Yue (Knox) Liu
Research Scientist · Singapore Management University
Trustworthy AI for software development

About

Software Engineering Artificial Intelligence Cybersecurity

I'm a Research Scientist at Singapore Management University, building agentic vulnerability detection systems for government software products in collaboration with GovTech Singapore. I obtained my Ph.D. from Monash University (2024), advised by Chakkrit Tantithamthavorn and Li Li.

My research aims to make AI-powered software development trustworthy in practice. I have published 15+ papers in top-tier venues (ICSE, ASE, TOSEM) and received an ACM SIGSOFT Distinguished Paper Award. My research for AI systems has helped improve popular AI development tools including OpenClaw, Zed, VMware, and SWE-agent.

I care deeply about democratizing AI for software development. With AI, anyone can now become a software developer. But not every developer comes from the same background or community. I am dedicated to making AI coding tools accessible, inclusive, and empowering for developers of all backgrounds and skill levels.

AI Models for Code
Evaluation, reliability, and explainability of AI models in software engineering
Development Ecosystems
Security of IDE plugins, agentic editors, and AI coding tools
AI Solutions
Quality, security, and self-repair of code produced by AI systems
Human Factors
Developer perception, trust, and adoption of AI coding tools

Education

  • Ph.D. in Information Technology
    Monash University, Australia — Advisors: Chakkrit Tantithamthavorn, Li Li, Chetan Arora
    2021–2024
  • B.S. in Computer Science
    Southern University of Science and Technology, China
    2015–2019

News

  • 2025 Joined Singapore Management University as a Research Scientist, collaborating with GovTech Singapore.
  • 2025 Paper on users' perception of AI coding assistants received the ACM SIGSOFT Distinguished Paper Award at ASE 2025.
  • 2025 Paper on security of framework-constrained program generation accepted at ICSE 2026.
  • 2024 Successfully defended my Ph.D. thesis at Monash University.

Selected Publications

Full list on Google Scholar.

Conference Papers

When AI Takes the Wheel: Security Analysis of Framework-Constrained Program Generation
Yue Liu, Zhenchang Xing, Shidong Pan, and Chakkrit Tantithamthavorn
ICSE 2026 (Core A*, CCF A)
PDF
"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistants
Yunbo Lyu, Zhou Yang, Jieke Shi, Jianming Chang, Yue Liu, David Lo
ASE 2025 (Core A*, CCF A) Distinguished Paper
PDF
Protect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
Yue Liu, Chakkrit Tantithamthavorn, and Li Li
SANER 2025, 551–562 (Core A, CCF B)
Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
ISSRE 2022, 169–180 (Core A, CCF B)
PDF Code

Journal Papers

Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
Xinyu She, Yue Liu, Yanjie Zhao, Yiling He, Li Li, Chakkrit Tantithamthavorn, Zhan Qin, and Haoyu Wang
ACM TOSEM, 2025 (Core A*, CCF A)
PDF Code
On the Reliability and Explainability of Language Models for Program Generation
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, and Li Li
ACM TOSEM, 2024, 33(5): 1–26 (Core A*, CCF A)
PDF Code
Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues
Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Tantithamthavorn, Li Li, Xuan-Bach D. Le, and David Lo
ACM TOSEM, 2024, 33(5): 1–26 (Core A*, CCF A) Top 15 Most Downloaded
PDF Code
Automatically Recommend Code Updates: Are We There Yet?
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, Patanamon Thongtanunam, and Li Li
ACM TOSEM, 2024, 33(8): 1–27 (Core A*, CCF A)
PDF
Large Language Models for Software Engineering: A Systematic Literature Review
Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John Grundy, and Haoyu Wang
ACM TOSEM, 2024, 33(8): 1–79 (Core A*, CCF A) Top 5 Most Downloaded
PDF
Deep Learning for Android Malware Defenses: a Systematic Literature Review
Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
ACM Computing Surveys, 2022, 55(8): 1–36 (Core A*, SCI-Q1)
PDF Code

Preprints / Under Review

"Your AI, My Shell": Demystifying Prompt Injection Attacks on Agentic AI Coding Editors
Yue Liu, Yanjie Zhao, Yunbo Lyu, Ting Zhang, Haoyu Wang, and David Lo
Under review, 2025
PDF

Professional Service

Program Committee

  • WWW 2026
  • MSR 2023, 2026
  • IUI 2026
  • IJCAI 2025
  • IJCNN 2025

Journal Reviewer

  • TSE, TOSEM, TMC
  • IST, JSS, ASE Journal
  • IEEE Software, KAIS

Conference Reviewer

  • ICSE 2024
  • WWW 2025
  • COLING 2025
  • IUI 2025
  • AAAI UC 2025

Awards & Honors

  • ACM SIGSOFT Distinguished Paper Award, ASE 20252025
  • Researcher Access Program Funding, OpenAI2024–2025
  • Google Cloud Research Credits2025
  • Postgraduate Publications Award, Monash University2024
  • Ph.D. Scholarship (Full Time), Monash University2019–2024
  • Excellent Undergraduate Thesis, SUSTech2019

Teaching

Monash University, Australia

  • FIT3077 Software Engineering: Architecture and Design — TA, Spring 2022
  • FIT2099 Object-Oriented Design and Implementation — TA, Spring 2022
  • FIT1051 Programming Fundamentals in Java — TA, Fall 2022

Southern University of Science and Technology, China

  • CS203 Data Structures and Algorithm Analysis — TA, Fall 2018
  • CS209 Computer System Design and Application — TA, Spring 2018, Fall 2017
  • CS201 Computer Organization Principle — TA, Spring 2018

Prepared to Teach

Introduction to Programming Data Structures & Algorithms Object-Oriented Programming Database Systems Software Testing Software Architecture Software Analysis Program Analysis AI for Software Engineering

Contact

I am actively seeking Lecturer / Assistant Professor and Research Scientist positions. I am also open to research collaborations. Feel free to reach out.

yuehhhliu@gmail.com Scholar GitHub LinkedIn