Welcome to Zhenlan’s homepage!

Updated on 25 Aug. 2023

Zhenlan Ji is currently a Ph.D. student at the Department of Computer Science and Engineering, Hong Kong University of Science and Technology, under the supervision of Prof. Shuai Wang. In 2021, he received his Bachelor’s degree in Computer Science and Technology from Nanjing University, Nanjing, China. His research interests include Software Engineering, Security, and Deep Learning, with a focus on the application of Causality Analysis.

Education

• Ph.D. in Computer Science and Engineering, The Hong Kong University of Science and Technology. Sept 2021 - Now
• B.S. in Computer Science and Technology (FinTech), Nanjing University.
  Sept 2017 - June 2021

Publications

• [ICSE] Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning.
  Pingchuan Ma, Zhenlan Ji, Peisen Yao, Shuai Wang, and Kui Ren.
  In The 46th IEEE/ACM International Conference on Software Engineering, 2024.

• [ASE] Causality-Aided Trade-off Analysis for Machine Learning Fairness.
  Zhenlan JI, Pingchuan Ma, Shuai Wang, Yanhui Li.
  In The 38th IEEE/ACM International Conference on Automated Software Engineering, 2023.
  [preprint] [code]

• [ASE] PerfCE: Performance Debugging on Databases with Chaos Engineering-Enhanced Causality Analysis.
  Zhenlan JI, Pingchuan Ma, Shuai Wang.
  In The 38th IEEE/ACM International Conference on Automated Software Engineering, 2023.
  [preprint] [code] [documentation]

• [ICSE] CC: Causality-Aware Coverage Criterion for Deep Neural Networks.
  Zhenlan JI, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang.
  In The 45th IEEE/ACM International Conference on Software Engineering, 2023.
  [code]

• [SEKE] Unlearnable Examples: Protecting Open-Source Software from Unauthorized Neural Code Learning.
  Zhenlan JI, Pingchuan Ma, Shuai Wang.
  In The 34th International Conference on Software Engineering and Knowledge Engineering, 2022.
  [code]

• [TIFS] NoLeaks: Differentially Private Causal Discovery Under Functional Causal Model.
  Pingchuan Ma, Zhenlan Ji, Qi Pang, Shuai Wang.
  In IEEE Transactions on Information Forensics and Security, 2022.

Academic Services

Artifact Evaluation Committee:

• 2022: ISSTA
• 2023: ISSTA

External Reviewer:

• 2022: ASE, AsiaCCS
• 2023: ISSTA, USENIX Security, FSE, CCS, ASE

Teaching

• Teaching Assistant, COMP2011 - Programming with C++, HKUST, 2022 Fall.
• Teaching Assistant, COMP3633 - Competitive Programming in Cybersecurity II, HKUST, 2023 Spring.