Divyam Madaan

I am a fourth year Ph.D. student at New York University, Courant Institute of Mathematical Sciences, under the supervision of Sumit Chopra and Kyunghyun Cho. Previously, I completed my Masters at Machine Learning and Artificial Intelligence (MLAI) Lab in Korea Advanced Institute of Science and Technology (KAIST), where I was advised by Sung Ju Hwang. My research has two primary objectives: (a) develop methods that can harness information from multiple modalities, and (b) improve the model's ability to perform consistently in future time periods.

Publications

Predicting Alzheimer’s Diseases and Related Dementias in 3‐year timeframe with AI Foundation Model on Electronic Health Records

Weicheng Zhu, Huanze Tang, H. Rajamohan, Divyam Madaan, Ankush Chaudhari, Shih‐Lun Huang, Xinyue Ma, S. Chopra, John A Dodson, Abraham A. Brody, Arjun V. Masurkar, N. Razavian

Alzheimer's & Dementia 2024

ABS
HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis

HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis

Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, S. Chopra, Divyam Madaan

arXiv.org 2024

ABSPDF
Jointly Modeling Inter-&Intra-Modality Dependencies for Multi-modal Learning

Jointly Modeling Inter-&Intra-Modality Dependencies for Multi-modal Learning

Divyam Madaan, Taro Makino, S. Chopra, Kyunghyun Cho

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Predicting Risk of Alzheimer’s Diseases and Related Dementias with AI Foundation Model on Electronic Health Records

Weicheng Zhu, Huanze Tang, Hao Zhang, H. Rajamohan, Shih‐Lun Huang, Xinyue Ma, Ankush Chaudhari, Divyam Madaan, Elaf Almahmoud, S. Chopra, John A Dodson, Abraham A. Brody, A. Masurkar, N. Razavian

medRxiv 2024

ABS
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis

On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis

Divyam Madaan, D. Sodickson, K. Cho, S. Chopra

International Conference on Medical Imaging with Deep Learning 2023

ABSHTMLPDF
Heterogeneous Continual Learning

Heterogeneous Continual Learning

Divyam Madaan, Hongxu Yin, Wonmin Byeon, J. Kautz, Pavlo Molchanov

Computer Vision and Pattern Recognition 2023

ABSHTMLPDF
Improving Representational Continuity via Continued Pretraining

Improving Representational Continuity via Continued Pretraining

Michael Sun, Ananya Kumar, Divyam Madaan, Percy Liang

ABSPDF
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey

What Do NLP Researchers Believe? Results of the NLP Community Metasurvey

Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Sam Bowman

Annual Meeting of the Association for Computational Linguistics 2022

ABSPDF
Representational Continuity for Unsupervised Continual Learning

Representational Continuity for Unsupervised Continual Learning

Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang

International Conference on Learning Representations 2021

ABSPDF
Online Coreset Selection for Rehearsal-based Continual Learning

Online Coreset Selection for Rehearsal-based Continual Learning

Jaehong Yoon, Divyam Madaan, Eunho Yang, S. Hwang

International Conference on Learning Representations 2021

ABSPDF
Learning to Generate Noise for Multi-Attack Robustness

Learning to Generate Noise for Multi-Attack Robustness

Divyam Madaan, Jinwoo Shin, S. Hwang

International Conference on Machine Learning 2020

ABSPDF
Learning to Generate Noise for Robustness against Multiple Perturbations

Learning to Generate Noise for Robustness against Multiple Perturbations

Divyam Madaan, Jinwoo Shin, Sung Ju Hwang

arXiv.org 2020

Adversarial Neural Pruning with Latent Vulnerability Suppression

Adversarial Neural Pruning with Latent Vulnerability Suppression

Divyam Madaan, Jinwoo Shin, Sung Ju Hwang

International Conference on Machine Learning 2019

Adversarial Neural Pruning

Adversarial Neural Pruning

Divyam Madaan, Sung Ju Hwang

arXiv.org 2019

ABSPDF
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting

VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting

Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall

IEEE Global Conference on Signal and Information Processing 2019

ABSPDF
Real Time Attention Based Bidirectional Long Short-Term Memory Networks for Air Pollution Forecasting

Real Time Attention Based Bidirectional Long Short-Term Memory Networks for Air Pollution Forecasting

Radhika Dua, Divyam Madaan, Prerana Mukherjee, Brejesh Lall

International Conference on Big Data Computing Service and Applications 2019

ABS

A Background Report on Usability of Australian E-Government Website

Divyam Madaan

Assessing the Usability and Accessibility of Austrian E-Government Website

Divyam Madaan

Improving Representational Continuity via Continued Pretraining

Michael Sun, Ananya Kumar, Divyam Madaan, Percy Liang

arXiv.org 2023

ABSPDF
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning

Rethinking the Representational Continuity: Towards Unsupervised Continual Learning

Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang

arXiv.org 2021

Improvement of contrast of images in Poor Light : a Research and Analysis

Improvement of contrast of images in Poor Light : a Research and Analysis

Divyam Madaan, Sonia Chaudhary, Susheel Kumar, Jind

Empirical Comparison & Analysis of Shuffle Exchange Network and Its Variants

Empirical Comparison & Analysis of Shuffle Exchange Network and Its Variants

Sonia Chaudhary, Divyam Madaan, Susheel Kumar, Jind

Review on Human Computer Interaction Learning From History & Need of Rethinking

Review on Human Computer Interaction Learning From History & Need of Rethinking

S. Lata, Divyam Madaan, Sonia Chaudhary