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I am a CS PhD student at University of Wisconsin Madison working with Professor Josiah Hanna. Prior to this, I was a Master's student with Professor Zsolt Kira working on using Reinforcement Learning (RL) for long-horizon home-rearrangement in Habitat2.0. I received my Bachelor's degree in Electrical Engineering with a minor in Computer Science from IITGN .
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Broadly, I'm interested in Reinforcement Learning (RL) and it's application in the field of Robotics. My goal is to explore the limits of generalization in long-horizon RL across tasks and applied to distinct environments. To this end, I have explored hierarchical RL using Skill-Chaining for my Master's thesis. With a background in 3D Computer Vision, I'm interested in leveraging this to bridging the Sim2Real gap, enabling seamless interaction in the real world. |
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Given a set of pre-trained skills performing specific aspects of rearrangement , i.e Navigating, Picking up or Placing objects, we developed a hierarchical fine-tuning scheme that can fine-tune these policies simultaneously. Our method addresses the hand-off challenge in rearrangement where subsequent skills are not aligned (i.e the navigation skill-terminates too far from the couch). Our method demonstrates superior performance (about 13% in rearrangement success) over a static policy. |
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We propose an assembly framework that can assemble a shape in a canonical order by progressively gathering information. Compared to prior frameworks, our method achieves upto 10% improvement in part accuracy and 15% improvement in connectivity accuracy. |
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In this paper, we propose a deep learning based approach to localize forgery in a JPEG image. We develop a multi-coloumn CNN architecture that utilizes spatial and frequency domain information and classify each 8x8 JPEG block as single or double compressed. |
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We detect double compression at the patch level (64 x 64) or (128 x 128) by introducing an additional feature based on difference of DCT coefficients. Our classification network achieves upto 1.52% improvement in detection accuracy. |
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We utilize language tokens to understand distinctions between shapes. Given a text-label we find the closest match to the target shape. |
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We study the problem of Inverse Reinforcement Learning on the LinUCB algorithm and obtaining an optimal regret gurantee. |
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We develop a python implementation of the Eulerian Motion Magnification algorithm for revealing subtle changes in the world. |
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We simulate the motion of UAV's as they are launched from a football field and move randomly on a sphere colliding with each other. |
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A tool for interactively interpolating between points using 4 different spline types. |
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Website inspired by Jon Barron |