Indrani Bhattacharya, PhD
Assistant Professor, Department of Biomedical Data Science, Center for Precision Health and Artificial Intelligence (CPHAI)
Dr. Indrani Bhattacharya is an Assistant Professor in the Department of Biomedical Data Science and the Center for Precision Health and Artificial Intelligence (CPHAI). Dr. Bhattacharya’s research interests are in developing human-centered, translational, machine learning systems for healthcare applications. She is specifically interested in investigating how to seamlessly integrate and learn from complementary multimodal imaging and non-imaging data for developing these systems. The two focus areas of her research include: (a) medical imaging-based computational systems to assist clinicians in early disease detection, characterization and treatment planning, and (b) multimodal behavior estimation systems to assess and improve behavioral health, patient wellbeing, and doctor-patient interactions.
Dr. Bhattacharya completed her bachelor’s in electrical engineering from Jadavpur University, India, and her MS and PhD from the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, NY. Thereafter, she joined the Department of Radiology (Division of Integrative Biomedical Imaging Informatics) at Stanford University School of Medicine, CA, as a postdoctoral scholar and continued on as an academic research staff up until she joined Dartmouth. Dr. Bhattacharya’s research has always been highly interdisciplinary, at the intersection of computer vision and machine learning, medicine, and social science research. Outside of work, Dr. Bhattacharya enjoys traveling, painting, participating in cultural events, watching movies and TV shows, cooking, and spending time with friends.
Selected Publications
- Vesal S, Gayo I, Bhattacharya I, Natarajan S, Marks LS, Barratt DC, Fan RE, Hu Y, Sonn GA, Rusu M. Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study. Med Image Anal. 2022 Nov;82:102620. doi: 10.1016/j.media.2022.102620. PMID: 36148705; PMCID: PMC10161676.
- Bhattacharya I, Khandwala YS, Vesal S, Shao W, Yang Q, Khandelwala Y, Soerensen SJC, Fan RE, Ghanouni P, Kunder CA, Brooks JD, Hu Y, Rusu M, Sonn GA. A review of artificial intelligence in prostate cancer detection on imaging. Therapeutic Advances in Urology. 2022;14. doi:10.1177/17562872221128791
- Stacke K, Bhattacharya I, Tse JR, Brooks JD, Sonn GA, Rusu M. Correlated feature aggregation by region helps distinguish aggressive from indolent clear-cell renal cell carcinoma on computed tomography. Medical Physics. 29 Sept 2022.
- Bhattacharya I, Lim DS, Aung HL, Liu X, Seetharaman A, Kunder CA, Shao W, Soerensen SJC, Fan RE, Ghanouni P, To'o KJ, Brooks JD, Sonn GA, Rusu M. Bridging the gap between prostate radiology and pathology through machine learning. Med Phys. 2022 Aug;49(8):5160-5181. doi: 10.1002/mp.15777. PMID: 35633505; PMCID: PMC9543295.
- Bhattacharya I, Seetharaman A, Kunder C, Shao W, Chen LC, Soerensen SJC, Wang JB, Teslovich NC, Fan RE, Ghanouni P, Brooks JD, Sonn GA, Rusu M. Selective identification and localization of indolent and aggressive prostate cancers via CorrSigNIA: An MRI-pathology correlation and deep learning framework. Med Image Anal. 2022 Jan;75:102288. doi: 10.1016/j.media.2021.102288. PMID: 34784540; PMCID: PMC8678366.
- Zhang L, Bhattacharya I, Morgan M, Foley M, Riedl C, Foucault Welles B. Multiparty visual co-occurrences for estimating personality traits in group meetings. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), Snowmass, CO, USA, 2020, pp. 2074-2083.
- Zhang L, Morgan M, Bhattacharya I, Foley M, Braasch J, Riedl C, Welles BF, Radke RJ. Improved visual focus of attention estimation and prosodic features for analyzing group interactions. Proceedings of the ACM International Conference on Multimodal Interaction (ICMI), Suzhou, China, Oct. 2019.
- Bhattacharya I, Foley M, Zhang N, T. Zhang T, Ku C, Mine C, Li M, Ji H, Riedl C, Welles BF, Radke RJ. The Unobtrusive Group Interaction (UGI) corpus. Proceedings of the ACM International Conference on Multimedia Systems (MMSys), Amherst, MA, Jun. 2019.
- Bhattacharya I, Foley M, Zhang N, Zhang T, Ku C, Mine C, Ji H, Riedl C, Welles BF, Radke RF. A multimodal-sensor-enabled smart room for unobtrusive group meeting analysis. Proceedings of the ACM International Conference on Multimodal Interaction (ICMI), Boulder, CO, Oct. 2018.
- Bhattacharya I, Radke RJ. Arrays of single pixel time-of-flight sensors for privacy-preserving tracking and coarse pose estimation. Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, Mar. 2016.