Scott
Fong, Kei Sen
Frost, Thomas
Gadgil, Soham
Gichoya, Judy
Hershkovich, Leeor
Im, Sujeong
Jain, Bhavya
Jeanselme, Vincent
Jia, Furong
Jin, Qixuan
Jin, Yuxuan
Kapash, Daniel
Kapoor, Geetika
Kiafar, Behdokht
Kleiner, Matthias
Kraft, Stefan
Kumar, Annika
Kyung, Daeun
Liang, Zhongyuan
Lin, Joanna
Liu, Qianchu
Liu, Chang
Luan, Hongzhou
Lunt, Chris
López, Leopoldo Julían Lechuga
McDermott, Matthew B. A.
Noroozizadeh, Shahriar
O'Brien, Connor
Oh, YongKyung
Ota, Mixail
Pfohl, Stephen
Pi, Meagan
Pias, Tanmoy Sarkar
Rocheteau, Emma
Sethi, Avishaan
Shirakawa, Toru
Silver, Anita
Simha, Neha
Stankeviciute, Kamile
Sunog, Max
Szolovits, Peter
Tang, Shengpu
Tang, Jialu
Tierney, Aaron
Valdovinos, John
Wallace, Byron
Wang, Will Ke
Washington, Peter
Weiss, Jeremy
Wolfe, Daniel
Wong, Emily
Yun, Hye Sun
Zhang, Xiaoman
Zhang, Xiao Yu Cindy
Jeong, Hayoung
Thakoor, Kaveri A.
author_facet Alsentzer, Emily
Charpignon, Marie-Laure
Chen, Bill
D'Souza, Niharika
Fries, Jason
Jiang, Yixing
Kashyap, Aparajita
Kim, Chanwoo
Lee, Simon
Mandyam, Aishwarya
Mbilinyi, Ashery
Mehandru, Nikita
Nagesh, Nitish
Nuwagira, Brighton
Pierson, Emma
Pillai, Arvind
Sano, Akane
Syeda-Mahmood, Tanveer
Yadav, Shashank
Adhanom, Elias
Afza, Muhammad Umar
Archer, Amelia
Bedi, Suhana
Bikia, Vasiliki
Chang, Trenton
Chen, George H.
Chen, Winston
Chiang, Erica
Choi, Edward
Ciora, Octavia
Dozie-Nnamah, Paz
Elsharief, Shaza
Engelhard, Matthew
Eshragh, Ali
Feng, Jean
Fessel, Josh
Fleming, Scott
Fong, Kei Sen
Frost, Thomas
Gadgil, Soham
Gichoya, Judy
Hershkovich, Leeor
Im, Sujeong
Jain, Bhavya
Jeanselme, Vincent
Jia, Furong
Jin, Qixuan
Jin, Yuxuan
Kapash, Daniel
Kapoor, Geetika
Kiafar, Behdokht
Kleiner, Matthias
Kraft, Stefan
Kumar, Annika
Kyung, Daeun
Liang, Zhongyuan
Lin, Joanna
Liu, Qianchu
Liu, Chang
Luan, Hongzhou
Lunt, Chris
López, Leopoldo Julían Lechuga
McDermott, Matthew B. A.
Noroozizadeh, Shahriar
O'Brien, Connor
Oh, YongKyung
Ota, Mixail
Pfohl, Stephen
Pi, Meagan
Pias, Tanmoy Sarkar
Rocheteau, Emma
Sethi, Avishaan
Shirakawa, Toru
Silver, Anita
Simha, Neha
Stankeviciute, Kamile
Sunog, Max
Szolovits, Peter
Tang, Shengpu
Tang, Jialu
Tierney, Aaron
Valdovinos, John
Wallace, Byron
Wang, Will Ke
Washington, Peter
Weiss, Jeremy
Wolfe, Daniel
Wong, Emily
Yun, Hye Sun
Zhang, Xiaoman
Zhang, Xiao Yu Cindy
Jeong, Hayoung
Thakoor, Kaveri A.
