Triet Le

Dr Triet Le

Lecturer

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.

I am currently a continuing Lecturer, a.k.a. Assistant Professor, and a Software Security lead in the Centre for Research on Engineering Software Technologies in the School of Computer and Mathematical Sciences at The University of Adelaide, Australia, where I also obtained my PhD. My research interests are but not limited to Software Security Analytics and Mining Software Repositories. My current work focuses on developing Machine Learning and Deep Learning techniques for detecting, analysing, and mitigating software vulnerabilities, aiming to proactively prevent cyber-attacks and ensure a secure digital economy. My latest profile can be found at https://trietle.net/.

My research aims to bring to design, develop, and evaluate smart solutions based on state-of-the-art Artificial Intelligence technologies such as machine learning and deep learning to automate and distill recommendations on secure software engineering.

Specifically, my PhD thesis advances the field of software security by providing knowledge and automation support for software vulnerability assessment using data-driven approaches. Software vulnerability assessment provides important and multifaceted information to prevent and mitigate dangerous cyber-attacks in the wild. The key contributions include a systematisation of knowledge, along with a suite of novel data-driven techniques and practical recommendations for researchers and practitioners in the area. The thesis results help improve the understanding and inform the practice of assessing ever-increasing vulnerabilities in real-world software systems. This in turn enables more thorough and timely fixing prioritisation and planning of these critical security issues.

  • Journals
    Year Citation
    2024 Arani, A. K., Le, T. H. M., Zahedi, M., & Ali Babar, M. (2024). Systematic Literature Review on Application of Learning-based Approaches in Continuous Integration. IEEE Access, 12, 135419-135450.
    DOI Scopus3
    2023 Wang, J., Lv, H., Tong, X., Ren, W., Shen, Y., Lu, L., & Zhang, Y. (2023). Modulation of radical and nonradical pathways via modified carbon nanotubes toward efficient oxidation of binary pollutants in water. Journal of Hazardous Materials, 459, 132334.
    DOI Scopus17
    2023 You, Y., Ma, Z., Gu, Y., Ren, J., Wang, Y., Li, Y., . . . Hou, F. (2023). Litter leachates transform soil bacterial composition enhancing nitrogen fixation in alpine meadow. APPLIED SOIL ECOLOGY, 189, 11 pages.
    DOI
    2023 Xu, R., Shi, W., Kamran, M., Chang, S., Jia, Q., & Hou, F. (2023). Grass-legume mixture and nitrogen application improve yield, quality, and water and nitrogen utilization efficiency of grazed pastures in the loess plateau. FRONTIERS IN PLANT SCIENCE, 14, 17 pages.
    DOI
    2023 Le, T. H. M., Chen, H., & Babar, M. A. (2023). A Survey on Data-driven Software Vulnerability Assessment and Prioritization. ACM Computing Surveys, 55(5), 1-39.
    DOI Scopus34 WoS3
    2022 Ghani, M. U., Kamran, M., Ahmad, I., Arshad, A., Zhang, C., Zhu, W., . . . Hou, F. (2022). Alfalfa-grass mixtures reduce greenhouse gas emissions and net global warming potential while maintaining yield advantages over monocultures. SCIENCE OF THE TOTAL ENVIRONMENT, 849, 14 pages.
    DOI
    2022 Mai, T. V. T., Nguyen, H. D., Nguyen, P. D., Nguyen, H. T., Na, O. M., Le, T. H. M., & Huynh, L. K. (2022). Ab initio kinetics of OH-initiated oxidation of cyclopentadiene. Fuel, 317, 1-10.
    DOI Scopus8 WoS4
    2022 Le, T. H. M. (2022). Towards an Improved Understanding of Software Vulnerability Assessment
    Using Data-Driven Approaches.
    2020 Le, T. H. M., Chen, H., & Babar, M. A. (2020). Deep Learning for Source Code Modeling and Generation: Models, Applications, and Challenges. ACM Computing Surveys, 53(3), 38 pages.
    DOI Scopus106 WoS46
    2018 Le, T. H. M., Tran, T. T., & Huynh, L. K. (2018). Identification of hindered internal rotational mode for complex chemical species: A data mining approach with multivariate logistic regression model. Chemometrics and Intelligent Laboratory Systems, 172, 10-16.
    DOI Scopus60 WoS46
    2017 Le, T. H. M., Do, S. T., & Huynh, L. K. (2017). Algorithm for auto-generation of hindered internal rotation parameters for complex chemical systems. Computational and Theoretical Chemistry, 1100, 61-69.
    DOI Scopus50 WoS42
    2017 Minh Le, T. H., & Duong, T. H. (2017). Online collaborative video annotation framework using Good Relations ontology for E-commerce. International Journal of Advanced Computer Research, 7(31), 121-135.
    DOI

  • Book Chapters
    Year Citation
    2023 Maadad, N., & Yu, M. (2023). Wellbeing and Online Learning: Perspectives of Refugee-Background Students. In M. White, F. McCallum, & C. Boyle (Eds.), New Research and Possibilities in Wellbeing Education (pp. 245-265). Springer.
    DOI

