World's Best Scientists 2026 revealed!

Overview

Alvin Cheung is affiliated with the University of California, Berkeley in the United States. Their research primarily spans the broad field of computer science, with a significant focus on specialized areas including computer networks and communications, artificial intelligence, information systems, computer vision and pattern recognition, and hardware and architecture.

The scientist's work covers multiple core topics such as advanced database systems and queries, distributed systems and fault tolerance, parallel computing and optimization techniques, cloud computing and resource management, topic modeling, natural language processing techniques, and service-oriented architecture and web services.

Cheung has published extensively, contributing numerous articles to various publication venues. Their frequent venues of publication include:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Proceedings of the ACM on Programming Languages
  • ACM SIGMOD Record
  • Communications of the ACM

Among the recent papers authored or coauthored by Alvin Cheung are:

  • "The Seattle Report on Database Research," 2020, ACM SIGMOD Record
  • "The Seattle Report on Database Research," 2022, Communications of the ACM
  • "Katara: synthesizing CRDTs with verified lifting," 2022, Proceedings of the ACM on Programming Languages
  • "Keep CALM and CRDT On," 2022, Proceedings of the VLDB Endowment
  • "QED: A Powerful Query Equivalence Decider for SQL," 2024, Proceedings of the VLDB Endowment

Frequent collaborators in their research include Joseph M. Hellerstein, Shadaj Laddad, Mae Milano, Conor Power, and Sahil Bhatia. Their collaborative work forms a substantial part of their scholarly output, with notable joint publications contributing to advancements in database systems and distributed computing.

Best Publications

  • Summarizing Source Code using a Neural Attention Model

    Srinivasan Iyer;Ioannis Konstas;Alvin Cheung;Luke Zettlemoyer

  • Learning a Neural Semantic Parser from User Feedback

    Srinivasan Iyer;Ioannis Konstas;Alvin Cheung;Jayant Krishnamurthy

  • Packet Transactions: High-Level Programming for Line-Rate Switches

    Anirudh Sivaraman;Alvin Cheung;Mihai Budiu;Changhoon Kim

  • Synthesizing highly expressive SQL queries from input-output examples

    Chenglong Wang;Alvin Cheung;Rastislav Bodik

  • Optimizing database-backed applications with query synthesis

    Alvin Cheung;Armando Solar-Lezama;Samuel Madden

  • Mapping Language to Code in Programmatic Context

    Srinivasan Iyer;Ioannis Konstas;Alvin Cheung;Luke Zettlemoyer

  • Undefined behavior: what happened to my code?

    Xi Wang;Haogang Chen;Alvin Cheung;Zhihao Jia

  • Towards Traceability across Sovereign, Distributed RFID Databases

    Rakesh Agrawal;Alvin Cheung;Karin Kailing;Stefan Schonauer

  • Automatic partitioning of database applications

    Alvin Cheung;Samuel Madden;Owen Arden;Andrew C. Myers

  • A new method for design of robust digital circuits

    D. Patil;S. Yun;S.-J. Kim;A. Cheung

  • HoTTSQL: proving query rewrites with univalent SQL semantics

    Shumo Chu;Konstantin Weitz;Alvin Cheung;Dan Suciu

  • Verified lifting of stencil computations

    Shoaib Kamil;Alvin Cheung;Shachar Itzhaky;Armando Solar-Lezama

  • PipeGen: Data Pipe Generator for Hybrid Analytics

    Brandon Haynes;Alvin Cheung;Magdalena Balazinska

  • The Seattle Report on Database Research

    Daniel Abadi;Anastasia Ailamaki;David Andersen;Peter Bailis

  • Leveraging lock contention to improve OLTP application performance

    Cong Yan;Alvin Cheung

  • Sloth: being lazy is a virtue (when issuing database queries)

    Alvin Cheung;Samuel Madden;Armando Solar-Lezama

  • How not to structure your database-backed web applications: a study of performance bugs in the wild

    Junwen Yang;Cong Yan;Pranav Subramaniam;Shan Lu

  • Cosette: An Automated Prover for SQL.

    Shumo Chu;Chenglong Wang;Konstantin Weitz;Alvin Cheung

  • Packet Transactions: High-level Programming for Line-Rate Switches

    Anirudh Sivaraman;Mihai Budiu;Alvin Cheung;Changhoon Kim

  • Automatic Partitioning of Database Applications

    Alvin Cheung;Owen Arden;Samuel Madden;Andrew C. Myers

Frequent Co-Authors

Magdalena Balazinska
Magdalena Balazinska University of Washington
Luis Ceze
Luis Ceze University of Washington
Dan Suciu
Dan Suciu University of Washington
Rastislav Bodik
Rastislav Bodik University of Washington
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Shan Lu
Shan Lu University of Chicago
Andrew C. Myers
Andrew C. Myers Cornell University

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