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.

News

[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.

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

Fool Your Large (Vision and) Language Model With Embarrassingly Simple Permutations.
[paper][code]
Yongshuo Zong, Tingyang Yu, Bingchen Zhao, Ruchika Chavhan, Timothy Hospedales.
arXiv 2023.

What If the TV Was Off? Examining Counterfactual Reasoning Abilities of Multi-modal Language Models. [paper][code]
Letian Zhang, Xiaotong Zhai, Zhongkai Zhao, Xin Wen, Yongshuo Zong, Bingchen Zhao.
arXiv 2023.

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

Meta Omnium: A Benchmark for General-Purpose Learning-to-learn. [website][paper][code]
Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy Hospedales.
Computer Vision and Pattern Recognition (CVPR 2023)

MEDFAIR: Benchmarking Fairness for Medical Imaging. [paper][code][website][docs]
Yongshuo Zong, Yongxin Yang, Timothy Hospedales.
International Conference on Learning Representations (ICLR 2023 Spotlight)

conST: an Interpretable Multi-modal Contrastive Learning Framework for Spatial Transcriptomics. [paper][code]
Yongshuo Zong, Tingyang Yu, Xuesong Wang, Yixuan Wang, Zhihang Hu, Yu Li.
Biorxiv (2022).

scMinerva: a GCN-featured Interpretable Framework for Single-cell Multi-omics Integration with Random Walk on Heterogeneous Graph. [paper][code]
Tingyang Yu, Yongshuo Zong, Yixuan Wang, Xuesong Wang, Yu Li.
Biorxiv (2022).