  • Conference Papers
    Year Citation
    2024 Le, T. H. M., Babar, M. A., & Thai, T. H. (2024). Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT. In Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering (pp. 679-685). Online: ACM.
    DOI Scopus3
    2024 Minh Le, T. H., Du, X., & Babar, M. A. (2024). Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study. In Proceedings - 2024 IEEE/ACM 21st International Conference on Mining Software Repositories, MSR 2024 (pp. 716-727). Online: ACM.
    DOI Scopus3
    2024 Nguyen, A. T., Le, T. H. M., & Babar, M. A. (2024). Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++. In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (pp. 72-83). Barcelona, Spain: IEEE Computer Society.
    DOI
    2024 Le, T. H. M., & Ali Babar, M. (2024). Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?. In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (pp. 119-130). Barcelona: IEEE Computer Society.
    DOI
    2024 Le, T. H. M., & Babar, M. A. (2024). Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?. In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (pp. 131-142). Barcelona: IEEE Computer Society.
    DOI
    2023 Arani, A. K., Zahedi, M., Le, T. H. M., & Babar, M. A. (2023). SoK: Machine Learning for Continuous Integration. In Proceedings - 2023 IEEE/ACM International Workshop on Cloud Intelligence and AIOps, AIOps 2023 (pp. 8-13). Online: IEEE.
    DOI Scopus3
    2022 Le, T., Hin, D., Croft, R., & Babar, M. (2022). DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning. In Proceedings - 2021 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021 (pp. 717-729). online: IEEE.
    DOI Scopus54 WoS11
    2022 Duan, X., Ge, M., Le, T. H., Ullah, F., Gao, S., Lu, X., & Babar, M. A. (2022). Automated Security Assessment for the Internet of Things. In Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC Vol. 2021-December (pp. 47-56). online: IEEE.
    DOI Scopus17 WoS7
    2022 Le, T. H. M., & Babar, M. A. (2022). On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models. In MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories (pp. 621-633). Pittsburgh Pennsylvania, USA: Association for Computing Machinery.
    DOI Scopus19 WoS5
    2021 Le, T. H. M., Croft, R., Hin, D., & Babar, M. A. (2021). A large-scale study of security vulnerability support on developer Q&A websites. In Proceedings of the Evaluation and Assessment in Software Engineering Conference (EASE 2021) (pp. 109-118). New York, United States: Association for Computing Machinery.
    DOI Scopus17 WoS6
    2020 Nguyen, T. V., Nguyen, N. T. H., Le, T., Nguyen, S. T. T., & Huynh, L. (2020). Estimation of Heat of Formation for Chemical Systems using the Lasso Regression-Based Approach. In ICSCA 2020: Proceedings of the 2020 9th International Conference on Software and Computer Applications (pp. 21-25). New York, NY, USA: ACM Digital Library.
    DOI
    2020 Le, T. H. M., Hin, D., Croft, R., & Babar, M. A. (2020). PUMiner: Mining security posts from developer question and answer websites with PU learning. In MSR '20: Proceedings of the 17th International Conference on Mining Software Repositories (MSR 2020) (pp. 350-361). New York, NY: ACM.
    DOI Scopus22 WoS11
    2019 Le, T. H. M., Sabir, B., & Babar, M. A. (2019). Automated software vulnerability assessment with concept drift. In IEEE International Working Conference on Mining Software Repositories Vol. 2019-May (pp. 371-382). online: IEEE.
    DOI Scopus45
    2018 Le, H. M. T., Tran, T. T., & Lam, K. H. (2018). Linear support vector machine to classify the vibrational modes for complex chemical systems. In Proceedings of the 2nd International Conference on Machine Learning and Soft Computing (ICMLSC 2018) (pp. 10-14). New York: Association for Computing Machinery.
    DOI WoS1
    2018 Chan, D. C. Y., Lee, Y. S., Bura, S., Arianoglou, M., Teoh, T. G., Collado, M. C., . . . Sykes, L. (2018). The vaginal microbiota and the adaptive immune system in pregnant and nonpregnant women. In BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY Vol. 125 (pp. E32). WILEY.
    2017 Rasheed, Z. B. M., Lee, Y. S., MacIntyre, D. A., Bennett, P. R., & Lynne, S. (2017). Activation of the TLR3 Receptor: A Possible Mechanism for Virally Induced Preterm Labour.. In REPRODUCTIVE SCIENCES Vol. 24 (pp. 110A). FL, Orlando: SAGE PUBLICATIONS INC.
    2017 Mitra, A., MacIntyre, D., Lai, J., Lee, Y., Smith, A., Marchesi, J., . . . Kyrgiou, M. (2017). The Impact of Excisional Treatment for Cervical Intraepithelial Neoplasia on the Vaginal Microbiota.. In REPRODUCTIVE SCIENCES Vol. 24 (pp. 89A). FL, Orlando: SAGE PUBLICATIONS INC.
    2016 Nguyen, H. S., Pham, H. P., Duong, T. H., Nguyen, T. P. T., & Le, H. M. T. (2016). Personalized facets for faceted search using wikipedia disambiguation and social network. In T. B. Nguyen, T. VanDo, H. A. LeThi, & N. T. Nguyen (Eds.), Advanced Computational Methods for Knowledge Engineering Vol. 453 (pp. 229-241). Berlin: SPRINGER.
    DOI Scopus2 WoS1
    2013 Nguyen, N. Q., Debreceni, T. L., Burgstad, C. M., Bellon, M., Wishart, J. M., Rayner, C., & Horowitz, M. (2013). Whey Protein Pre-Load Attenuates Post-Prandial Hyperglycemia and Slows Carbohydrate Absorption in Patients With Roux-en-Y Gastric Bypass. In GASTROENTEROLOGY Vol. 144 (pp. S268). W B SAUNDERS CO-ELSEVIER INC.
    2012 Nguyen, N. Q., Debreceni, T. L., Burgstad, C. M., Wishart, J. M., Bellon, M., Rayner, C., & Horowitz, M. (2012). Effects of Posture and Meal Volume on Pouch Emptying, Intestinal Transit, Blood Glucose, Gut Hormone Concentrations and Gastrointestinal Symptoms in Patients With Gastric Bypass. In GASTROENTEROLOGY Vol. 142 (pp. S560). CA, San Diego: W B SAUNDERS CO-ELSEVIER INC.

