Triet Le

Triet Le

Higher Degree by Research Candidate

School of Computer Science

Faculty of Sciences, Engineering and Technology

I am currently a PhD student in Computer Science at The University of Adelaide, Australia. I obtained my first-class honours bachelor degree in Computer Science with a GPA of 95.6/100 and graduated as a valedictorian from the International University – Vietnam National University, Ho Chi Minh City. My research interests include but are not limited to data mining and machine learning as well as their interdisciplinary applications. In my undergraduate study, I utilized machine learning and data mining techniques to predict some challenging chemical properties. I published 10 papers including 2 SCI-indexed journal articles and won 4-time best conference paper awards. My PhD will expand my research works to investigate how machine learning can perform predictive analytics in various domains of software engineering and cybersecurity.

I am investigating the applications of machine learning and deep learning methods for the prediction of software vulnerabilities in public databases such as Common Vulnerabilities and Exposures as well as National Vulnerability Database. I plan to identify the essential features that can effectively represent the software vulnerabilities. Moreover, I want to build a robust predictive analytics framework to support the security experts to resolve the vulnerabilities with priority.

  • Journals

    Year Citation
    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 Scopus11 WoS10
    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 Scopus41 WoS39
    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 Scopus37 WoS35
    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.
    Le, T. H. M., Chen, H., & Babar, M. A. (n.d.). A Survey on Data-driven Software Vulnerability Assessment and Prioritization. ACM Computing Surveys.
    Le, T. H. M., & Babar, M. A. (n.d.). On the Use of Fine-grained Vulnerable Code Statements for Software
    Vulnerability Assessment Models.
  • Conference Papers

    Year Citation
    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.
    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.
    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 ACM International Conference Proceeding Series (pp. 109-118). New York, United States: Association for Computing Machinery.
    DOI Scopus4 WoS3
    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 ACM International Conference Proceeding Series (pp. 21-25). ACM.
    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 Scopus8
    2019 Le, T., Sabir, B., & Babar, M. (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 Scopus15
    2018 Le, H. 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
    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.), Advances in Intelligent Systems and Computing Vol. 453 (pp. 229-241). Vienna, AUSTRIA: SPRINGER-VERLAG BERLIN.
    DOI Scopus1

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