About Me
I am currently an Intramural Postdoctoral Fellow in the Computational Health Research Branch at National Library of Medicine (NLM) at National Institures on Health (NIH), working with Dr Jeremy Weiss. My research interests broadly lie at the intersection of machine learning and healthcare with applications to medical imaging, clinical NLP and Electronic Health Records (EHR) data.
I finished my PhD in Computer Science and Engineering at Washington University in St Louis. I was jointly supervised by both Dr Philip Payne and Dr Aristeidis Sotiras. My PhD dissertation research focused on investigating novel deep learning methods that can learn intermediate data-driven representations from multimodal healthcare data for interpreting model decisions for patient-specific clinical outcomes.
Before joining WashU, I completed my Bachelor’s in Electrical Engineering from Jadavpur University and my Masters in Technology (M.Tech) from Indian Statistical Institute under the supervision of Dr Swagatam Das. My master’s dissertation research was on the topic “On the Choice of Appropriate Combination of Classifier and Decomposition Scheme for Multiclass Imbalanced Data Classification : A Comparative Analysis”.
For more details about me and my research, please check out my CV.
Recent News
- February 2025 Our work on “Developing Approaches to Incorporate Donor Lung CT Images into Machine Learning Models to Predict Severe Primary Graft Dysfunction after Lung Transplantation” is available online at American Journal of Transplanation. Link to paper.
- January 2025 Our work on “Multimodal Variational Autoencoder: a Barycentric View” has been accepted in AAAI 2025 as an oral presentation. Preprint available.
- December 2024 I successfully defended my PhD dissertation titled “Multimodal representation learning frameworks for modeling progression and heterogeneity in Alzheimer’s Disease”
- October 2024 Our work on Examining heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles has been published in PlOS One.
- September 2024 Our JAMIA Open paper HiMAL: Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting Alzheimer’s disease progression is now published and online.
- May 2024: Presented my research (poster) in IEEE ISBI 2024, Athens, Greece.
- May 2024: Received Honors (top 5%) in the Periodic Review of Doctoral Students (PRODS 2024) in WashU CSE
- February 2024: Paper on Improving multimodal normative modelling using mixture-of-products variational autoencoders accepted in the IEEE ISBI 2024. Preprint available in ArXiv.
- October 2023: 2 NeurIPS 2023 workshop papers accepted in XAI-in-action and Deep Generative Models for Health (DGM4H)
- May 2023: Received Honors (top 5%) in the Periodic Review of Doctoral Students (PRODS 2023) in WashU CSE
- February 2023: Received Student travel award and Robert F. Wagner All-Conference Best Paper Award Finalist at SPIE Medical Imaging 2023
- November 2022: Oral paper on multimodal normative modelling accepted to SPIE Medical Imaging 2023.
- October 2022: Passed CSE dissertation proposal exam
- May 2022: Received Honors (top 5%) in the Periodic Review of Doctoral Students (*PRODS 2022) in WashU CSE
- March 2022: Oral paper on explainable AI in healthcare accepted to ACM BCB 2022 conference
- December 2021: Abstract accepted for oral presentation in AMIA Informatics Summit 2022
- August 2021: Review paper on machine learning techniques on Alzheimer’s Disease diagnosis accepted in JAMIA Open