Mitra, Debasis
Debasis Mitra
Professor | College of Engineering and Science: Department of Electrical Engineering and Computer Science
Contact Information
Expertise
Personal Overview
Debasis Mitra is a Professor in the Department of Computer Science at Florida Institute of Technology. He received a Ph.D. in Computer Science from the Center for Advanced Computer Studies of the University of Louisiana at Lafayette. Mitra's first Ph.D. was in Physics from the Indian Institute of Technology at Kharagpur. He was an Assistant and Associate Professor in Computer Science at Jackson State University before joining Florida Institute of Technology. In the past Mitra has worked on reasoning with spatial and temporal knowledge. He is a recipient of the National Science Foundation Career Award and the Fulbright Scholarship.
Current research focus in Mitra's Lab is in Bio-medicine and Inverse Problems. The group is engaged in improving analysis of Nuclear Medical images. A long term vision in the lab is to understand the molecular biology of different diseases for improving human health. The group works on applications of Machine learning over Image understanding problems, from medical domains to archeology.
Students about to complete their Bachelor's/Master's/Ph.D. with strong mathematical background and interest in research are welcome to contact Mitra.
Educational Background
B.Sc.-Physics, Kolkata University, India
M.S.-Physics, Indian Institute of Technology at Kharagpur, India
Ph.D.-Mathematical physics, Indian Institute of Technology at Kharagpur, India
Ph.D.-Comp. Sc., University of Louisiana at Lafayette
Professional Experience
Professorial ranks: Jackson State University, MS., and Florida Inst. of Tech., FL
Visiting researcher: Stanford University, CA; Lawrence Berkeley National Lab, CA; University of Paris, France; Vienna Inst. of Tech., Austria; Linkopings University, Sweden; Indian Inst. Tech. Mumbai, India; Tata Inst. of Fundamental Research Mumbai, India; and Asian Inst. of Tech. Bangkok, Thailand, and Indian Statistical Institute, Kolkata, India.
Current Courses
Artificial Intelligence, Scientific Computing
Selected Publications
Chang, H., Kobzarenko, V., Mitra, D. (2024) “Inverse Radon Transform with Deep Learning: an application in cardiac motion correction.” Physics of Medicine and Biology 69(3). doi: 10.1088/1361-6560/ad0eb5. PMID: 37988757.
He et al. (2023) "Heavy-chain CDR3-engineered B cells facilitate in vivo evaluation of HIV-1 vaccine candidates." Cell Immunity. 2023 Oct 10;56(10):2408-2424.e6. doi: 10.1016/j.immuni.2023.07.003. Epub 2023 Aug 1. PMID: 37531955.
Liu et al. (2022) "Incorporating Radiomics into Machine learning models to predict outcomes of neuroblastoma". Jnl of Digital Imaging.35(3):605-612.
Sawant et al. (2022) “JetCurry I. Reconstructing three-dimensional jet geometry from two-dimensional images.” Astronomy and Computing, 41(10063).
“Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis.” Huang S-y, Franc BL, Harnish R, Liu G, Mitra D, Copeland TP, Arasu VA, Kornak J, Jones EF, Behr S, Hylton NM, Price ER, Esserman L, Seo Y. Nature Partners Journal Breast Cancer, Article number: 24, 2018. https://www.nature.com/articles/s41523-018-0078-2
Pan H, Chang H, Mitra D, Gullberg GT, and Seo Y. “Sparse domain approaches in dynamic SPECT imaging with high-performance computing.” American Journal of Nuclear Medicine and Molecular Imaging, 7(6):283-294, 2017.
“Clustering Initiated Factor Analysis (CIFA) Application for Tissue Classification in Dynamic Brain PET.” Boutchko R, Mitra D, Baker S, Jagust W, and Gullberg GT. Journal of Cerebral Blood Flow & Metabolism – Nature, doi:10.1038/jcbfm.2015.69, April 2015.
“Reconstruction of 4-D Dynamic SPECT Images From Inconsistent Projections Using a Spline Initialized FADS Algorithm (SIFADS).” Abdalah M, Boutchko, R, Mitra D, and Gullberg GT. IEEE Transactions in Medical Imaging, 34(1): 216-228, 2015.
Recognition & Awards
Academic Excellence award, the Legislature of the State of Mississippi
Career Award, National Science Foundation
Research Fellow, Fulbright foundation
Research
Medical Imaging: processing nuclear medical images for improving diagnosis and prognosis.
Inverse problem: sparse optimization, tomographic reconstruction for emission, transmission, and scattering tomography.
Machine learning: deep learning on medical images, topological data analysis.
Writing non-fictions