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Xujie Sie-BW_F

Xujie Si

Appointment

  • Canada CIFAR AI Chair
  • Pan-Canadian AI Strategy

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About

Xujie Si’s research lies at the intersection of programming languages and artificial intelligence. He is interested in developing AI-based techniques to democratize programming for non-professional programmers, and to help professional programmers build secure and reliable software with less effort. He has developed intelligent systems that automatically synthesize programs from input and output examples, mine correct/incorrect software usages from massive codebases, efficiently diagnose software vulnerabilities through a small amount of user feedback, and formally verify software correctness without requiring human annotations. On the other hand, he is interested in leveraging formal methods and programming principles to improve AI techniques, especially in terms of interpretability, robustness, and data efficiency.  

Awards

  • ACM SIGPLAN Distinguished Paper Award, PLDI, 2019
  • CSAW Best Applied Security Paper finalist, 2016

Relevant Publications

  • Si, X., Raghothaman, M., Heo, K., & Naik, M. (2019). Synthesizing datalog programs using numerical relaxation. arXiv preprint arXiv:1906.00163.
  • Heo, K., Raghothaman, M., Si, X., & Naik, M. (2019, June). Continuously reasoning about programs using differential bayesian inference. In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (pp. 561-575).
  • Si, X., Dai, H., Raghothaman, M., Naik, M., & Song, L. (2018). Learning loop invariants for program verification. Advances in Neural Information Processing Systems, 31, 7751-7762.
  • Si, X., Zhang, X., Grigore, R., & Naik, M. (2017, July). Maximum satisfiability in software analysis: Applications and techniques. In International Conference on Computer Aided Verification (pp. 68-94). Springer, Cham.
  • Yun, I., Min, C., Si, X., Jang, Y., Kim, T., & Naik, M. (2016). APISan: Sanitizing {API} Usages through Semantic Cross-Checking. In 25th {USENIX} Security Symposium ({USENIX} Security 16) (pp. 363-378).

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