  • Preprint
    Year Citation
    2025 Ye, Z., Le, T. H. M., & Babar, M. A. (2025). LLMSecConfig: An LLM-Based Approach for Fixing Software Container
    Misconfigurations.
    2024 Le, T. H. M., Babar, M. A., & Thai, T. H. (2024). Software Vulnerability Prediction in Low-Resource Languages: An
    Empirical Study of CodeBERT and ChatGPT.
    2024 Le, T. H. M., Du, X., & Babar, M. A. (2024). Are Latent Vulnerabilities Hidden Gems for Software Vulnerability
    Prediction? An Empirical Study.
    2024 Zhang, B., Le, T. H. M., & Babar, M. A. (2024). MVD: A Multi-Lingual Software Vulnerability Detection Framework.
    2024 Arani, A. K., Le, T. H. M., Zahedi, M., & Babar, M. A. (2024). Systematic Literature Review on Application of Learning-based Approaches
    in Continuous Integration.
    2024 Le, T. H. M., & Babar, M. A. (2024). Automatic Data Labeling for Software Vulnerability Prediction Models:
    How Far Are We?.
    2024 Nguyen, A. T., Le, T. H. M., & Babar, M. A. (2024). Automated Code-centric Software Vulnerability Assessment: How Far Are
    We? An Empirical Study in C/C++.
    2024 Le, T. H. M., & Babar, M. A. (2024). Mitigating Data Imbalance for Software Vulnerability Assessment: Does
    Data Augmentation Help?.

I have won many competitive grants and fundings to support my research:

  • Royal Society's Catalyst Seeding Fund for the project "Automated Cybersecurity Assessment Platform as a Service". PIs: Dr. Mengmeng Ge, Prof. Ali Babar, Prof. Chelsea Liu, and myself

  • ACM SIGSOFT CAPS Support Grant for attending and presenting at ICSE/MSR 2022 (CORE A*)

  • ACM SIGAI Student Travel Support Grant for attending and presenting at ASE 2021 (CORE A*)
  • CREST's Travel Grant for attending and presenting at EASE 2021 (CORE A)
  • ECMS HDR Travelling Scholarship 2020 for attending and presenting at ICSE/MSR 2020 (CORE A*)
  • Travel Grant from the School of Computer Science at the University of Adelaide for attending and presenting at ICSE/MSR 2019 (CORE A*)

Teaching

  • Software Engineering Research Project (2022 - 2025 Semesters 1 and 2)
  • Secure Programming (2025 Semester 2, Trimester 2)
  • Algorithm Design and Data Structures (2024 Semester 2)
  • Software Architecture (2021 Semester 2)
  • Software Architecture (2020 Semester 2)
  • Software Process Improvement (2020 Semester 1)
  • Secure Software Engineering (2019 Semester 2)
  • Software Engineering Research Project (2019 Semester 2)

 

 

  • Current Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2025 Co-Supervisor Towards AI-Driven Security Enhancement for Infrastructure as Code Doctor of Philosophy Doctorate Full Time Mr Ziyang Ye
    2025 Co-Supervisor Soft Prompt Protection Against Adversrial Attack For Large Language Model Application Doctor of Philosophy Doctorate Full Time Mr Jinyang Li
    2024 Co-Supervisor Automated discovery and analysis of security-related technical debt Doctor of Philosophy Doctorate Full Time Mr The Anh Nguyen
    2023 Co-Supervisor Developing Cybersecurity Threat Detection and Prediction Framework using Natural Language Processing Doctor of Philosophy Doctorate Full Time Mr Mehdi Kholoosi
    2022 Co-Supervisor Exploring the Potential of Machine Learning Methods for Optimizing Software Delivery in DevOps Architecture Doctor of Philosophy Doctorate Full Time Mr Ali Kazemi Arani
  • Position: Lecturer
  • Phone: 83134425
  • Email: triet.h.le@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Four
  • Org Unit: Computer Science
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