Debottama Das

Research Interests

My research focus is on quantitative analysis of human subcortical brain structures, with a particular emphasis on the thalamus and its subnuclei.I primarily work with diffusion MRI to characterize microstructural organization and to develop data driven segmentation frameworks.In addition, I use population based modelling approaches on diffusion derived microstructural measures and thalamo cortical connectivity to characterize variability and structural differences across individuals.

Background

I am originally from India and completed my Bachelor’s degree in Electronics and Communication Engineering at SRM Institute of Science and Technology, Chennai. In 2021, I moved to the United States to pursue a Master’s degree in Electrical and Computer Engineering (ECE) at the University of Arizona(UofA), where my academic training focused on machine learning and medical image analysis. Building on this foundation, I continued at the UofA to begin my Ph.D. in ECE, with my research centered on diffusion MRI based analysis of human subcortical region.

Publications

Journal Publications

1. Nguyen, D. H., Kumar, V., Das, D., Bilgin, A., Patterson, D., Cacciola, A., & Saranathan, M. (2025). Revisiting the Role of Structural Connectivity-Based Parcellation in Thalamic Nuclei Segmentation: comparison with recent state-of-the-art methods. medRxiv, 2025-09.
2. Das, D., Iyengar, M.S., Majdi, M.S. et al. Deep learning for thyroid nodule examination: a technical review. Artif Intell Rev 57, 47 (2024). https://doi.org/10.1007/s10462-023-10635-9

Conference Publications

1. Das, D., Iglehart, C., Bilgin, A., & Saranathan, M. Fast and Efficient Diffusion-based Thalamic Segmentation Using Spectral Clustering.

Personal

Outside of research, I enjoy learning about history, watching movies, and experimenting with cooking new cuisines in my free time.