Publications & Presentations

My current research interest focuses on developing Machine Learning and Deep Learning for analyzing and assessing security vulnerabilities in software systems.

You can find the latest updates about my research on Google Scholar, Research Gate, and GitHub.


PUBLICATIONS

Theses

Ph.D. thesis. T. H. M. Le, "Towards an Improved Understanding of Software Vulnerability Assessment Using Data-Driven Approaches," The University of Adelaide, 2022.


Journal Articles

J5. T. H. M. Le, H. Chen, and M. A. Babar, "A Survey on Data-driven Vulnerability Assessment and Prioritization," accepted for publication in ACM Comput. Surv., 2022. [SCI indexed, SJI rating: Q1, Impact factor: 10.28]. Pre-print. The online and up-to-date version of the survey can be found here.


J4. T. H. M. Le, H. Chen, and M. A. Babar, "Deep Learning for Source Code Modeling and Generation: Models, Applications, and Challenges," ACM Comput. Surv., vol. 53, p. Article 62, 2020. [SCI indexed, SJI rating: Q1, Impact factor: 10.28]. Pre-print.


J3. T. H. M. Le, T. T. Tran, and L. K. Huynh, "Identification of Hindered Internal Rotational Mode for Complex Chemical Species: A Data Mining Approach with Multivariate Logistic Regression Model," Chemometrics and Intelligent Laboratory Systems, vol. 172, pp. 10–16, 2018. [SCI indexed, Impact factor: 3.491].


J2. T. H. M. Le, S. T. Do, and L. K. Huynh, "Algorithm for Auto-Generation of Hindered Internal Rotation Parameters for Complex Chemical Systems," Computational and Theoretical Chemistry, vol. 1100, pp. 61-69, 2017. [SCI-indexed, Impact factor: 1.926]


J1. T. H. M. Le and T. H. Duong, "Online Collaborative Video Annotation Framework using GoodRelations Ontology for E-commerce," International Journal of Advanced Computer Research, vol. 7, pp. 121-135, 2017.



Conference Papers

C11. T. H. M. Le, Xiaoning Du, and M. A. Babar, "Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study," The IEEE/ACM 21st International Conference on Mining Software Repositories (MSR), 2024. [CORE A, Acceptance rate: 29%]. Pre-print. Code.


C10. A. K. Arani, M. Zahedi, T. H. M. Le, M. A. Babar, "SoK: Machine Learning for Continuous Integration," The Workshop on Cloud Intelligence / AIOps, co-located with The International Conference on Software Engineering (ICSE), 2023. Pre-print.


C9. T. H. M. Le and M. A. Babar, "On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models," The IEEE/ACM 19th International Conference on Mining Software Repositories (MSR), 2022. [CORE A, Acceptance rate: 34%]. Pre-print. Code.


C8. X. Duan, M. Ge, T. H. M. Le, F. Ullah, S. Gao, X. Lu and M. A. Babar, "Automated Security Assessment for the Internet of Things," The 26th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC), 2021, pp. 47-56. Pre-print. Code.


C7. T. H. M. Le, D. Hin, R. Croft and M. A. Babar, "DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning,"  The 36th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2021, pp. 717-729. [CORE A*, Acceptance rate: 19%]. Pre-print. Video. Code.


C6. T. H. M. Le, R. Croft, D. Hin and M. A. Babar, "A Large-scale Study of Security Vulnerability Support on Developer Q&A Websites," The 25th International Conference on Evaluation and Assessment in Software Engineering (EASE), 2021, pp. 109-118. [CORE A, Acceptance rate: 27%]. Pre-print. Video. Code.


C5. T. H. M. Le, D. Hin, R. Croft and M. A. Babar, "PUMiner: Mining Security Posts from Developer Question and Answer Websites with PU Learning," The IEEE/ACM 17th International Conference on Mining Software Repositories (MSR), 2020, pp. 350–361. [CORE A, Acceptance rate: 25.7%]. Pre-print. Video. Code.


C4. T. H. M. Le, B. Sabir, and M. A. Babar, "Automated Software Vulnerability Assessment with Concept Drift," The IEEE/ACM 16th International Conference on Mining Software Repositories (MSR), 2019, pp. 371–382. [CORE A, Acceptance rate: 25%]. Pre-print. Code.


C3. T. H. M. Le, T. T. Tran, and L. K. Huynh, "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, 2018, pp. 10-14. [Best Paper Award]


C2. T. H. M. Le, S. T. Do, and L. K. Huynh, "MSMC-GUI - An Automatic Setup Tool for Hindered Internal Rotation Treatment for Ab Initio Thermodynamic Property Calculations," in Proceedings of The 5th World Conference on Applied Sciences, Engineering and Technology, HCMC, 2016, pp. 239-243.


C1. H. S. Nguyen, H. P. Pham, T. H. Duong, T. P. T. Nguyen, and T. H. M. Le, "Personalized Facets for Faceted Search Using Wikipedia Disambiguation and Social Network," in Proceedings of Advanced Computational Methods for Knowledge Engineering, ed: Springer, 2016, pp. 229-241.


PRESENTATIONS


Invited Talks

I4. "Data-Driven Support for Software Vulnerability Assessment & Prioritisation" at the InSecLab at the University of Information Technology, Vietnam, January 2024.


I3. "Data-driven Software Vulnerability Prediction" at Australian Institute for Machine Learning (AIML), September 2023.


I2. "Data-driven Support for Software Vulnerability Assessment and Prioritisation" in CREST Software Security Symposium at the University of Adelaide, September 2022. Video.


I1. "DeepCVA: Automated Commit-level Software Vulnerability with Deep Multi-task Learning" in Dr. Suranga Seneviratne's group at the University of Sydney, May 2022.



Poster Presentations

P6. T. H. M. Le, B. Sabir, and M. Ali Babar, "Text-based Predictive Analytics of Software Vulnerabilities in Public Databases," Australasian Lab for Cyber Security Ideas, 2018. Poster [Best Poster Presentation Award  - 3rd Prize]


P5. T. H. M. Le, C. H. Dam, L. T. Pham, and Lam K. Huynh, "A Reaction-based Ensemble Machine Learning Method to Determine the Heat of Formation for Chemical Systems," Asian Consortium on Computational Materials Science, 2018. Poster


P4. T. H. M. Le and Lam K. Huynh, "A Reaction-based Similarity Refinement Approach to Estimate the Heat of Formation for Chemical Systems," Asian Consortium on Computational Materials Science, 2018. Poster


P3. T. H. M. Le and Lam K. Huynh, "MSMC-GUI: An Interactive Tool for Thermodynamic and Kinetic Data Mining for Complex Chemical Systems," The 1st Taiwan-Thailand-Vietnam Workshop on Theoretical and Computational Chemistry, 2018. Poster [Best Poster Presentation Award]


P2. T. H. M. Le, T. T. Tran, and L. K. Huynh, "A Data Mining Approach to Determine the Hindered Internal Rotational Frequency for Chemical Species," The 21st International Annual Symposium on Computational Science and Engineering, Thailand, August 2017. Poster. [Best Poster Presentation Award]


P1. T. H. M. Le, S. T. Do, and L. K. Huynh, "MSMC-GUI: An Interactive Tool for Data Munging and Analysis for Chemical System," The Third International Conference on Computational Science and Engineering, HCMC, 2016, p. 67. Poster