● Worked on a high-throughput training system that optimizes efficiency and resource utilization of Reinforcement Learning algorithms by up to 20% across games and simulations than the state-of-the-art systems (accepted at ICML 2020).

● Research was based on applying on-policy Reinforcement Learning algorithms to control a swarm of Quadrotors.

● Built a faster alternative to Python multiprocessing queue and also worked on CI pipelines for ML Research Projects.

● Worked in tandem with the Autonomous Vehicle Lab at USC on Navigation and Path Planning for an autonomous car to participate in IGVC 2020.

● Worked on designing and developing a platform that makes it easy to get high-quality training data for Machine Learning models at scale.

● Researched on integrating Machine Learning to automate certain Q&A capabilities.

● Optimizing and writing SQL Queries to fetch data for various internal analytical purposes.

● Using Cognos And Salesforce to generate Business Intelligence reports enhancing Fundraising and Donor campaigns.

● Worked as a part of the Steel Security Research Lab on an application called DEW (Distributed Experiment Workflow) that aids information security researchers in running experiments on multiple testbeds via a Distributed setup.