About Me
I am a third-year Ph.D. student in Computer Science at the Australian Institute for Machine Learning (AIML), Adelaide University (formerly The University of Adelaide), advised by Prof. Javen Qinfeng Shi. I study representation learning, asking how natural language supervision determines which semantic structure is captured, preserved, or lost in vision-language models. My work combines theoretical analysis with controlled empirical study to understand contrastive learning, cross-modal alignment, and identifiability in representation learning, with the long-term goal of building more interpretable and reliable multimodal AI systems.
News
2026
We had three papers on representation learning accepted to ICML 2026.
May 01
I attended MLSS Melbourne 2026 and enjoyed learning from world-class speakers and connecting with the community.
Feb 11
Check out our new preprint: The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-Modal Divergence.
Jan 28
2025
I served as a guest lecturer in Statistical Machine Learning and presented recent advances in vision-language modeling. Slides.
Oct 15
2025
Our work On the Value of Cross-Modal Misalignment in Multimodal Representation Learning was selected as a Spotlight at NeurIPS 2025.
Sep 19
We released the preprint On the Value of Cross-Modal Misalignment in Multimodal Representation Learning.
Apr 14
2024
Our work CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts was accepted at ECCV 2024.
Jul 02
Previous news
Selected Publications (view all )
Honors & Awards
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NeurIPS Scholar Award2025
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Adelaide University Research Scholarships2023
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Award for Outstanding Graduates, Wuhan University of Technology2019