Kayhan Batmanghelich

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Kayhan Batmanghelich

Assistant Professor
Department of Electrical and Computer Engineering
Boston University

batman@bu.edu
Phone: 617-358-0538
My CV (please contact me)

 

8 St Mary’s St, Office 421
Boston, MA 02215

I am an Assistant Professor at the Department of Electrical and Computer Engineering at Boston University. My research is at the intersection of medical vision (medical image analysis), machine learning, and bioinformatics. I develop algorithms to analyze and understand medical images, genetic data, and other electrical health records, such as clinical reports. The main themes of research in my lab are about the main challenges of AI in healthcare: (1) Explainability, (2) Data Efficiency, (3) Multimodal Data Fusion, and Causality. My lab works on Alzheimer’s Disease, Chronic Obstructive Pulmonary Disease (COPD), and Non-Alcoholic Fatty Liver Disease (NAFLD) projects. Our research is supported by funding from NIH, NSF, and industry awards.  Read More

Recent News

Our method to identify the disease change is out in Radiology AI!

Aug 22, 2024

RSNA Radiology AI journal accepted our paper about disease change identification using an anatomically informed approach. Congrats to Ke and the rest of the team!

MedSyn paper is accepted to TMI!

Jun 05, 2024

Congratulations to Yanwu and Li! MedSyn is the first prompable 3D diffusion model of lung CT!

Our lab received Hariri Focus Research Award!

May 15, 2024

Our collaborative project with Dr. Clare Poynton to develop a Vision Language model to audit risk models for breast cancer has received Hariri Focused Research awards!

Early accept of Mammo-CLIP in MICCAI!

May 13, 2024

Vision Language Foundational model for joint embedding of mammogram image and radiology reports is early accepted to MICCAI, congrats to Shantanu!

Self-Supervised Learning paper is in MedIA!

Dec 05, 2023

Congrats to Ke and Li for their recent paper in MedIA! This is a way to go for Self-Supervised Learning in medical imaging .

Our fast diffusion paper is accepted in NeurIPs!

Sep 27, 2023

Congrats to Yanwu for his second NeurIPs paper!   We are going to have more development in this direction soon!

Selected Publications

Probabilistic Modeling of Imaging, Genetics and the Diagnosis

K.N. Batmanghelich, A. Dalca, G. Quon, M. Sabuncu, P. Golland
IEEE Trans Med Imaging

Explanation by Progressive Exaggeration

S. Singla, B. Pollack, J. Chen, K. Batmanghelich

Eighth International Conference on Learning Representations (ICLR)

 

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

S. Singla, M. Gong, S. Ravanbakhsh, F. Sciurba, B. Poczos, K.  Batmanghelich
Medical Image Computing & Computer-Assisted Intervention (MICCAI)

Twin Auxiliary Classifiers GAN

M.*, Y. Xu*, Ch. Li, Kun Zhang, K. Batmanghelich (*: equal contribution)
NeurIPS 2019 [Spotlight 2.4%]

Lab Members

Li Sun

PhD Student (Pitt-ISP)
Research Assistant

Yanwu Xu

PhD Student (Pitt-ISP)
Research Assistant

Rick Chang

PhD Student (Pitt-Biostat)
Research Assistant

Shantanu Ghosh

PhD Student (Pitt-ISP)
Research Assistant

Nihal Murali

PhD Student (Pitt-ISP)
Research Assistant

Matthew Ragoza

PhD Student (Pitt-ISP)
Research Assistant

Maxwell Reynolds

PhD Student (Pitt-DBMI)
Research Assistant

Alumni

Jiaming Bai

Lisa Hou

Fan Qian

Keyi Yu