Summary
Swaminathan Gurumurthy is a PhD student in Robotics at Carnegie Mellon University with a decade of experience developing reinforcement learning and robotic perception systems under advisors Zico Kolter and Zac Manchester. His work spans stable off-policy/on-policy RL methods, meta-learning for policy alignment, and practical robotic mapping—experience gained through internships at Mila, Nuro, IISc, and the Australian Centre for Robotic Vision. He blends rigorous academic research with hands-on system building, from self-imitation and coordinated exploration algorithms to bundle-adjusted sparse mapping for challenging underground environments. Based in Pittsburgh, he pairs strong theoretical foundations with applied problem-solving in safety-critical and sample-constrained settings, often focusing on stabilizing learning and modeling multimodal distributions when data is limited.
10 years of coding experience
Doctor of Philosophy - PhD Robotics, Doctor of Philosophy - PhD Robotics at Carnegie Mellon University
Electrical Engineering, Electrical Engineering at Indian Institute of Technology (Banaras Hindu University), Varanasi