Guanglin Zhou

I am a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science and the Queensland Digital Health Centre at The University of Queensland, where I work with Sebastiano Barbieri. From February 2021 to August 2024, I completed my Ph.D at the School of Computer Science and Engineering at UNSW Sydney under the supervision of Lina Yao and Liming Zhu, and received the 2024 Dean's Award for Outstanding PhD Theses. From May to December 2023, I joined the Center for Artificial Intelligence Research, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE, as a research intern, collaborating closely with Kun Zhang and Salman Khan.

Email / GitHub / Google Scholar / LinkedIn

Research

My research explores causality and foundation models, with a focus on addressing real-world challenges such as distributional robustness and the applications in healthcare. I am currently focusing on developing generative medical event models using Integrated electronic medical records (ieMR) data from Queensland Health.

(*: Co-First Author; #: Corresponding Author.)

From Small to Large: In-Context Learning as a New Paradigm for Domain Generalization

Guanglin Zhou^*^#, Zhongyi Han^*, Shaoan Xie^*, Shiming Chen, Biwei Huang, Liming Zhu, Xin Gao, Lina Yao, Salman Khan

International Journal of Computer Vision (IJCV), 2025

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Generating clinically realistic EHR data via a hierarchy- and semantics-guided transformer

Guanglin Zhou^#, Sebastiano Barbieri

28th European Conference on Artificial Intelligence (ECAI), 2025 (Oral Presentation)

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HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization

Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang

IEEE Transactions on Multimedia (TMM), 2024

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How Well Does GPT-4V (ision) Adapt to Distribution Shifts? A Preliminary Investigation

Zhongyi Han^*, Guanglin Zhou^*, Rundong He^*, Jindong Wang, Tailin Wu, Yilong Yin, Salman Khan, Lina Yao, Tongliang Liu, Kun Zhang

ICLR 2024 ME-FoMo Workshop, 2024

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Meta-learning for Estimating Multiple Treatment Effects with Imbalance

Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu

International Conference on Web Information Systems Engineering (WISE), 2023

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Contrastive counterfactual learning for causality-aware interpretable recommender systems

Guanglin Zhou, Chengkai Huang, Xiaocong Chen, Xiwei Xu, Chen Wang, Liming Zhu, Lina Yao

32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023 (Oral Presentation)

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Emerging synergies in causality and deep generative models: A survey

Guanglin Zhou, Shaoan Xie, Guangyuan Hao, Shiming Chen, Biwei Huang, Xiwei Xu, Chen Wang, Liming Zhu, Lina Yao, Kun Zhang

arXiv, 2023

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Cycle-balanced representation learning for counterfactual inference

Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu

2022 SIAM International Conference on Data Mining (SDM), 2022 (Oral Presentation)

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Miscellanea

I enjoy swimming in the ocean. Coogee is my favorite, and I had a great time there.

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