Ayush Goel is a systems-focused research scientist with eight years of experience building and optimizing networking and distributed systems, currently driving Network.AI research at Meta. He holds a PhD from the University of Michigan and has moved research into practice across Hewlett Packard Labs and IBM Research, working on high-performance computing, heterogenous deep learning optimizations, and network-aware systems. Ayush blends deep systems thinking with hands-on engineering—publishing papers, filing patents, and leading knowledge transfers to product teams. His background includes low-level binary analysis, container and Android systems work, and contributions to GCC tooling during a Google Summer of Code stint, reflecting a strong foundation in compilers and tooling. Based in California, he excels at turning research ideas into deployable solutions that improve infrastructure performance at scale. A systems enthusiast by trade, he often operates at the intersection of networking, distributed runtime optimization, and practical product impact.
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