Shubham Ugare is a research scientist in New York with a decade of experience at the intersection of programming languages and machine learning, currently working on AI for code generation at Meta. He holds a PhD in Computer Science from UIUC and has blended industrial impact with research through roles at Bloomberg, Microsoft, and multiple internships at Uber focused on leveraging LLMs and static analysis to automatically fix and prevent bugs. As an engineer he contributed core functionality and extensive tests to Uber’s widely used NullAway project, improving nullability analysis for Java and helping reduce NPEs at scale. His background spans designing DSLs for efficient ML compilation, invariant synthesis using AI, and static tools for Go, reflecting a rare mix of PL theory and practical tooling. Known for shipping robust analyses and tooling, he pairs rigorous academic training with hands-on system-building that bridges research prototypes and production developer workflows. He's also the maintainer of a public academic portfolio and code samples at shubhamugare.github.io, signaling an ongoing commitment to open research and reproducibility.
10 years of coding experience
3 years of employment as a software developer
Bachelor of Technology (BTech), Computer Science and Engineering (With minor in Mathematics), 9.42/10.0, Bachelor of Technology (BTech), Computer Science and Engineering (With minor in Mathematics), 9.42/10.0 at Indian Institute of Technology, Guwahati
A tool to help eliminate NullPointerExceptions (NPEs) in your Java code with low build-time overhead
Role in this project:
Back-end Developer & Test Automation Engineer
Contributions:15 reviews, 17 commits, 32 PRs in 2 years
Contributions summary:Shubham primarily contributed to the NullAway project by implementing features related to nullability analysis and enhancing the tool's ability to detect potential null pointer exceptions in Java code. They added support for assert statements, ensuring the correct propagation of nullness information and improved the handling of restrictive annotations for method overriding, leading to more accurate analysis results. The user also added and expanded upon the unit tests to cover various cases of nullable checks and edge cases, ensuring the tool's reliability and functionality.
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