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Alvin Cheung received his undergraduate degree from Stanford University. ^[1] and his PhD in computer science from MIT under Samuel Madden and Armando Solar-Lezama. He joined the Paul G. Allen School of Computer Science & Engineering at the University of Washington as an assistant professor after receiving his PhD. He moved to the University of California, Berkeley in 2019 where he is currently an associate professor in the Electrical Engineering and Computer Sciences department.

Cheung's group works on various research problems that span across data management to programming languages. In data management, his group developed the Cosette, the first fully automated solver that decides the equivalence of SQL queries, ^[2] along with various data management systems for video data: LightDB, ^[3] the Visual Road video processing benchmark, ^[4] and Spatialyze. ^[5]

In programming languages, Cheung's group is known for verified lifting, ^[6] a technique that uses program synthesis rather than traditional pattern matching-based rules to compile code. His group has also developed program synthesis-based algorithms to help end users write code using natural language and examples. ^{[7] [8] [9]}

Cheung also teaches a popular undergraduate database class with Joseph Hellerstein at UC Berkeley. ^[10]

Awards and Recognitions

Cheung's research group has received a number of best paper awards. Cheung himself is a recipient of the Sloan Research Fellowship in 2019, ^[11] early career awards from the United States Department of Energy, ^[12] the National Science Foundation, ^[13] the Office of Naval Research. ^[14]

In addition, Cheung is also a recipient of the Presidential Early Career Award for Scientists and Engineers for his research on code transformations. ^[15] He has also received the Very Large Databases Endowment's Early Career Research Contribution Award for his data management work. ^[16]

References