kaiyuanw@utexas.edu
kaiyuanw@google.com
PhD
Department of Electrical and Computer Engineering
The University of Texas at Austin
Currently at Google
I obtained my PhD in the Software Verification, Validation and Testing (SVVAT) group at the University of Texas at Austin. My adviser is Sarfraz Khurshid. I obtained my M.S. degree in software engineering at UT Austin in 2015 and my B.S. degree in computer science at Beijing Univeristy of Technology in 2013. I am currently working at Google Core Systems. My PhD dissertation can be found here.
My research interests lie in the field of software engineering. I have worked on a number of projects related to program synthesis, fault localization, automated program repair, regression test selection, model checking, mutation testing, automated test generation and symbolic execution. Overall, I am passionate about challenges and enjoy learning new technologies.
Recently, I am interested in combining machine learning techniques with my software engineering research.
Arxiv | [32] | Scalable Machine Learning Training Infrastructure for Online Ads Recommendation and Auction Scoring Modeling at Google G. Kurian, S. Sardashti, R. Sims, F. Berger, G. Holt, Y. Li, J. Willcock, K. Wang, H. Quiroz, A. Salem, J. Grady |
ICSE SEIP 2025 | [31] | Automating ML Model Development at Scale K. Wang, Y. Li, J. Shen, K. Sheng, Y. You, J. Zhang, S. Ayyalasomayajula, J. Grady, M. Wicke |
ASE 2024 | [30] | Efficient Incremental Code Coverage Analysis for Regression Test Suites J. Wang*, K. Wang*, P. Nie (*equal contribution) |
NeurIPS 2023 | [29] | Symbolic Discovery of Optimization Algorithms X. Chen, C. Liang, D. Huang, E. Real, K. Wang, H. Pham, X. Dong, T. Luong, C. Hsieh, Y. Lu, Q. Le |
Neural Networks Journal 2022 | [28] | MoET: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning M. Vasic, A. Petrovic, K. Wang, M. Nikolic, R. Singh, S. Khurshid |
FSE Demo 2021 | [27] | AlloyFL: A Fault Localization Framework for Alloy T.A. Khan, A. Sullivan, K. Wang |
ICSE SEIP 2021 | [26] | Smart Build Targets Batching Service at Google K. Wang, D. Rall, G. Tener, V. Gullapalli, X. Huang, A. Gad |
ISSRE 2020 | [25] | Fault Localization for Declarative Models in Alloy K. Wang, A. Sullivan, D. Marinov, S. Khurshid |
ISSTA 2020 | [24] | Scalable Build Service System with Smart Scheduling Service K. Wang, G. Tener, V. Gullapalli, X. Huang, A. Gad, D. Rall |
PLDI 2020 | [23] | A Study of the Learnability of Relational Properties M. Usman, W. Wang, M. Vasic, K. Wang, H. Vikalo, S. Khurshid |
TACAS 2020 | [22] | A Study of Symmetry Breaking Predicates and Model Counting W. Wang, M. Usman, A. Almaawi, K. Wang, K. S. Meel and S. Khurshid |
ISSRE 2019 | [21] | Symbolic Execution for Importance analysis and Adversarial generation in Neural Networks D. Gopinath, M. Zhang, K. Wang, B. Kadron, C. Pasareanu and S. Khurshid |
SPIN 2019 | [20] | A Study of Learning Data Structure Invariants Using Off-the-shelf Tools M. Usman, W. Wang, K. Wang, C. Yelen, N. Dini, S. Khurshid |
TACAS 2019 | [19] | Incremental Analysis of Evolving Alloy Models W. Wang, K. Wang, M. Gligoric, S. Khurshid |
ICST 2019 | [18] | Learning to Optimize the Alloy Analyzer W. Wang, K. Wang, M. Zhang, S. Khurshid |
ICSE Poster 2019 | [17] | Symbolic Execution for Attribution and Attack Synthesis in Neural Networks C. Pasareanu, D. Gopinath, S. Khurshid, K. Wang, M. Zhang |
ICSE Demo 2019 | [16] | ARepair: A Repair Framework for Alloy K. Wang, A. Sullivan, S. Khurshid |
JPF 2018 | [15] | A Progress Bar for the JPF Search Using Program Executions K. Wang, H. Converse, M. Gligoric, S. Misailovic, S. Khurshid |
ASE 2018 | [14] | Automated Model Repair for Alloy K. Wang, A. Sullivan, S. Khurshid |
FSE Demo 2018 | [13] | ASketch: A Sketching Framework for Alloy K. Wang, A. Sullivan, D. Marinov, S. Khurshid |
FSE Demo 2018 | [12] | SketchFix: A Tool for Automated Program Repair Approach Using Lazy Candidate Generation J. Hua, M. Zhang, K. Wang, S. Khurshid |
ABZ 2018 | [11] | Solver-based Sketching of Alloy Models using Test Valuations K. Wang, A. Sullivan, D. Marinov, S. Khurshid |
ABZ 2018 | [10] | Systematic Generation of Non-Equivalent Expressions for Relational Algebra K. Wang, A. Sullivan, M. Koukoutos, D. Marinov, S. Khurshid |
ICSE 2018 | [9] | Towards Refactoring-Aware Regression Test Selection K. Wang, C. Zhu, A. Celik, J. Kim, D. Batory, M. Gligoric |
ICSE 2018 | [8] | Towards Practical Program Repair with On-Demand Candidate Generation J. Hua, M. Zhang, K. Wang, S. Khurshid |
ICSE Demo 2018 | [7] | MuAlloy: A Mutation Testing Framework for Alloy K. Wang, A. Sullivan, S. Khurshid |
ICST 2018 | [6] | EdSynth: Synthesizing API Sequences with Conditionals and Loops Z. Yang, J. Hua, K. Wang, S. Khurshid |
ICST Demo 2018 | [5] | AUnit: A Test Automation Tool for Alloy A. Sullivan, K. Wang, S. Khurshid |
ICST 2017 | [4] | Automated Test Generation and Mutation Testing for Alloy A. Sullivan, K. Wang, R.N. Zaeem, S. Khurshid |
JPF 2017 | [3] | JPR: Replaying JPF Traces Using Standard JVM K. Wang, S. Khurshid, M. Gligoric |
SQAMIA 2017 | [2] | Evaluating State Modeling Techniques in Alloy A. Sullivan, K. Wang, S. Khurshid, D. Marinov |
ICSME 2016 | [1] | Repairing Intricate Faults in Code Using Machine Learning and Path Exploration D. Gopinath, K. Wang, J. Hua, S. Khurshid |
AST 2022 | Program Committee |
ASE 2019 | Research Track Program Committee |
ISSTA 2017 | Artifact Evaluation Committee |
09/2018-Present | Staff Software Engineer, Google, Mountain View, CA |