Gia Bao Doan
School of Computer Science
Faculty of Sciences, Engineering and Technology
My research is about Trustworthy Machine Learning System, security aspect of Machine Learning and Deep Learning.
My research is about trustworthy and security of Machine Learning and Deep Learning systems.
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Appointments
Date Position Institution name 2022 - ongoing Postdoctoral Research Associate The University of Adelaide 2014 - 2018 Process and Equipment Engineer Intel Products Vietnam -
Language Competencies
Language Competency English Can read, write, speak, understand spoken and peer review Vietnamese Can read, write, speak, understand spoken and peer review -
Education
Date Institution name Country Title 2018 - 2022 University of Adelaide Australia Doctor of Philosophy 2012 - 2014 RMIT University Vietnam Vietnam Master of Engineerings 2007 - 2012 Danang University of Technology Vietnam Bachelor of Electronics and Communication Engineering -
Research Interests
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Journals
Year Citation 2022 Doan, B. G., Xue, M., Ma, S., Abbasnejad, E., & Ranasinghe, D. C. (2022). TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems. IEEE Transactions on Information Forensics and Security, 17, 3816-3830.
2021 Gao, Y., Kim, Y., Doan, B. G., Zhang, Z., Zhang, G., Nepal, S., . . . Kim, H. (2021). Design and Evaluation of a Multi-Domain TrojanDetection Method on Deep Neural Networks. IEEE Transactions on Dependable and Secure Computing, 19(4), 1-14.
WoS1 -
Conference Papers
Year Citation 2022 Yang, S., Doan, B. G., Montague, P., De Vel, O., Abraham, T., Camtepe, S., . . . Kanhere, S. S. (2022). Transferable Graph Backdoor Attack. In ACM International Conference Proceeding Series (pp. 321-332). ACM.
2020 Doan, B. G., Abbasnejad, M., & Ranasinghe, D. C. (2020). Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems. In Annual Computer Security Applications Conference, ACSAC 2020 (pp. 897-912). online: ACM.
Scopus28 WoS17
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