I received my PhD in Data Science and AI from Monash University and subsequently continued there as a Postdoctoral Researcher. 

My research focuses on improving the generalization and robustness of deep neural networks by developing optimization algorithms that mitigate overfitting and enhance model reliability across optimization, data distribution, and ensemble learning.      

I am currently extending this research to Large Language Models and Diffusion Models, with a particular focus on efficient fine-tuning and test-time adjustment. 

I am especially interested in personalized generative AI, where foundation models are adapted to specific users, tasks, and custom concepts while maintaining fidelity, controllability, robustness, and safety.