I'm a second-year CS PhD student at the University of Texas at Dallas (UTD), advised by Dr. Yunhui Guo. Before this, I obtained my MS in Electrical Engineering from the University of Southern California (USC) and a Bachelor's degree from IIIT Bhubaneswar (IIIT-Bh), India, with an honors degree in Electrical and Electronics Engineering.
My research focuses on enhancing model robustness, adaptability, and generalization to rapid distributional shifts during deployment, with an emphasis on continual learning. Additionally, I am engaged in projects on active learning for 3D object detection/segmentation and machine unlearning in generative models.
Adaptive learning rate continual test-time adaptation method based on model prediction uncertainty and parameter sensitivity to rapid distributional shifts.
Developed an end-to-end general software tool to automate the reconstruction of fiber bundles in the brainstem of the human brain, using diffusion
MRI images, for the HCP Aging dataset (to be publicly released soon).
Leveraged deep learning based registration and label fusion methods to automatically generate the anatomical ROIs that are critical for fiber
bundle reconstruction.
University of Southern California Student Researcher Los Angeles, CA
Dec 2021 - Dec 2022
Performed speaker recognition from rt-MRI videos, based on an unsupervised disentanglement representation learning scheme.
Contributed to the development of generating embeddings from 2D sagittal-view rt-MRI videos to distinguish between speakers based on their
articulatory representations from vocal tract landmarks.
National University of Singapore Part-time Research Assistant Remote
July 2020 - Apr 2021
Experimented with different encoder-decoder architectures (ex. LinkNet) by plugging in spatio-temporal modules (ex. convLSTM) to perform
pixel-wise prediction of the needle trajectory in ultrasound images during a kidney biopsy.
Proposed the integration of a DGMN (Dynamic Graph Message Passing) network in DGCN (Dual Graph Convolutional Network), for efficient
semantic segmentation, to model long-range dependencies in an OCT image.
Indian Institute of Science Bachelor's Thesis and Student Researcher Bangalore, India
Dec 2019 - Sep 2020
Studied acoustic-to-articulatory inversion (AAI) modelβs performance on the dysarthric speech when the model was trained in a corpus dependent
manner using a matched low-resource dysarthric corpus or using a mismatched cross-corpus with rich acoustic-articulatory data.
Investigated the benefit of utilizing cross-corpus acoustic-articulatory data using transfer learning and joint-training techniques for the articulatory
predictions of dysarthric subjects.
Indian Institute of Technology Kharagpur Summer Research Intern Kharagpur, India
May 2019 - Jul 2019
Developed an in-house template matching algorithm, of various phases, to detect breaths in speech recordings using end-to-end deep neural
networks.
Employed a heuristic technique to join close predicted breath segments, and segments below a certain threshold were removed, for postprocessing
and to remove any misclassification errors.
Building CORD.ai, a deep learning research community, as a core member and volunteer researcher.
I'm a cis male.
I consider myself lucky to have grown up in two beautiful cities in India - Bangalore and Bhubaneswar, that have infused in me a lot of character and development. I've also spent two quality years in the vibrant, diverse, gently warm, and sprawling city of Los Angeles, California. Absolutely look forward to staying in new places and experiencing different cultures.
I'm a HUGE fan of the classical formats of cricket. You'd often find me watching old test match highlights or SRT straight drives. Nothing can get more sublime than that. I bet! I don't consider IPL/T20 cricket as a thing AT ALL.
I think mobile photography is like a side gig for me? My phone instantly comes out the moment my eyes catch sight of a beautiful view.
I also spend a lot of time in quality humor - dark humor per se. We could talk about that later.