Jubi Taneja is a research engineer with 11 years of experience building trustworthy, high-performance compilers and AI-driven developer tooling, currently focused on AI compilers and verified kernel generation at Microsoft Research and Gimlet Labs. With a PhD from the University of Utah and a history of work spanning kernel development, static analysis, and superoptimization, Jubi blends formal methods, solver-based techniques, and LLMs to push compiler automation forward. Notable contributions include a PTX-level equivalence checker, the LLM-Vectorizer framework for verified loop vectorization, and practical enhancements to the well-known google/souper superoptimizer to support LLVM intrinsics. He mentors PhD students and engineers through SIGPLAN’s long-term program, reflecting a strong commitment to community and knowledge transfer. Based in San Francisco, he brings a rare combination of deep verification expertise and hands-on systems engineering aimed at making compiler optimizations both provably correct and compute-efficient.
11 years of coding experience
14 years of employment as a software developer
The University of Utah
B.Tech Computer Science, B.Tech Computer Science at Punjabi University
Contributions:33 commits, 44 PRs, 111 comments in 5 years 5 months
Contributions summary:Jubi contributed to the `google/souper` repository by adding support for intrinsics like `cttz`, `ctlz`, `ctpop`, and `bswap`. They modified the `KLEEBuilder.cpp` to implement these intrinsic functions and also made changes to the `Inst` and `Parser` files. These changes suggest they are developing functionalities for the superoptimizer to support new LLVM IR intrinsic functions.
Automatic peephole optimizer for Cranelift JIT compiler
Contributions:194 commits, 115 pushes, 1 branch in 2 years 9 months
jitcraneliftcompilerjit-compileroptimizer
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