Xiaoning Du

Faculty of Information Technology, Monash University, Australia

Room 214, 20 Exhibition Walk

Clayton VIC 3800 Australia

I am a lecturer (a.k.a. Assistant Professor) at the Department of Software Systems and Cybersecurity of the Faculty of Information Technology, Monash University.

I obtained my Bachelor of Software Engineering degree from Fudan University in 2014, and I did my Ph.D. at Nanyang Technological University from 2015 to 2020, under the supervision of Prof. Yang Liu. Prior to joining Monash, I worked as a postdoc research fellow at Nanyang Technological University, under the supervision of Prof. Yi Li.

My 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, I am 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 my publication list for more details.

I am looking for self-motivated Ph.D. students with strong programming skills and relevant research experience. The position is sponsored by full scholarships. Please send me an email with your CV if you are interested. For Monash undergraduate and master students who wish to do honours or minor thesis with me, please check the available projects and send me a copy of your transcript when expressing interest.

news

Sep 2, 2022 Our paper “FuzzJIT: Towards Fuzzing JavaScript Engine JIT Compiler” is accepted to USENIX Security’23!
Jun 23, 2022 I will serve on the Program Committee of FSE’23 research track. Welcome submissions!
Jun 8, 2022 I received the 2022 FIT ECR Seed Grant! :moneybag: :v:
May 11, 2022 Our paper ICSE’22 paper “On the Importance of Building High-quality Training Datasets for Neural Code Search” received ACM SIGSOFT distinguished paper award nomination (19/197)!
Jan 14, 2022 Our paper “CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning” is accepted to WWW’22!
Dec 3, 2021 Our paper “On the Importance of Building High-quality Training Datasets for Neural Code Search” is accepted to ICSE’22!
Oct 25, 2021 Our paper “CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning” is online at arXiv! :bell:
Oct 8, 2021 I was invited to be a Co-Chair of the SCORE contest in ICSE’23! Register your team and win a travel to Melbourne!
Aug 30, 2021 I received the 2021 FIT ECR Seed Grant! :moneybag: :ok_woman:
Feb 15, 2021 I joined the Faculty of Information Technology at Monash University as a lecturer! :smile:

selected publications

  1. FuzzJIT: Towards Fuzzing JavaScript Engine JIT Compiler
    Junjie Wang, Zhiyi Zhang, Shuang Liu, Xiaoning Du, and Junjie Chen
    The 32nd USENIX Security Symposium (USENIX Security ’23) 2023
  2. CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning
    Zhensun Sun, Xiaoning Du, Fu Song, Mingze Ni, and Li Li
    The ACM Web Conference 2022 (WWW) 2022
  3. On the Importance of Building High-quality Training Datasets for Neural Code Search
    Zhensu Sun, Li Li, Yan Liu, Xiaoning Du, and Li Li
    44th International Conference on Software Engineering (ICSE) 2022
  4. Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks
    Xiyue Zhang, Xiaoning Du, Xiaofei Xie, Lei Ma, Yang Liu, and Meng Sun
    35th AAAI Conference on Artificial Intelligence 2021
  5. Who is real bob? adversarial attacks on speaker recognition systems
    Guangke Chen, Sen Chen, Lingling Fan, Xiaoning Du, Zhe Zhao, Fu Song, and Yang Liu
    42nd IEEE Symposium on Security and Privacy (SP) 2021
  6. Towards characterizing adversarial defects of deep learning software from the lens of uncertainty
    Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, and Meng Sun
    42nd IEEE/ACM International Conference on Software Engineering (ICSE) 2020
  7. Marble: Model-based robustness analysis of stateful deep learning systems
    Xiaoning Du, Yi Li, Xiaofei Xie, Lei Ma, Yang Liu, and Jianjun Zhao
    35th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2020
  8. DeepStellar: model-based quantitative analysis of stateful deep learning systems
    Xiaoning Du, Xiaofei Xie, Yi Li, Lei Ma, Yang Liu, and Jianjun Zhao
    27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE) 2019
  9. Devign: effective vulnerability identification by learning comprehensive program semantics via graph neural networks
    Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu
    Advances in Neural Information Processing Systems (NeurIPS) 2019
  10. Leopard: Identifying vulnerable code for vulnerability assessment through program metrics
    Xiaoning Du, Bihuan Chen, Yuekang Li, Jianmin Guo, Yaqin Zhou, Yang Liu, and Yu Jiang
    41st IEEE/ACM International Conference on Software Engineering (ICSE) 2019
  11. Trace-Length Independent Runtime Monitoring of Quantitative Policies
    Xiaoning Du, Alwen Tiu, Kun Cheng, and Yang Liu
    IEEE Transactions on Dependable and Secure Computing (TDSC) (IF 6.404) 2019