Research
I'm interested to explore and understand the most mesmerizing aspect of human intelligence: our ability to extract and abstract information so rapidly & flexibly by perceiving & interacting with our environment. My burning question is: How do we infer so much from so little? In pursuit of this question, I am exploring and learning about ideas in deep learning, programming languages and logic.
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News
Mar '21 |
Accepted UT Austin MSCS offer! Will join Fall 2021. |
Mar '21 |
Our paper on training NN using DE has been accepted at IEEE CEC 2021 for Oral presentation! |
Mar '21 |
Our paper on comparitive study of training NN has been accepted at IEEE CEC 2021 for Oral presentation! |
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Projects
Internships and other professional experience.
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Exploring Feature Extraction of Atari 2600 Games with Deep Reinforcement Learning
Mentor: Prof. Achal Agarwal
Mahindra Ecole Centrale, 2020
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Exploring feature extraction in Reinforcement Learning problems, specifically tackling Atari 2600 game environment. Working with unsupervised image segmentation DL models, computer vision techniques and popular RL algorithms such as DQN, A2C and PPO. Conducting a study on interpretability and transferability of RL algorithms.
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Topic2Document
Mentor: Prof. Srinath Srinivasa
Web Science Lab, International Institute of Information Technology - Bangalore, 2019
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Convert a given input bag of words vector into a natural language virtual document. This library was developed for the Narrative Arc project.
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Sentence Prediction using Topic Modeling
Mentor: Anumpam Mediratta
ShowUpHotels, 2018
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A Python library to train topic models for sentence prediction using gensim and MALLET. It was developed as a summer internship project under the guidance of Anupam Mediratta.
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Other Projects
These include side projects and hackathon stuff.
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Predict future jobs using historic job data and news data
Hackathon
Winner, Smart India Hackathon, 2020
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Our solution basically uses historical job data for information about the location, salary and requirements and News articles that provide information about the future (ie. predictions).
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Distributed Compute Fabric using Mobile Devices
Hackathon
3rd Place, Start-up Sprint, E-Summit @ MEC, 2020
Platform to make computation on smartphones accessible and profitable. Designed and implemented efficient data and compute traffic distribution algorithms.
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AI/ML for Cart Conversion
Hackathon
Winner, Dell EMC Hack-to-Hire, 2019
Multifaceted solution to solve the cart conversion problem faced by e-commerce companies. Contribution included developing a recommender system using Bayesian Networks and ensemble learning (Classification and Regression methods).
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DinoEnv Gym Environment
Project
College Dorm, 2019
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OpenAI Gym environment based on the Google Chrome Dino game.
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oWatcher
Project
College Dorm, 2017
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Discord bot to display detailed in-game performance statistics of a players in Overwatch by Blizzard Entertainment.
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