About me

I am currently a PhD student at the University of Edinburgh, supervised by Prof. Timothy Hospedales and Dr. Yongxin Yang, where I am funded by UKRI CDT in Biomedical AI. I obtained my BSc in computer science from Tongji University, in 2021.

I am broadly interested in machine learning and its applications in biomedicine, especially with multi-modal learning and large vision-language models. Feel free to drop me an email for potential collaborations!

👉 I am actively looking for a research intern position this year. Shoot me an email if you think I am a good fit! (Flexible to anywhere/anytime)

Research Interests

  • Machine Learning: Multimodal Learning, Algorithmic Fairness, Self-supervised Learning.
  • AI4Healthcare: Computational Biology, Medical Imaging.


[05/2024] Both VLGuard and Fool your (V)LLMs are accepted to ICML’24!
[04/2024] Giving a talk about VLGuard at BMVA Trustworthy Multimodal Foundation Models Symposium!
[02/2024] C-VQA is accepted to CVPR’24!
[01/2024] Giving a talk about Fool your (V)LLMs at BMVA Vision-Language Symposium!
[11/2023] Invited talk about MEDFAIR at FAIMI workshop!
[02/2023] Meta-Omnium is accepted to CVPR’23!
[01/2023] MEDFAIR is accepted to ICLR’23 as spotlight!

Publications / Preprints

Check my Google scholar.

VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning.
Yongshuo Zong*, Ondrej Bohdal*, Timothy Hospedales.
arXiv 2024.

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy Hospedales.
ICML 2024.

Fool Your Large (Vision and) Language Model With Embarrassingly Simple Permutations.
Yongshuo Zong, Tingyang Yu, Bingchen Zhao, Ruchika Chavhan, Timothy Hospedales.
ICML 2024.

What If the TV Was Off? Examining Counterfactual Reasoning Abilities of Multi-modal Language Models.
Letian Zhang, Xiaotong Zhai, Zhongkai Zhao, Xin Wen, Yongshuo Zong, Bingchen Zhao.
CVPR 2024.

Self-Supervised Multimodal Learning: A Survey.
Yongshuo Zong, Oisin Mac Aodha, Timothy Hospedales.
arXiv 2023.

Meta Omnium: A Benchmark for General-Purpose Learning-to-learn.
Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy Hospedales.
CVPR 2023.

MEDFAIR: Benchmarking Fairness for Medical Imaging.
Yongshuo Zong, Yongxin Yang, Timothy Hospedales.
ICLR 2023 (Spotlight)

conST: an Interpretable Multi-modal Contrastive Learning Framework for Spatial Transcriptomics.
Yongshuo Zong, Tingyang Yu, Xuesong Wang, Yixuan Wang, Zhihang Hu, Yu Li.
preprint 2022.

scMinerva: a GCN-featured Interpretable Framework for Single-cell Multi-omics Integration with Random Walk on Heterogeneous Graph.
Tingyang Yu, Yongshuo Zong, Yixuan Wang, Xuesong Wang, Yu Li.
preprint 2022.