Registered user since Tue 26 Jan 2016
Jubi Taneja is a Member of Technical Staff at Gimlet Labs working at the intersection of AI, compiler optimizations, and formal verification. Her work focuses on building trustworthy, self-learning compiler systems by leveraging Large Language Models (LLMs) while ensuring correctness through rigorous formal methods. At Microsoft Research, she has led the development of tools like the LLM-Vectorizer and PTX-level kernel equivalence checkers to verify AI-generated and handwritten GPU optimizations. Jubi earned her Ph.D. from the University of Utah, where her work on testing LLVM’s static analyses for soundness and precision earned a Distinguished Paper Award at CGO 2020. She is also a member of Sigma Xi, The Scientific Research Honor Society. An active member of the programming languages community, she serves as a mentor for SIGPLAN-M, co-leads the Women in Compilers & Tools initiative, and has served on numerous program committees, including PLDI, CGO, LCTES and TACO.
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