Suhas Subramanya is a Senior Researcher at Microsoft with 11 years of experience building systems that make machine learning faster and more resource-efficient. His work spans production-scale research projects—like DiskANN and BLAS-on-Flash—that use flash storage to scale billion-point nearest-neighbor search and terabyte-scale ML workloads with dramatic reductions in RAM usage. A CMU PhD candidate with prior internships at Google and multiple research roles at Microsoft, he blends systems engineering, algorithm design, and applied ML to deliver measurable resource and performance gains. He has hands-on experience implementing out-of-memory algorithms and CUDA-accelerated solutions, and his contributions have targeted web-scale search infrastructure used across Bing. Known for turning research prototypes into production-relevant systems, he often focuses on pragmatic trade-offs that enable large-scale ML without exotic hardware. Based in Seattle, he maintains an active technical presence (suhasjs.github.io) that showcases both papers and system artifacts.
11 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology Madras
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
Contributions:65 commits, 56 pushes, 5 branches in 28 days
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