About Me
Hi! I’m a Masters student in Electrical and Computer Engineering at Georgia Tech. I’m interested in working in Reinforcement Learning and its applications in games and beyond. I also have a good programming and math background which enables me to implement and test my ideas. I love breaking my head over Ted-Ed puzzles and occasionally solving jigsaw puzzles, I like to run, read and hula hoop :)
Projects
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TECLAT: Adapting CURL to predict a transition score as an auxiliary task to improve sample effiency.
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Compare RL algorithms such as Deep Q-Learning, Double DQN, Dueling DQN and Advantage Actor Critic on Atari environment.
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Object tracking using Particle filter for gamification
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Image denoising using partial differential equations
Research
Using auxiliary tasks,such as object detection to initialize agents to play Starcraft 2 to improve sample efficiency with Prof. Zsolt Kira from College of Interative Computing in the Robotics Perception and Learning lab.
Publications
Stepwise and Quadratic Discriminant Analysis of P300 signals for Controlling a Robot
Work and Skills
- Software Engineer at Microsoft.
- Software Engineering Intern at Microsoft: implemented enhanced process logging for Azure to help in better understanding node health
- Graduate Teaching Assistant for Computer Networks (CS6250) at Georgia Tech in Summer 2021.
- Graduate Teaching Assistant for Computer Networks (CS3251) at Georgia Tech in Spring 2021, Fall 2021, Spring 2022 and Fall 2022. I implemented an autograder from scratch to hasten grading.
- Worked as a Network Engineer and created several automation workflows for SDN solution deployment in Data Center and Enterprise domains, from 2018 to 2020.
- Internship at Cisco Systems India, worked on designing and implementing a web portal for device management, in 2018.
- Summer internship at Adobe Systems India, in 2017: Worked on comparing different deep learning frameworks based on learning curves and ease of use.
- Summer internship at Adobe Systems India, in 2017: Worked on the initial stages of a Reinforcement Learning based ad-recommendation engine.