Bio
Dr. Aniket is a Postdoctoral Research Associate at the Electrification and Energy Infrastructures Division (EEID), ORNL. Overall, the goal of his research is to improve imaging systems (Magnetic Resonance Imaging, Computed Tomography etc.) that are useful for several applications. It involves solving inverse problems (reconstruction, denoising, super-resolution etc.) for enhanced imaging performance. His experience lies in physics-guided/model-based deep learning (combination of physics-based and deep-learning models) techniques. During his PhD, Aniket developed a robust, memory-efficient model-based deep learning algorithm for the image reconstruction task to significantly accelerate MRI scanning. His expertise spans across multiple areas including linear algebra, signal processing, optimization techniques, machine learning and scientific programming.
For more details, please visit my personal website.
Awards
Best Machine Learning Paper Award at the IEEE International Symposium on Biomedical Imaging (ISBI) 2019.
Summa Cum Laude Merit Award at the International Society of Magnetic Resonance in Medicine (ISMRM) Exhibition 2021
National Institute of Health (NIH) Travel Grant for IEEE ISBI 2019
NIH Travel Grant for IEEE ISBI 2023
Education
2023: PhD, Electrical and Computer Engineering, University of Iowa, Iowa City, USA
2022: MS, Electrical and Computer Engineering, University of Iowa, Iowa City, USA
2015: B.Tech, Electronics and Communication Engineering, National Institute of Technology, Silchar, India
Professional Service
Reviewer
Journals:
IEEE Transactions on Computational Imaging
IEEE Transactions on Medical Imaging
Magnetic Resonance in Medicine
Conferences:
IEEE International Symposium on Biomedical Imaging
ECCV European Conference for Computer Vision