Aditya Kamath is a computer systems and architecture researcher and PhD candidate at the University of Washington with nine years of experience investigating data movement and its performance impact from single-node CPUs/GPUs to multi-machine distributed systems. He has bridged industry and academia through research internships at Meta, Microsoft, and AMD—work that includes in-GPU collective communication for Mixture-of-Experts LLMs and a novel attention kernel for mixed-prefill LLM inference (ASPL0S 2025). His work focuses on practical, high-performance solutions for collective communication and LLM inference kernels, evidenced by contributions to projects like ROC_SHMEM and collaborations with large-scale lab infrastructure. Based in Seattle, he combines systems-level insight with hands-on implementation across hardware-aware software stacks, often targeting bottlenecks that are overlooked in higher-level ML workflows.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Washington
Bachelor of Technology, Computer Science and Engineering, Bachelor of Technology, Computer Science and Engineering at National Institute of Technology Karnataka
Contributions:7 commits, 5 pushes, 1 branch in 1 year 9 months
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