I am a Postdoctoral Research Fellow at the University of Adelaide, focusing on the Robustness of deep neural networks. 

My work is supervised by Associate Professor Damith Ranasinghe and Associate Professor Ehsan Abbasnejad. It involves collaboration with key stakeholders from the University of New South Wales, Data61 (CSIRO), and the Defence Science and Technology Group (DSTG), Australia.

Before joining the University of Adelaide, I spent nearly four years at Intel Vietnam, holding various roles. 

I began as a Manufacturing Supervisor, leading a medium team of direct reports, and later advanced to the position of Senior Process and Equipment Engineer. 

For a more detailed overview of my professional experience, please refer to my CV.

• Feb 2025 - I will serve as a Program Committee for NeurIPS (CORE Rank: A*) conference.

• Jan 2025 - I will serve as a Program Committee for ICML (CORE Rank: A*) conference.

• Dec 2024 - AAAI'25 - Our paper titled Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks is accepted to the AAAI (CORE Rank: A*) conference in 2025. 

• Dec 2024 - ACSAC'2024 - Hawaii (USA) - I attended and presented our paper titled On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World

• Sep 2024 - ESORICS'2024 - Bydgoszcz (Poland) - I attended and presented our paper titled Bayesian Learned Models Can Detect Adversarial Malware For Free.

• 2024 - I served as a Program Committee for NeurIPS-2024, ICML-2024, ICLR-2024, ECCV-2024  and AAAI-2024 conferences.

• 2023 - I served as a Program Committee for NeurIPS-2023, ICCV-2023, AAAI-2023 conferences.

• 2022 - I served as a Program Committee for ICML-2022, ECCV-2022, CVPR-2022 conferences.

• Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks
  BG Doan, A Shamsi, XY Guo, A Mohammadi, H Alinejad-Rokny, ...
  AAAI Conference on Artificial Intelligence (AAAI-25, Rank A*), 2025.

• Bayesian Learned Models Can Detect Adversarial Malware For Free
  BG Doan, DQ Nguyen, P Montague, T Abraham, O De Vel, S Camtepe, ...
  European Symposium on Research in Computer Security (ESORICS, Rank A), 2024.

• On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World
  BG Doan, DQ Nguyen, C Lindquist, P Montague, T Abraham, O De Vel, ...
  Annual Computer Security Applications Conference (ACSAC, Rank A), 2024.

• Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness
  BG Doan, S Yang, P Montague, O De Vel, T Abraham, S Camtepe, ...
  AAAI Conference on Artificial Intelligence (AAAI-23, Rank A*), 2023.

• TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems
  BG Doan, M Xue, S Ma, E Abbasnejad, DC Ranasinghe
  IEEE Transactions on Information Forensics and Security (TIFS, Q1), 2022.

• Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense
  BG Doan, EM Abbasnejad, JQ Shi, DC Ranasinghe
  International Conference on Machine Learning (ICML, Rank A*), 5309-5323, 2022.

• Februus: Input purification defense against trojan attacks on deep neural network systems
  BG Doan, E Abbasnejad, DC Ranasinghe
  Annual Computer Security Applications Conference (ACSAC - Rank: A) 2020, 897-912, 2020.

• Transferable Graph Backdoor Attack
  S Yang, BG Doan, P Montague, O De Vel, T Abraham, S Camtepe, ...
  Int. Symp. on Research in Attacks, Intrusions and Defenses (RAID, Rank A), 2022.

• Backdoor attacks and countermeasures on deep learning: A comprehensive review
  Y Gao, BG Doan, Z Zhang, S Ma, J Zhang, A Fu, S Nepal, H Kim
  arXiv preprint arXiv:2007.10760

• Design and evaluation of a multi-domain Trojan detection method on deep neural networks
  Y Gao, Y Kim, BG Doan, Z Zhang, G Zhang, S Nepal, DC Ranasinghe, ...
  IEEE Transactions on Dependable and Secure Computing (TDSC, Q1), 2021.

• Towards Robust Deep Neural Networks
  GB Doan
  University of Adelaide, 2022.