Divyam Madaan

I am a fifth year Ph.D. student at New York University, Courant Institute of Mathematical Sciences, advised by Sumit Chopra and Kyunghyun Cho. Previously, I completed my Masters at the MLAI Lab at KAIST, advised by Sung Ju Hwang.

My research focuses on (a) developing methods that harness information from multiple modalities, and (b) improving models' ability to generalize across time.

Read Formal Bio →

Publications

Full list on Google Scholar

Divyam Madaan, Sumit Chopra, Kyunghyun Cho
International Conference on Learning Representations (ICLR) 2026 Conference
Divyam Madaan, Varshan Muhunthan, Kyunghyun Cho, Sumit Chopra
International Conference on Learning Representations (ICLR) 2026 Conference
Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho
Neural Information Processing Systems (NeurIPS) 2024 Conference
Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan
Machine Learning for Health (ML4H) 2024 Conference
Weicheng Zhu, Huanze Tang, Hao Zhang, Haresh Rengaraj Rajamohan, Shih-Lun Huang, Xinyue Ma, Ankush Chaudhari, Divyam Madaan, Elaf Almahmoud, Sumit Chopra, John A Dodson, Abraham A Brody, Arjun V Masurkar, Narges Razavian
Alzheimer's Association International Conference 2024 Conference
Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov
Conference on Computer Vision and Pattern Recognition (CVPR) 2023 (Highlight) Conference
Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
Association for Computational Linguistics (ACL) 2023 Conference
Divyam Madaan, Daniel Sodickson, Kyunghyun Cho, Sumit Chopra
Medical Imaging with Deep Learning (MIDL) 2023 Conference
Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang
International Conference on Learning Representations (ICLR) 2022 (Oral presentation) Conference
Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang
International Conference on Learning Representations (ICLR) 2022 Conference
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
International Conference for Machine Learning (ICML) 2021 Conference
NeurIPS Meta-Learning Workshop 2020 Workshop
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
International Conference for Machine Learning (ICML) 2020 Conference
NeurIPS Safety and Robustness in Decision Making Workshop 2019 Workshop
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall
IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2019 Conference
Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara, Divyam Madaan, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton
Preprint 2019 Preprint

Academic Service

Conference Reviewer

  • Neural Information Processing Systems (NeurIPS) (2020 – 2025)
  • International Conference on Machine Learning (ICML) (2020 – 2025)
  • International Conference on Learning Representations (ICLR) (2022 – 2026)
  • Conference on Lifelong Learning Agents (CoLLAs) (2023, 2025)
  • Conference on Health, Inference, and Learning (CHIL) 2025
  • International Conference on Artificial Intelligence and Statistics (AISTATS) 2025
  • Association for the Advancement of Artificial Intelligence (AAAI) 2021
  • Asian Conference on Machine Learning (ACML) 2019-2020

Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • International Journal of Computer Vision (IJCV)
  • Transactions on Machine Learning Research (TMLR)

Workshop Reviewer

  • ContinualAI Unconference 2023
  • NeurIPS MetaLearning Workshop 2020
  • ICML New Frontiers in Adversarial Machine Learning Workshop 2020

Volunteer

  • International Conference on Learning Representations (ICLR) (2020, 2022)
  • International Conference on Machine Learning (ICML) (2020, 2021)
  • Neural Information Processing Systems (NeurIPS) (2020, 2022)

Teaching

New York University, Teaching Assistant (Fall 2022 – Spring 2025)

  • Machine Learning (DS-GA 1003) – Spring 2025
  • Natural Language Processing with Representation Learning (DS-GA 1011) – Fall 2024
  • Causal Inference (DS-GA 3001) – Spring 2024
  • Fundamentals of Machine Learning (CSCI-UA 473) – Fall 2023, 2025
  • Machine Learning for Healthcare (CSCI-GA 3033 / DS-GA 3001) – Fall 2022