Registered user since Fri 4 May 2018
Qingkai Shi is a Postdoc Research Associate in the department of computer science at Purdue University. His major research interest is the use of compiler techniques to ensure software reliability. He has published extensively at premium venues of programming languages (PLDI, OOPSLA), software engineering (ICSE, FSE), and cybersecurity (S&P). His research received many awards including ACM SIGSOFT Distinguished Paper Award and Hong Kong Ph.D. Fellowship. His research has led to the discovery of over a hundred software vulnerabilities in open-source software and has been successfully commercialized in Sourcebrella Inc, a static analysis tool vendor. Qingkai obtained his B.S. and Ph.D. from Nanjing University and the Hong Kong University of Science and Technology, respectively.
- Author of Fast Bit-Vector Satisfiability within the Technical Papers-track
- Author of DeepGini: Prioritizing Massive Tests to Enhance the Robustness of Deep Neural Networks within the Technical Papers-track
- Author of Test Recommendation System Based on Slicing Coverage Filtering within the Tool Demonstration-track
- Author of Escaping Dependency Hell: Finding Build Dependency Errors with the Unified Dependency Graph within the Technical Papers-track
- Author of Functional Code Clone Detection with Syntax and Semantics Fusion Learning within the Technical Papers-track