About me
I am a Ph.D. student in the Department of Computational Mathematics, Science and Engineering at Michigan State University. I am a member of the Signals, Learning, and Imaging (SLIM) group, advised by Prof. Saiprasad Ravishankar.
My research interests lie in computational imaging, inverse problems, and medical imaging, with a focus on MRI acquisition and reconstruction, scan-adaptive sampling methods, and learning-based reconstruction algorithms. I am particularly interested in combining signal processing, optimization, and machine learning for accelerated and robust imaging.
I received my M.S. in Electrical Engineering from the Indian Institute of Technology Madras in 2020, where I worked on computational electromagnetics and microwave remote sensing under the supervision of Dr. Uday K. Khankhoje.
News
Feb 2026: Our works Learning Patient-Adaptive Undersampling Patterns for Cardiac MRI Using Nearest Neighbor Search and Scan-Adaptive Deep Learning-Based Sampling with Pre-Optimized Mask Supervision have been accepted for poster presentation at the 2026 ISMRM Annual Meeting, Cape Town, South Africa.
Jan 2026: Our work Scan-Adaptive MRI Undersampling Using Neighbor-Based Optimization (SUNO) has been accepted to IEEE Transactions on Computational Imaging (link).
Dec 2025: Awarded the CMSE Ginther Research Fellowship, Michigan State University.
Sep 2025: Our work Learning Scan-Adaptive MRI Undersampling Patterns with Pre-Optimized Mask Supervision has been submitted to IEEE ICASSP 2026 (arXiv).
Sep 2025: Our work UGoDIT: Unsupervised Group Deep Image Prior via Transferable Weights has been accepted to NeurIPS 2025 (link).
May 2025: Our work Learning Robust Features for Scatter Removal and Reconstruction in Dynamic X-Ray Tomography has been published in Optics Express (link).
Apr 2025: Received the Outstanding Graduate Student Award, College of Engineering, Michigan State University.
Aug 2024: Awarded the CMSE Ginther Outstanding Research Award, Michigan State University.
Apr 2024: Our work Patient-Adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering has been accepted to IEEE ICASSP 2024 (link).
Nov 2023: Our work Patient-Adaptive MRI Undersampling Using Neighborhood Clustering has been accepted to the Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop, NeurIPS 2023 (link).
Oct 2023: Our work Residual Encoding Using Neural Field for Image Sequence Modeling has been accepted to the Asilomar Conference on Signals, Systems, and Computers (link).
Aug 2023: Our work Scatter Removal in Dynamic X-Ray Tomography Using Learned Robust Features has been accepted to the Computational Optical Sensing and Imaging meeting (Optica) (link).