World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
12342
World Ranking
7048
National Ranking
3093

Research.com Recognitions

  • 2014 - ACM Distinguished Member

Overview

Clark Barrett is affiliated with Stanford University in the United States. Their research primarily spans the field of Computer Science with a substantial focus on Artificial Intelligence, Computational Theory and Mathematics, Software, Hardware and Architecture, and Electrical and Electronic Engineering.

The main topics of their work include:

  • Formal Methods in Verification
  • Logic, programming, and type systems
  • Adversarial Robustness in Machine Learning
  • Software Testing and Debugging Techniques
  • Explainable Artificial Intelligence (XAI)
  • Security and Verification in Computing
  • Advanced Neural Network Applications

Barrett has a significant number of recent papers published across varied venues. Some of these include:

  • "FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU," 2023, arXiv (Cornell University)
  • "Reluplex: a calculus for reasoning about deep neural networks," 2021, Formal Methods in System Design
  • "Identifying and Mitigating the Security Risks of Generative AI," 2023, Foundations and Trends® in Privacy and Security
  • "AHA: An Agile Approach to the Design of Coarse-Grained Reconfigurable Accelerators and Compilers," 2022, ACM Transactions on Embedded Computing Systems
  • "H₂O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models," 2023, arXiv (Cornell University)

Frequent publication venues where Barrett's work appears include:

  • arXiv (Cornell University)
  • Journal of Automated Reasoning
  • Lecture Notes in Computer Science
  • Formal Methods in System Design
  • EPiC Series in Computing

Within collaborative research, Barrett has worked notably with several coauthors such as:

  • Cesare Tinelli
  • Yoni Zohar
  • Haoze Wu
  • Andrew Reynolds
  • Guy Katz

In addition to journal and conference publications, Barrett has also contributed to academic literature as an author of a book titled Algorithms for Verifying Deep Neural Networks, published by Now Publishers in 2021.

Their contributions have been recognized with the award of ACM Distinguished Member in 2014.

Best Publications

  • Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

    Guy Katz;Clark W. Barrett;David L. Dill;Kyle Julian

  • Satisfiability Modulo Theories

    Clark W. Barrett;Cesare Tinelli

  • The SMT-LIB Standard Version 2.0

    Clark Barrett;Aaron Stump;Cesare Tinelli

  • cvc5: A Versatile and Industrial-Strength SMT Solver

    Unknown

  • The Marabou Framework for Verification and Analysis of Deep Neural Networks

    Guy Katz;Derek A. Huang;Duligur Ibeling;Kyle Julian

  • CVC Lite: A new implementation of the cooperating validity checker: Category B

    Clark W. Barrett;Sergey Berezin

  • CVC: A Cooperating Validity Checker

    Aaron Stump;Clark W. Barrett;David L. Dill

  • Validity Checking for Combinations of Theories with Equality

    Clark W. Barrett;David L. Dill;Jeremy R. Levitt

  • Checking Satisfiability of First-Order Formulas by Incremental Translation to SAT

    Clark W. Barrett;David L. Dill;Aaron Stump

  • A decision procedure for an extensional theory of arrays

    A. Stump;C.W. Barrett;D.L. Dill;J. Levitt

  • A decision procedure for bit-vector arithmetic

    Clark W. Barrett;David L. Dill;Jeremy R. Levitt

  • A DPLL(T) Theory Solver for a Theory of Strings and Regular Expressions

    Tianyi Liang;Andrew Reynolds;Cesare Tinelli;Clark Barrett

  • Counterexample-Guided Quantifier Instantiation for Synthesis in SMT

    Andrew Reynolds;Morgan Deters;Viktor Kuncak;Cesare Tinelli

  • SMT-COMP: satisfiability modulo theories competition

    Clark Barrett;Leonardo de Moura;Aaron Stump

  • Algorithms for Verifying Deep Neural Networks

    Changliu Liu;Tomer Arnon;Christopher Lazarus;Christopher A. Strong

  • Splitting on demand in SAT modulo theories

    Clark Barrett;Robert Nieuwenhuis;Albert Oliveras;Cesare Tinelli

  • Provably Minimally-Distorted Adversarial Examples

    Nicholas Carlini;Guy Katz;Clark Barrett;David L. Dill

  • An industrially effective environment for formal hardware verification

    C.-J.H. Seger;R.B. Jones;J.W. O'Leary;T. Melham

  • Solving quantified verification conditions using satisfiability modulo theories

    Yeting Ge;Clark Barrett;Cesare Tinelli

  • Towards Proving the Adversarial Robustness of Deep Neural Networks

    Guy Katz;Clark W. Barrett;David L. Dill;Kyle Julian

  • 6 Years of SMT-COMP

    Clark Barrett;Morgan Deters;Leonardo Moura;Albert Oliveras

Frequent Co-Authors

Cesare Tinelli
Cesare Tinelli University of Iowa
David L. Dill
David L. Dill Stanford University
Mykel J. Kochenderfer
Mykel J. Kochenderfer Stanford University
Leonardo de Moura
Leonardo de Moura Microsoft (United States)
Pat Hanrahan
Pat Hanrahan Stanford University
Lenore D. Zuck
Lenore D. Zuck University of Illinois at Chicago
Mark Horowitz
Mark Horowitz Stanford University
Corina S. Pasareanu
Corina S. Pasareanu Carnegie Mellon University
Amir Pnueli
Amir Pnueli Weizmann Institute of Science
Nicholas Carlini
Nicholas Carlini Google (United States)

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