Alvin Cheung

Alvin Cheung is an Associate Professor in the Department of Computer Science at the University of California, Berkeley, where he is a member of the Data Systems and Foundations group and Programming Systems group. He also participates in the Sky Computing Lab and SpeciaLIzed Computing Ecosystems (SLICE) Lab, and serves as a faculty affiliate at the Berkeley Institute for Data Science. His research spans database systems, programming languages, and software engineering with applications across various domains.

Professor Cheung's research focuses on creating systems that bridge the gap between data management and programming languages. His work centers on three main themes: verified lifting techniques for inferring program properties; designing new data processing and programming language techniques; and improving end-user data programming experiences through novel interfaces and code generators. His research integrates formal methods, deep learning, and program synthesis to solve practical challenges in data-intensive applications.

His publications reveal a strong trend toward leveraging machine learning, particularly large language models, to enhance code generation, optimization, and understanding. Recent work increasingly focuses on verified approaches that combine formal reasoning with neural techniques, addressing challenges in database systems, compiler design, and programming language theory while maintaining correctness guarantees.

• ACSIC Rock Star Award (2025)
• AITO Dahl Nygaard Junior Prize (2024)
• VLDB Early Career Research Contributions Award (2023)
• Army Research Office Young Investigator Award (2022)
• Office of Naval Research Young Investigator Award (2021)
• Sloan Research Fellowship (2019)
• DOE Presidential Early Career Award for Scientists & Engineers (2019)

Professor Cheung has advised numerous doctoral and master's students who have gone on to positions at leading technology companies including AWS, OpenAI, Microsoft Research, and Adobe Research. His research has been generously supported by multiple federal agencies including the National Science Foundation, Department of Energy, Office of Naval Research, Army Research Office, and Intel Corporation, reflecting the significance and impact of his work across both academic and industrial settings.

He leads research efforts in the EPIC Data Lab, Sky Computing Lab, and SLICE Lab, where his team develops innovative approaches to data management, programming systems, and specialized computing ecosystems. Current projects focus on applying verified lifting techniques, developing new data processing frameworks, and creating user-friendly interfaces for data programming across diverse application domains.