Department of Electrical and Computer Engineering
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
Apr 24, 2023
Oct 11, 2022
Congrats to Sumedha and Nihal for their paper in WACV! They showed how our previous work on Counterfactual Explainer could be used to fix an overconfident BlackBox classifier!
Sep 07, 2022
Happy for Yingci! Her manuscript has been accepted to Oral Oncology!
Sep 02, 2022
Jun 02, 2022
Two papers are accepted in MICCAI 2022! Congrats to Ke Yu, Yanwu Xu, and Shantanu Ghosh!
Apr 26, 2022
Mar 02, 2022
Congratulations to Yanwu for his CVPR paper! His method uses the Maximal Spatial Perturbation idea that significantly enhances image-to-image translation!
K.N. Batmanghelich, A. Dalca, G. Quon, M. Sabuncu, P. Golland
IEEE Trans Med Imaging
S. Singla, B. Pollack, J. Chen, K. Batmanghelich
Eighth International Conference on Learning Representations (ICLR)
S. Singla, M. Gong, S. Ravanbakhsh, F. Sciurba, B. Poczos, K. Batmanghelich
Medical Image Computing & Computer-Assisted Intervention (MICCAI)
M.*, Y. Xu*, Ch. Li, Kun Zhang, K. Batmanghelich (*: equal contribution)
NeurIPS 2019 [Spotlight 2.4%]