About Me

I’m Knox Liu, a Ph.D. student at Monash University, with a research focus on software security and AI Alignment Research for software development. I’m deeply passionate about harnessing the power of artificial intelligence to enhance and secure the software development lifecycle. My goal is to develop methodologies and tools that ensure the reliability and safety of AI-driven software development applications. Particularly, I am trying to explore the following research questions:

  1. How reliable AI-driven software development applications?
  2. How can we improve the reliability of AI-driven software development applications?
  3. What best practices should software developers follow to ensure reliable AI-driven software development?

If they look interesting to you, let's see more about my research and publications.

Research interests:

I'm also open to connections and collaborations now. Whether you're an experienced researcher, have an interesting project idea, or are a junior looking for guidance, I'm eager to hear from you. Feel free to contact me to discuss potential opportunities.

Publications

Ph.D. Thesis


Towards Reliable LLM-based Software Development Tools
Yue Liu
If you are interested in my work, please refer to my presentation slides in the meantime. The completed dissertation will be uploaded soon after the final review process.

International Journals


On the Reliability and Explainability of Language Models for Program Generation
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, and Li Li
ACM Transactions on Software Engineering and Methodology (TOSEM 2024), to appear (Core A*, CCF A)

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 Transactions on Software Engineering and Methodology (TOSEM 2024), to appear (Core A*, CCF A)

Deep Learning for Android Malware Defenses: a Systematic Literature Review
Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
ACM Computing Surveys (CSUR 2022), 55(8): 1-36 (Core A*, SCI-Q1)

Automatically Recommend Code Updates: Are We There Yet?
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, Patanamon Thongtanunam, Li Li
ACM Transactions on Software Engineering and Methodology (TOSEM 2024), to appear (Core A*, CCF A)

Pre-Prints


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

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

International Conferences


Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
33rd International Symposium on Software Reliability Engineering (ISSRE 2022), 169-180 (Core A, CCF B)

Island model genetic algorithm for feature selection in non-traditional credit risk evaluation
Yue Liu, Adam Ghandar, and Georgios Theodoropoulos
IEEE congress on evolutionary computation (CEC), June 2019, 2771-2778 (Core B)

A metaheuristic strategy for feature selection problems: Application to credit risk evaluation in emerging markets
Yue Liu, Adam Ghandar, and Georgios Theodoropoulos
2019 IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr), May 2019, 1-7

Workshops


Detecting Temporal Inconsistency in Biased Datasets for Android Malware Detection
Haonan Hu, Yue Liu, Yanjie Zhao, Yonghui Liu, Xiaoyu Sun, Chakkrit Tantithamthavorn, and Li Li
38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW 2023), 17-23

Online NEAT for Credit Evaluation--a Dynamic Problem with Sequential Data
Yue Liu, Adam Ghandar, and Georgios Theodoropoulos
2nd KDD Workshop on Anomaly Detection in Finance, August 2019

Research Services

Program Committee Member

  • AAAI 2024: The 38th Annual AAAI Conference on Artificial Intelligence, Undergraduate Consortium (Core A*)
  • MSR 2025: International Conference on Mining Software Repositories, Junior Program Committee (Core A)
  • MSR 2023: International Conference on Mining Software Repositories, Junior Program Committee (Core A)

Journal Reviewer

  • TSE: IEEE Transactions on Software Engineering (Core A*)
  • TMC: IEEE Transactions on Mobile Computing (Core A*)
  • IEEE Software

Conference Reviewer

  • WWW 2024: The International World Wide Web Conference (Core A*)
  • EACL 2023: The 18th Conference of the European Chapter of the Association for Computational Linguistics (Core A)
  • NeurIPS 2024: The 4th Workshop on Mathematical Reasoning and AI

Honors and Funding

  • Researcher Access Program Funding, OpenAI, 2024
  • Google Cloud Research Credits, 2025
  • Postgraduate Publications Award, Monash University, 2024

Teaching

Spring 2022

FIT3077 Software Engineering: Architecture and Design - Teaching Assistant, Monash University
FIT2099 Object oriented Design and Implementation - Teaching Assistant, Monash University

Fall 2022

FIT1051 Programming fundamentals in Java - Teaching Assistant, Monash University

Fall 2018

CS203 Data Structure and Algorithm Analysis - Teaching Assistant, SUSTech

Spring 2018

CS209 Computer System Design and Application - Teaching Assistant, SUSTech
CS201 Computer Organization Principle - Teaching Assistant, SUSTech

Fall 2017

CS209 Computer System Design and Application - Teaching Assistant, SUSTech

Contact

I'm open to connections and collaborations now, please don't hesitate to reach out to me via email:

Email: yue.liu1@monash.edu