Varun A. Kelkar

Department of Electrical and Computer Engineering (ECE)
University of Illinois at Urbana-Champaign

I am a PhD candidate with the Computational Imaging Science Lab, advised by Prof. Mark A. Anastasio.

My work is about developing ML-based algorithms for solving ill-posed imaging inverse problems, with applications to medical imaging. I have also worked on compressive microscopy, phase retrieval, physics of optical tomography, statistical optics and objective assessment of image quality.

I completed my undergrad (B.Tech.) in Engineering Physics from Indian Institute of Technology Madras in July 2017, and my MS in ECE from UIUC in August 2019.

I have done research internships at Mitsubishi Electric Research Labs (summer 2022), Algorithmic Systems Group at Analog Garage, Analog Devices Inc. (summer 2019), and LIGO 40m Lab, Caltech (summer 2016). I worked on various signal processing and imaging problems throughout these internships.


Apr 5, 2023 I gave a talk about our work on evaluating generative models in the 6th Health Data Analytics Workshop hosted at University of Illinois! Recording available here.
Jul 14, 2022 I was invited to give a talk on our work on assessing GANs at the AAPM Annual Meeting tutorial session on Assessment of Deep-Learning Technologies in Medical Imaging! Link to the talk here.
Jun 5, 2022 I was invited to give a talk and lead a session at the Gordon Research Seminar on Imaging Science for early career researchers.
Feb 1, 2022 Our paper on quantifying hallucinations in image reconstruction was covered by several leading newsletters including IEEE Spectrum and within a Forbes article on AI bias. Read the paper here.
Mar 22, 2021 I was awarded the Oak Ridge Institute and FDA fellowship to evaluate GANs for medical imaging applications. Read more here.

selected publications

    Varun A Kelkar, Dimitrios S Gotsis, Frank J Brooks, Prabhat KC, Kyle J Myers, Rongping Zeng, and Mark A Anastasio
    IEEE transactions on medical imaging 2023
  2. ICML
    Varun A. Kelkar, and Mark A. Anastasio
    In Proceedings of the 38th International Conference on Machine Learning (ICML) 2021
    Sayantan Bhadra*, Varun A. Kelkar*, Frank J. Brooks, and Mark A. Anastasio
    IEEE Transactions on Medical Imaging 2021
    Xiaohui Zhang*, Varun A Kelkar*, Jason Granstedt, Hua Li, and Mark A Anastasio
    Journal of Medical Imaging 2021
    Varun A Kelkar, Sayantan Bhadra, and Mark A Anastasio
    IEEE Transactions on Computational Imaging 2021
  6. Nat. Photon.
    Chenfei Hu*, Jeffrey J Field*, Varun Kelkar, Benny Chiang, Keith Wernsing, Kimani C Toussaint, Randy A Bartels, and Gabriel Popescu
    Nature Photonics 2020