Accepting applications from PhD students.
Email: Zhiwu.Huang@soton.ac.uk
Dr. Zhiwu Huang is a Lecturer (Assistant Professor) affiliated with the Vision, Learning, and Control (VLC) group in the School of Electronics and Computer Science (ECS) at the University of Southampton.
Dr. Zhiwu Huang specializes in computer vision and machine learning for artificial general intelligence. His current research focuses on generative AI (GenAI) functions of generation, detection, emotion, and action in computers, devices, and robots, with the potential for broad impact in healthcare, art, and education. His research team has been exploring computer vision and machine learning approaches like diffusion generative modeling, geometric deep learning, and continual deep learning. Ultimately, they aim to make machines more capable and controllable, enabling them to better understand both the physical world and human beings.
COMP6252: Deep Learning Technologies
COMP6237: Data Mining
AICE1006: Data Analytics
COMP6200: MSc Project
COMP3200: Part III Individual Project
ELEC1028: Personal Tutorial
IS424: Data Mining and Business Analytics, SMU Singapore
IS483: IS Application Project, SMU Singapore
Dr. Zhiwu Huang is a Lecturer (Assistant Professor) in the School of Electronics and Computer Science at the University of Southampton, where he has been serving since January 2023. Prior to joining Southampton, he held the position of Postdoctoral/Guest Researcher at ETH Zurich from September 2015 to July 2021. Following that, he served as an Assistant Professor of Computer Science at Singapore Management University from September 2021 to December 2022. Dr. Huang obtained his Ph.D. degree from the University of Chinese Academy of Sciences in 2015.
Dr Huang’s expertise lies in computer vision and machine learning for artificial general intelligence. His current research focuses on generative AI (GenAI) functions such as generation, detection, emotion, and action in computers, devices, and robots, with potential applications in healthcare, art, and education. His research team is exploring approaches like diffusion generative modeling, geometric deep learning, and continual deep learning. Ultimately, their goal is to make machines more capable and controllable, enabling them to better understand the physical world and human beings.
Dr. Huang is an accomplished researcher with numerous publications in top-tier conferences focused on computer vision, machine learning, and artificial intelligence. He is a member of IEEE and serves as an Associate Editor for IET Computer Vision. He is also actively involved in the academic community, contributing as a reviewer and meta-reviewer for major conferences and journals in these fields. He has played a key role in organizing multiple workshops in collaboration with prestigious conferences, including CVPR, ICCV, and ECCV.