I am an MS student at the Robotics Institute of Carnegie Mellon University, advised by Professor Shubham Tulsiani. I have a natural affinity towards Computer Vision, Machine Learning and great confidence in their ability to uplift human society. Recently, I am working towards developing generic autoregressive 3D shape priors and exploring their utility for shape completion and reconstruction tasks.
Before CMU, I worked as a Sr. Machine Learning Engineer with the Advanced Technology Labs in Samsung Research, India. I worked closely with Dr. Shankar Venkatesan towards developing AI systems that can remove obstructions from real-world images. For my undergraduate thesis, I was fortunate to be advised by Professor Arijit Sur on the problem of Image Memorability Prediction.
Download my resumé.
M.S. Computer Vision, 2022
Carnegie Mellon University
B.Tech. Computer Science & Technology, 2018
Indian Institute of Technology, Guwahati
Capstone project on exploring autoregressive shape priors for 3D objects and developing a unified framework for shape completion, single-view reconstruction and language guided generation
A graph convolution based approach to select multiple relevant sources (text or images) of information for multi-hop question answering.
Project on inverting models of 3D object recognition and classification in order to analyze interpretability
Course Assignment on Eight-Point Algorithm, finding epipolar correspondence and bundle adjustment for 3D reconstruction from noisy stereo correspondence
Course assignment to compute homography matrix, develop AR application and create panaromas using multiple images
Course assignment to use conventional filter responses (Gaussian, Laplacian of Gaussian etc.) to represent images and develop spatial pyramid based approach to classify scenes.
Flask based WebApp to recommend and view videos. Uses MySQL, MongoDB and Neo4j for tracking, storing and recommending videos
Implemented distributed merge-sort and android based client server application using the ForkJoin principle