Kexin Pei

Ph.D. Student

Department of Computer Science, Columbia University

kpei@cs.columbia.edu

Google Scholar, GitHub, Twitter

About Me

I am a fifth-year Ph.D. student at Department of Computer Science, Columbia University. I am co-advised by Suman Jana and Junfeng Yang, and work closely with Baishakhi Ray. Before coming to Columbia, I did my research-based Master at Department of Computer Science, Purdue University, advised by Dongyan Xu, Xiangyu Zhang, and Luo Si. Prior to Purdue, I worked at the HKBU Database Group, advised by Haibo Hu and Jianliang Xu. I am broadly interested in Security, Systems, and Machine Learning, with the current focus on developing ML architectures to understand program semantics and using them for program analysis and security.

Education

  • Ph.D., Department of Computer Science, Columbia University

  • M.S., Department of Computer Science, Purdue University

  • B.S., Department of Computer Science, Hong Kong Baptist University

Publication

  1. Kexin Pei, Jonas Guan, Matthew Broughton, Zhongtian Chen, Songchen Yao, David Williams-King, Vikas Ummadisetty, Junfeng Yang, Baishakhi Ray, Suman Jana. "StateFormer: Fine-Grained Type Recovery from Binaries using Generative State Modeling", to appear in Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021, Acceptance Rate: 24.5%). [pdf][code][slides][video]

  2. Kexin Pei, Zhou Xuan, Junfeng Yang, Suman Jana, Baishakhi Ray. "Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity". [pdf][code][slides]

  3. Kexin Pei*, Jonas Guan*, David Williams-King, Junfeng Yang, Suman Jana. "XDA: Accurate, Robust Disassembly with Transfer Learning", in Proceedings of the 2021 Network and Distributed System Security Symposium (NDSS 2021, Acceptance Rate: 15.2%). [pdf][code][slides][video]

  4. Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, Suman Jana. "NEUZZ: Efficient Fuzzing with Neural Program Smoothing", in Proceedings of the 40th IEEE Symposium on Security and Privacy (Oakland S&P 2019, Acceptance Rate: 13%). [pdf][code][slides][video]

  5. Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana. "Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems". in ICSE 2019 Workshop on Testing for Deep Learning and Deep Learning for Testing (DeepTest 2019). [pdf]

  6. Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana. "Efficient Formal Safety Analysis of Neural Networks", in Proceedings of the 32nd Conference on Neural Information Processing Systems (NIPS 2018, Acceptance Rate: 20.8%). [pdf][code][video]

  7. Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana. "Formal Security Analysis of Neural Networks using Symbolic Intervals", to appear in the 27th USENIX Security Symposium (USENIX Security 2018, Acceptance Rate: 19%). [pdf][code][video]

  8. Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray. "DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars", in Proceedings of the 40th International Conference on Software Engineering (ICSE 2018, Acceptance Rate: 21%). [pdf][code][results]

  9. Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana. "DeepXplore: Automated Whitebox Testing of Deep Learning Systems", in Proceedings of the 26th ACM Symposium on Operating Systems Principles (SOSP 2017, Acceptance Rate: 16%). Best Paper Award. [pdf][code][poster][slides]

    • Research Highlights of Communications of the ACM (CACM). [article][video].

    • 2nd Place in CSAW 2018 Top-10 Finalist of Applied Research Competition Finalist (CSAW'18).

    • In Research Highlights of ACM SigMobile: Mobile Computing and Communications (GetMobile).

    • In Proceedings of the NIPS 2017 Workshop on Machine Learning and Computer Security (MLSec 2017).

  10. Suphannee Sivakorn, George Argyros, Kexin Pei, Angelos D. Keromytis, Suman Jana. "HVLearn: Automated Black-box Analysis of Hostname Verification in SSL/TLS Implementations", in Proceedings of the 38th IEEE Symposium on Security and Privacy (Oakland S&P 2017, Acceptance Rate: 13%). [pdf][code]

  11. Kexin Pei, Zhongshu Gu, Brendan Saltaformaggio, Shiqing Ma, Fei Wang, Zhiwei Zhang, Luo Si, Xiangyu Zhang, Dongyan Xu. "HERCULE: Attack Story Reconstruction via Community Discovery on Correlated Log Graph", in Proceedings of the 32nd Annual Computer Security Applications Conference (ACSAC 2016, Acceptance Rate: 22%). [pdf]

  12. Zhaogui Xu, Xiangyu Zhang, Lin Chen, Kexin Pei, Baowen Xu. "Python Probabilistic Type Inference with Natural Language Support", in Proceedings of the 24th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE 2016, Acceptance Rate: 27%). Diamond Artifact Award. [pdf]

  13. Zhongshu Gu, Kexin Pei, Qifan Wang, Luo Si, Xiangyu Zhang, Dongyan Xu. "LEAPS: Detecting Camouflaged Attacks with Statistical Learning Guided by Program Analysis", in Proceedings of the 45th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2015, Acceptance Rate: 21%). [pdf]

  14. Haibo Hu, Jianliang Xu, Xizhong Xu, Kexin Pei, Byron Choi, Shuigeng Zhou. "Private Search on Key-Value Stores with Hierarchical Indexes", in Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE 2014, Acceptance Rate: 20%). [pdf]

Work Experience

Invited Talks

  • "Scalable, Accurate, Robust Binary Analysis with Transfer Learning Trace Modeling". National University of Singapore.

  • "Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity". University of Stuttgart

  • "XDA: Accurate, Robust Disassembly with Transfer Learning". Rutgers University

  • "Towards Testing and Verification of Machine Learning (ML) Systems". Microsoft Research Redmond

  • "Towards Testing and Verification of Machine Learning (ML) Systems". NEC Lab Princeton

  • "LEAPS: Detecting Camouflaged Attacks with Statistical Learning Guided by Program Analysis". CERIAS Security Seminar Series

Professional Activities

  • Program Committee. AAAI Conference on Artificial Intelligence (AAAI 2022)

  • Program Committee. International Conference on Learning Representations (ICLR 2022)

  • Program Committee. CSAW Applied Research Competition (CSAW 2021)

  • Program Committee. ACM Workshop on Artificial Intelligence and Security (AISec 2021)

  • Program Committee. Neural Information Processing Systems (NeurIPS 2021)

  • Reviewer. ACM Conference on Computer and Communications Security (CCS 2021)

  • Reviewer. USENIX Security Symposium (USENIX 2020)

  • Reviewer. ACM Conference on Computer and Communications Security (CCS 2017).

  • Reviewer. USENIX Security Symposium (USENIX 2017).

  • Reviewer. IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2016).

  • Reviewer. International Symposium on Research in Attacks, Intrusions, and Defenses (RAID 2016).

Personal