Saikat Dutta

Saikat Dutta is an Assistant Professor in the Department of Computer Science at Cornell University, where he joined in August 2024. His research sits at the intersection of Software Engineering and Machine Learning, with a focus on improving the reliability of machine learning systems and leveraging machine learning techniques to solve challenging software engineering problems.

His research interests span several key areas including automated test generation and debugging of ML/DL libraries, using AI/ML for automated software engineering, improving performance and effectiveness of regression tests in ML libraries, and static and dynamic analyses for probabilistic programming. His work bridges theoretical foundations with practical applications in real-world systems.

Dutta has developed multiple influential frameworks and tools including BugsInDLLs (a database of reproducible bugs in deep learning libraries), FLEX (for fixing flaky tests in ML projects), and TERA (for optimizing stochastic regression tests). His research has been published in top-tier venues including ICSE, FSE, ISSTA, PLDI, and ICLR.

• Amazon Research Award 2025
• Meta AI LLM Evaluation Research Grant 2025
• Mavis Future Faculty Fellowship 2022-23
• Facebook PhD Fellowship 2020-22
• 3M Foundation Fellowship 2019-2020

Dutta actively mentors PhD students including Yingao (Elaine) Yao, Shinhae (Joseph) Kim, and Junkai Huang. He has served on program committees for major conferences including ASE, ISSTA, and ICSE. His teaching includes courses on Software Engineering in the Era of ML/AI.