Sidharth Kathpal is a Senior Engineer specializing in machine learning performance with eight years of experience bridging research and production engineering in automotive and storage domains. With a Master’s in Computational Data Science from Carnegie Mellon and roles at Qualcomm and CMU, he focuses on applied deep reinforcement learning for safe, real-world autonomous driving systems. He has a proven track record of improving system-level performance—previously delivering a 20% IOPS gain on Zoned Namespace NVMe drives—and translating research prototypes into scalable deployments. At Qualcomm he advances ML performance tooling and safe-learning approaches that accelerate autonomous vehicle capability. Based in San Diego, he combines hands-on engineering, academic research experience from the LearnToRace challenge, and cross-functional collaboration to drive measurable impact.
8 years of coding experience
6 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Thapar Institute of Engineering & Technology
Master's degree Computational Data Science, Master's degree Computational Data Science at Carnegie Mellon University
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