contents The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025, at the University of California, Berkeley, in Berkeley, California, USA. As part of this year's program, we hosted Research Roundtables to catalyze collaborative, small-group dialogue around critical, timely topics at the intersection of machine learning and healthcare. Each roundtable was moderated by a team of senior and junior chairs who fostered open exchange, intellectual curiosity, and inclusive engagement. The sessions emphasized rigorous discussion of key challenges, exploration of emerging opportunities, and collective ideation toward actionable directions in the field. In total, eight roundtables were held by 19 roundtable chairs on topics of "Explainability, Interpretability, and Transparency," "Uncertainty, Bias, and Fairness," "Causality," "Domain Adaptation," "Foundation Models," "Learning from Small Medical Data," "Multimodal Methods," and "Scalable, Translational Healthcare Solutions."
format Preprint
id arxiv_https___arxiv_org_abs_2510_15217
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Alsentzer, Emily
Charpignon, Marie-Laure
Chen, Bill
D'Souza, Niharika
Fries, Jason
Jiang, Yixing
Kashyap, Aparajita
Kim, Chanwoo
Lee, Simon
Mandyam, Aishwarya
Mbilinyi, Ashery
Mehandru, Nikita
Nagesh, Nitish
Nuwagira, Brighton
Pierson, Emma
Pillai, Arvind
Sano, Akane
Syeda-Mahmood, Tanveer
Yadav, Shashank
Adhanom, Elias
Afza, Muhammad Umar
Archer, Amelia
Bedi, Suhana
Bikia, Vasiliki
Chang, Trenton
Chen, George H.
Chen, Winston
Chiang, Erica
Choi, Edward
Ciora, Octavia
Dozie-Nnamah, Paz
Elsharief, Shaza
Engelhard, Matthew
Eshragh, Ali
Feng, Jean
Fessel, Josh
Fleming, Scott
Fong, Kei Sen
Frost, Thomas
Gadgil, Soham
Gichoya, Judy
Hershkovich, Leeor
Im, Sujeong
Jain, Bhavya
Jeanselme, Vincent
Jia, Furong
Jin, Qixuan
Jin, Yuxuan
Kapash, Daniel
Kapoor, Geetika
Kiafar, Behdokht
Kleiner, Matthias
Kraft, Stefan
Kumar, Annika
Kyung, Daeun
Liang, Zhongyuan
Lin, Joanna
Liu, Qianchu
Liu, Chang
Luan, Hongzhou
Lunt, Chris
López, Leopoldo Julían Lechuga
McDermott, Matthew B. A.
Noroozizadeh, Shahriar
O'Brien, Connor
Oh, YongKyung
Ota, Mixail
Pfohl, Stephen
Pi, Meagan
Pias, Tanmoy Sarkar
Rocheteau, Emma
Sethi, Avishaan
Shirakawa, Toru
Silver, Anita
Simha, Neha
Stankeviciute, Kamile
Sunog, Max
Szolovits, Peter
Tang, Shengpu
Tang, Jialu
Tierney, Aaron
Valdovinos, John
Wallace, Byron
Wang, Will Ke
Washington, Peter
Weiss, Jeremy
Wolfe, Daniel
Wong, Emily
Yun, Hye Sun
Zhang, Xiaoman
Zhang, Xiao Yu Cindy
Jeong, Hayoung
Thakoor, Kaveri A.
Machine Learning
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025, at the University of California, Berkeley, in Berkeley, California, USA. As part of this year's program, we hosted Research Roundtables to catalyze collaborative, small-group dialogue around critical, timely topics at the intersection of machine learning and healthcare. Each roundtable was moderated by a team of senior and junior chairs who fostered open exchange, intellectual curiosity, and inclusive engagement. The sessions emphasized rigorous discussion of key challenges, exploration of emerging opportunities, and collective ideation toward actionable directions in the field. In total, eight roundtables were held by 19 roundtable chairs on topics of "Explainability, Interpretability, and Transparency," "Uncertainty, Bias, and Fairness," "Causality," "Domain Adaptation," "Foundation Models," "Learning from Small Medical Data," "Multimodal Methods," and "Scalable, Translational Healthcare Solutions."
title Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
topic Machine Learning
url https://arxiv.org/abs/2510.15217