Yash Sirvi

I am Yash Sirvi, a final-year undergraduate in the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur. I worked with Prof. Partha Pratim Chakrabarti on scalable learning-based solutions for NP-complete problems, focusing on the Travelling Salesman Problem. Under the guidance of Prof. Debashish Chakravarty, I developed game-theoretic planners for autonomous racing systems. I am also doing my Bachelor's Thesis under the supervision of Prof. Aritra Hazra to improve MARL techniques, addressing scalability and stability in multi-agent settings.

I have also interned at Quadeye Securities LLP as a Systems Engineer. There, I worked on optimizing the compiler pipeline for efficient regression test selection, designing algorithms to detect test and compilation failures early.

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Research

I'm interested in Algorithmic Optimization, Multi-Agent Reinforcement Learning (MARL), Planning, and Robotics, with an emphasis on scalability, efficiency, and real-world applications. I aim to develop innovative algorithms to tackle challenges in autonomous systems and multi-agent learning.