Projects per year
Personal profile
Biography
Dr Xiaoning Du received her Ph.D. from Nanyang Technological University in 2020 and her bachelor’s degree from Fudan University in 2014. Her research is mainly focused on the security and quality assurance of both traditional software and intelligent software with learning-based components, which covers but is not limited to software testing, program analysis, vulnerability detection, and runtime verification. Currently, she's quite interested in the DevOps of AI software systems, which aims to regulate the development and assessment process of AI-assisted solutions, support their post-deployment operation and guarantee trustworthy and sustainable AI services. Please check Xiaoning's personal webpage for more details.
Dr Du is looking for self-motivated Ph.D. students with strong programming skills and relevant research experience. The position is sponsored by full scholarships. Please drop an email with your CV if you are interested. For Monash undergraduate and master students who wish to do honours or minor thesis with her, please check the available projects and send a copy of your transcript when expressing interest.
Monash teaching commitment
Xiaoning has experience as the Lecturer for the following units in the Faculty of IT:
- FIT5003 Software security
- FIT4002 Software engineering industry experience studio project
Education/Academic qualification
Computer Science, PhD, Nanyang Technological University (NTU)
3 Aug 2015 → 29 Feb 2020
Software Engineering, Bachelor, Fudan University
1 Sept 2010 → 30 Jun 2014
Research area keywords
- Sotware Engineering
- Artificial intelligence
- Software Security
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 3 Active
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CSIRO Next Generation Graduates Program: Building National Cybersecurity Capabilities for Digital Transformation in Manufacturing
Xiang, Y., Georgakopoulos, D., Grundy, J., Du, X., Chen, C., Ma, S., Ruan, D., Zhang, J., Eisenbart, B., Jayaraman, P. P., Wen, S. & Li, L.
CSIRO - Commonwealth Scientific and Industrial Research Organisation
3/07/23 → 31/12/27
Project: Research
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CSIRO Next Generation Graduates Program: Privacy-Preserving Machine Learning: Technology Development and Adoption
Yuan, X., Liu, J., Ge, Z., Haffari, R., Yang, R., Yi, X., Sakzad, A., Fang, Y., Cui, S., Baiao Dowsley, R., Du, X., Salehi, M., Han, F., Wakefield, R., Abuadbba, S., Wu, T. & Liu, X.
1/01/23 → 31/12/27
Project: Research
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Algorand Centre of Excellence (ACE) on Sustainability Informatics for the Pacific
Liu, J., Rudolph, C., Pink, S., Yu, J., Gasevic, D., Steinfeld, R., Du, X., Liebman, A., Ma, X., Luebbers, J., Ince, P. D., Sakzad, A., Yuan, X., Baiao Dowsley, R., He, W., Ko, R. K. L., Dong, N., Kuchta, V., Komarek, A. M., Radke, A., Carvalho, G., Risius, M., Dargusch, P. J., Gramoli, V., Salampasis, D., Wang, Z., Au, M. H., Luo, X., Ali, S., Sharma, B., Boorman, J., Wainwright, T., Esgin, M., Cui, S. & Cui, H.
1/08/22 → 31/07/27
Project: Research
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DeepStellar: model-based quantitative analysis of stateful Deep Learning systems
Du, X., Xie, X., Li, Y., Ma, L., Liu, Y. & Zhao, J., 2019, ESEC/FSE'19 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Dumas, M., Pfahl, D., Apel, S. & Russo, A. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 477-487 11 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
123 Citations (Scopus) -
MARBLE: model-based robustness analysis of stateful deep learning systems
Du, X., Li, Y., Xie, X., Ma, L., Liu, Y. & Zhao, J., 2020, Proceedings - 2020 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020. Le Goues, C. & Lo, D. (eds.). New York NY USA: IEEE, Institute of Electrical and Electronics Engineers, p. 423-435 13 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
12 Citations (Scopus) -
Devign: effective vulnerability identification by learning comprehensive program semantics via graph neural networks
Zhou, Y., Liu, S., Siow, J., Du, X. & Liu, Y., 2019, NIPS Proceedings - Advances in Neural Information Processing Systems 32 (NIPS 2019). Wallach, H., Larochelle, H., Beygelzimer, A., d'AlcheBuc, F., Fox, E. & Garnett, R. (eds.). San Diego CA USA: Neural Information Processing Systems (NIPS), Vol. 32. 11 p. (Advances in Neural Information Processing Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile484 Citations (Scopus) -
LEOPARD: identifying vulnerable code for vulnerability assessment through program metrics
Du, X., Chen, B., Li, Y., Guo, J., Zhou, Y., Liu, Y. & Jiang, Y., 2019, 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE 2019). Bultan, T. & Whittle, J. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 60-71 12 p. (Proceedings - International Conference on Software Engineering; vol. 2019-May).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
81 Citations (Scopus) -
Towards characterizing adversarial defects of deep learning software from the lens of uncertainty
Zhang, X., Xie, X., Ma, L., Du, X., Hu, Q., Liu, Y., Zhao, J. & Sun, M., 2020, Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering, ICSE 2020. Cleland-Huang, J. & Marinov, D. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 739-751 13 p. (Proceedings - International Conference on Software Engineering).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
51 Citations (Scopus)