Summary
Kshitij Srivastava is a research-focused software engineer with nearly nine years of experience spanning industry and academia, currently driving AI research as a Research Assistant at UMass Lowell's Exalabs. He builds deep learning reward models for hierarchical reinforcement learning and is developing a personalized AR running-app recommender that leverages computer vision and real-time feedback, using ensemble methods and VAEs for state-space aggregation. In prior roles at Publicis Re:Sources and Capgemini, he automated data migrations, led real-time deployments, and delivered visualization components, honing Python, JavaScript, Apex, and cloud skills. He blends rigorous academic training with practical engineering to deliver scalable AI solutions across ML, DL, NLP, robotics, and swarm intelligence. He has a B.Tech from SRM University and is pursuing an MS in Computer Science at UMass Lowell, reflecting a strong commitment to continuous learning. Based in the United States, he brings a curious, results-driven approach to turning complex research into production-ready software.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Technology, Computer Science and Engineering, Bachelor of Technology, Computer Science and Engineering at SRM University
UMass Lowell
High School, Political Science and Government, High School, Political Science and Government at Genesis Global School
Hindi, English