Wilson Silva is an Assistant Professor in the Departments of Information and Computing Sciences and Biology at Utrecht University, as well as a Guest AI Researcher in the Department of Radiology at the Netherlands Cancer Institute. His research focuses on trustworthy artificial intelligence for life sciences, with particular emphasis on explainable AI, privacy-preserving machine learning, and enhancing generalizability in cancer research.
Before moving to the Netherlands, Wilson completed his PhD at the University of Porto/INESC TEC, where he conducted research within the Visual Computing and Machine Intelligence group under the guidance of Prof. Jaime Cardoso. During his PhD, he also spent time as a visiting researcher in Prof. Mauricio Reyes’ lab at the University of Bern in Switzerland. Wilson holds a master’s degree in Electrical and Computer Engineering from the University of Porto.

TBA

Yongshuo Zong is a final-year PhD student at the University of Edinburgh where he works with Prof. Timothy Hospedales. His research focus on multimodal learning, especially large vision-language models, with an emphasis on areas such as safety, robustness, in-context learning, and multi-image understanding. He also works in the area of AI for healthcare where he develops MEDFAIR, one of the most popular benchmarks for medical imaging fairness.

Large language models (LLMs) have become integral to daily life, powering numerous applications. Building on the foundation of LLMs, large vision-language models (VLMs) have been developed to seamlessly integrate visual and textual data, enabling advanced multimodal interactions with humans. In this talk, I will first provide an overview of the background of large language models and multimodal learning. I will then introduce key research challenges in advancing LLMs and VLMs, focusing on topics such as in-context learning, multi-image understanding, and long-context processing. Finally, I will discuss the challenges of deploying large vision-language models safely, discussing potential alignment strategies to ensure reliability and ethical use. This talk aims to give the audience an overview of the foundations, advancements, and current challenges in vision-language models, highlighting the latest research driving this field forward.