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Computer Science

D-Index
32
Citations
5826
World Ranking
12985
National Ranking
5238

Overview

Swarat Chaudhuri is a researcher affiliated with The University of Texas at Austin in the United States. Their work primarily spans the field of Computer Science, with a significant focus on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Software, and Control and Systems Engineering.

Their research interests cover a range of topics including Formal Methods in Verification, Topic Modeling, Reinforcement Learning in Robotics, Explainable Artificial Intelligence (XAI), Machine Learning and Algorithms, Natural Language Processing Techniques, and Domain Adaptation and Few-Shot Learning.

The following are some of their recent papers:

  • Neurosymbolic Programming, 2021, Foundations and Trends® in Programming Languages
  • Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Bottom-up synthesis of recursive functional programs using angelic execution, 2022, Proceedings of the ACM on Programming Languages
  • CFLOBDDs: Context-Free-Language Ordered Binary Decision Diagrams, 2024, ACM Transactions on Programming Languages and Systems
  • Neurosymbolic Reinforcement Learning with Formally Verified Exploration, 2020, arXiv (Cornell University)

Swarat Chaudhuri has published frequently in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Programming Languages
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Foundations and Trends® in Programming Languages
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The scientist has collaborated with several frequent co-authors, including:

  • Işıl Dillig
  • Thomas Reps
  • Chris Jermaine
  • Yisong Yue
  • Greg Durrett

In addition to research papers, Swarat Chaudhuri has contributed to book publications, including a title published by Springer Science+Business Media in 2023 named NASA Formal Methods.

Best Publications

  • A study of android application security

    William Enck;Damien Octeau;Patrick McDaniel;Swarat Chaudhuri

  • AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation

    Timon Gehr;Matthew Mirman;Dana Drachsler-Cohen;Petar Tsankov

  • Synthesizing data structure transformations from input-output examples

    John K. Feser;Swarat Chaudhuri;Isil Dillig

  • Incremental Task and Motion Planning: A Constraint-Based Approach

    Neil T. Dantam;Zachary K. Kingston;Swarat Chaudhuri;Lydia E. Kavraki

  • Component-based synthesis of table consolidation and transformation tasks from examples

    Yu Feng;Ruben Martins;Jacob Van Geffen;Isil Dillig

  • Programmatically Interpretable Reinforcement Learning

    Abhinav Verma;Vijayaraghavan Murali;Rishabh Singh;Pushmeet Kohli

  • Proving programs robust

    Swarat Chaudhuri;Sumit Gulwani;Roberto Lublinerman;Sara Navidpour

  • An incremental constraint-based framework for task and motion planning

    Neil T Dantam;Zachary K Kingston;Swarat Chaudhuri;Lydia E Kavraki

  • Continuity analysis of programs

    Swarat Chaudhuri;Sumit Gulwani;Roberto Lublinerman

  • A constraint-based approach to solving games on infinite graphs

    Tewodros Beyene;Swarat Chaudhuri;Corneliu Popeea;Andrey Rybalchenko

  • Continuity and robustness of programs

    Swarat Chaudhuri;Sumit Gulwani;Roberto Lublinerman

  • Subcubic algorithms for recursive state machines

    Swarat Chaudhuri

  • Optimization and abstraction: a synergistic approach for analyzing neural network robustness

    Greg Anderson;Shankara Pailoor;Isil Dillig;Swarat Chaudhuri

  • Neural Sketch Learning for Conditional Program Generation

    Vijayaraghavan Murali;Letao Qi;Swarat Chaudhuri;Chris Jermaine

  • SMT-based synthesis of integrated task and motion plans from plan outlines

    Srinivas Nedunuri;Sailesh Prabhu;Mark Moll;Swarat Chaudhuri

  • Path-based inductive synthesis for program inversion

    Saurabh Srivastava;Sumit Gulwani;Swarat Chaudhuri;Jeffrey S. Foster

  • Languages of nested trees

    Rajeev Alur;Swarat Chaudhuri;P. Madhusudan

  • Bayesian specification learning for finding API usage errors

    Vijayaraghavan Murali;Swarat Chaudhuri;Chris Jermaine

  • Smooth interpretation

    Swarat Chaudhuri;Armando Solar-Lezama

  • Model checking of linearizability of concurrent list implementations

    Pavol Černý;Arjun Radhakrishna;Damien Zufferey;Swarat Chaudhuri

  • Control Regularization for Reduced Variance Reinforcement Learning

    Richard Cheng;Abhinav Verma;Gabor Orosz;Swarat Chaudhuri

  • Imitation-Projected Programmatic Reinforcement Learning

    Abhinav Verma;Hoang Minh Le;Yisong Yue;Swarat Chaudhuri

  • Neurosymbolic Reinforcement Learning with Formally Verified Exploration

    Greg Anderson;Abhinav Verma;Isil Dillig;Swarat Chaudhuri

Frequent Co-Authors

Rajeev Alur
Rajeev Alur University of Pennsylvania
Lydia E. Kavraki
Lydia E. Kavraki Rice University
Isil Dillig
Isil Dillig The University of Texas at Austin
Yisong Yue
Yisong Yue California Institute of Technology
P. Madhusudan
P. Madhusudan University of Illinois at Urbana-Champaign
Moshe Y. Vardi
Moshe Y. Vardi Rice University
Sumit Gulwani
Sumit Gulwani Microsoft (United States)
Thomas Reps
Thomas Reps University of Wisconsin–Madison
Kousha Etessami
Kousha Etessami University of Edinburgh

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