Summary
Bao Doan is a postdoctoral researcher specializing in the robustness, security, and privacy of deep neural networks and large language models, with nine years of experience spanning academia and industry. Currently at UNSW after a PhD in Trustworthy Machine Learning from the University of Adelaide, he investigates adversarial threats and practical defenses that make ML systems more reliable in real-world deployments. His background includes hands-on process and team leadership at Intel, equipping him with a systems-first mindset for translating research into operational improvements. Bao bridges ML-for-security and security-for-ML, exploring how models can both defend and be protected, and he publishes work that targets deployment risks rather than only theoretical gaps. Based in Adelaide, he combines rigorous academic training with manufacturing-grade problem solving and Lean Six Sigma experience, enabling pragmatic, measurable impact. Colleagues describe him as a researcher who balances deep technical rigor with practical engineering discipline.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Trustworthy Machine Learning, Doctor of Philosophy - PhD, Trustworthy Machine Learning at University of Adelaide
Master’s Degree, Electronic and Computer Engineering, Distinction, Master’s Degree, Electronic and Computer Engineering, Distinction at RMIT University Vietnam
Bachelor’s Degree, Electrical and Electronics Engineering, Bachelor’s Degree, Electrical and Electronics Engineering at Danang University of Science and Technology