Nilesh Gupta is a PhD student and graduate research assistant at UT Austin specializing in large-scale machine learning, web search, and extreme classification, with a decade of engineering and research experience. He has applied those skills across industry research stints at Google, Google DeepMind, and Microsoft, working on LLM retrieval/ranking, large-vocabulary LLMs, and end-to-end search in massive output spaces. Prior roles span algorithmic trading infrastructure at Tower Research and program verification research in Europe, reflecting a blend of systems-level engineering and theoretical depth. Advised by Prof. Inderjit Dhillon, he focuses on scalable algorithms and dual-encoder approaches that bridge academic rigor and production relevance. His background from IIT Bombay and repeated collaborations with leading researchers suggest a track record of shipping research that targets real-world search and recommendation bottlenecks. A less obvious strength is his cross-domain fluency—moving from C++ exchange recovery pipelines to cutting-edge ML research—enabling practical, high-performance solutions.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy, Computer Science, Doctor of Philosophy, Computer Science at The University of Texas at Austin
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