Shubhashis Dipta is a PhD candidate and machine learning researcher specializing in making large language models reliably solve complex reasoning, tool-use, and multimodal tasks. His thesis—decomposing hard problems into atomic, verifiable subproblems—has driven practical advances at Amazon Alexa AI, Scale AI, and UMBC, producing published tools and metrics (e.g., PA3, VC-Inspector, GanitLLM, OMD-Bench) with measurable gains in efficiency and factuality. He combines rigorous research (ACL, AACL, SEM, CVPR workshops) with product-minded engineering experience from founding a cross-border e-commerce startup and building ML systems in industry. A mentor and reviewer for top venues, he also brings competitive programming and robotics pedigree that informs his problem-solving and system design. Authorized to work for any US employer, he is actively seeking Research Scientist roles in NLP and multimodal AI.
Contributions:71 commits, 2 PRs, 70 pushes in 4 years 4 months
pythoncppleetcodebit-manipulationproblems
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