Hi,
I’m an Applied Researcher at Fujitsu Research India, where my work primarily revolves around computer vision. Specifically, I focus on integrating non-Euclidean learning approaches into computer vision problems. Prior to joining Fujitsu, I completed my Masters by Research (M.Tech-RA) in Computer Science from IIT-Hyderabad. I was fortunate to be advised by Vineeth N Balasubramanian. During my Masters, I was also a graduate visiting researcher at the University of Toronto and Vector Institute with Animesh Garg.
My research interests are diverse but converge around computer vision and deep learning. Specifically, my previous works have been focused on data-efficient learning techniques such as active learning, transfer learning, and multi-modal learning. I have also explored topics such as adversarial robustness and Neural Architecture Search. Beyond solving research problems, I am also keen on applying machine learning to address real-world, industry-specific challenges.
While I have enjoyed a variety of teaching roles in the past, my current focus is on applied research. I used to serve as a Small Group coach at upGrad, was a student mentor for Udacity’s Nanodegree programs in AI, ML, and Deep Learning, and also worked as a Teaching Assistant at IIT-Hyderabad, where I was involved in creating assignments, content, and evaluation for various deep learning and machine learning courses.