Tushaar Gangavarapu is an MS CS student at Cornell (advised by Alexander Rush) and a research-focused engineer with nine years of industry and academic experience spanning applied NLP, ML systems, and mechanistic interpretability. He has built scalable long-context hybrid language models and hardware-aware Triton kernels during internships at IBM and Microsoft, and shipped production ML features at Amazon improving Kindle content quality and reader experience. His research explores alternate-attention and recurrent architectures (e.g., Mamba/Byte, RecurrentGemma) and uses sparse autoencoders to probe the role of recurrence in linear models, marrying theory with systems-level efficiency. Based in Austin and transitioning to a PhD at UT Austin, he combines hands-on kernel implementation skills with teaching and course co-instruction, suggesting a knack for translating deep research into practical, deployable systems.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy Computer Science, Doctor of Philosophy Computer Science at The University of Texas at Austin
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Cornell University
Bachelor of Technology Information Technology (specialization: Artificial Intelligence), Bachelor of Technology Information Technology (specialization: Artificial Intelligence) at National Institute of Technology Karnataka
Contributions:824 pushes, 1 branch in 5 years 1 month
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