Prof. Huang is actively working on efficient deep learning, dynamic neural networks, learning with limited data and reinforcement learning. His work on DenseNet won the Best Paper Award of CVPR (2017) and has collected more than 25,000 citations according to Google Scholar.

Dr. Sun is a theoretical neuroscientist also active in the deep learning community. Dr.Sun's work is centered around memory, in particular on how memories are dynamically consolidated for better generalisation. His work has been published in top tier journals, such as Nature and Nature Neuroscience,and it has had a strong impact on the related fields.

Prof. Tuytelaars' research focuses on dynamic neural networks, continual learning and representation learning for computer vision. As a recognized expert in this field, she has collected over 59,000 citations, received several awards and was Program Chair of ECCV'14 and CVPR'21, among other things.

Prof. Huang's research interest includes natural language processing, information retrieval, artificial intelligence and deep learning, including research on structural and reusable information inside large language models. She has published over 130 papers in major NLP, AI and IR conferences andjournals.

Dr. Locatello has published seminal papers in the fields of causal representationlearning, independent mechanisms, and slot attention, for which he has won several awards, including a best paper award at ICML and the ETH medal for outstanding doctoral dissertation. He has co-organized the 1st International Conference on Causal Learning and Reasoning (CLeaR).