Tuan-Anh Bui
Machine Learning Researcher in Generative AI and Trustworthy Machine Learning

Me and two boys
I am Research Fellow at the Department of Data Science and AI, Monash University. My research interest lies in the intersection between Generative AI and Trustworthy Machine Learning. For example, my research focuses on how to ensure that models like ChatGPT do not respond to harmful queries asking to create a bomb, or that models like Stable Diffusion do not generate sexual images. I got my Ph.D. from Monash University in November 2023, under the supervision of Prof. Dinh Phung and Dr. Trung Le. My thesis can be found here.
Before that, I had one year working as Research Engineer at Credit AI Lab, Trusting Social, and two years working as Research Assistant at Singapore University of Technology and Design with Prof. Ngai Man Cheung and Dr. Trung Tran.
news
Mar 21, 2025 | It was a great pleasure for me to present our works about Unlearning Concepts to the Machine Learning team at Canva. The slides are available here. I’m glad to see many interesting and practical/industry-related questions from the audience and see how our research can be applied to their real-world problems. |
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Feb 28, 2025 | I’m excited to share that I am officially a Chief Investigator of the Trustworthy Generative AI: Towards Safe and Aligned Foundation Models project, funded by the Department of Defence, Australia with an $800K AUD grant. The project focuses on four key areas of modern foundation models: Certification - Alignment - Multimodality - Personalization, where I am leading the Personalization stream. Our goal is to push the boundaries of safe and aligned generative AI, ensuring its responsible deployment in real-world applications. The project is led by Professor Dinh Phung and co-led by a team of experts from the Faculty of IT, Monash University, where I am honored to be part of. |
Feb 27, 2025 |
I’m excited to share that our paper “Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation” (led by Long Vuong) has been accepted to CVPR 2025! ![]() ![]() ![]() |
Jan 23, 2025 |
Hooray! I’m thrilled to finally share that our work has been accepted to ICLR 2025! This is more than just an acceptance—I’m truly proud that all reviewers recognized and appreciated the originality and creativity of our approach to concept unlearning, with a clear motivation and comprehensive experiments. The paper can be found here ![]() ![]() ![]() |
Oct 4, 2024 |
Excited to share another paper that I am very proud of. This paper is an extension of our NeurIPS 2024 paper, where we dive deeper into the impact of erasing one concept to the others, but this time, we focus on the choice of target concepts. The paper can be found here. Our paper’s name was inspired by the movie “Fantastic Beasts and Where to Find Them”. Hopefully, the reviewers enjoy it as much as the movie ![]() |
latest posts
Mar 15, 2025 | MS-Diffusion - Multi-subject Zero-shot Image Personalization with Layout Guidance (ICLR 2025) |
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Mar 14, 2025 | Unlearning LLMs |
Mar 8, 2025 | Foundation of Diffusion Models |