Xiaojuan QI

Professor Xiaojuan QI is an Associate Professor in the Department of Electrical and Computer Engineering at The University of Hong Kong. Her research interests include 3D Vision, Deep Learning, Artificial Intelligence, and AI for Science and Medicine. Prior to joining HKU, she was a Postdoctoral Researcher at the University of Oxford, UK. She received her Ph.D. from the Chinese University of Hong Kong (CUHK) in 2018 and her B.Eng. degree from Shanghai Jiao Tong University (SJTU) in 2014. She has also conducted research and academic exchanges at the University of Toronto and Intel Intelligent Systems Lab. Prof. Qi has authored over 100 peer-reviewed papers in leading venues across computer vision, computer graphics, and machine learning, including SIGGRAPH Asia, CVPR, ICCV, and NeurIPS. Her research aims to endow machines with the ability to perceive, understand, and reconstruct the visual world.

Xiaojuan Qi is an Associate Professor at The University of Hong Kong, specializing in 3D Vision, Deep learning, Artificial Intelligence, and Medical Image Analysis. Her research focuses on advancing deep learning techniques for medical image segmentation, particularly in liver and tumor detection from CT volumes. She has contributed to benchmark datasets like the Liver Tumor Segmentation (LiTS) challenge and developed hybrid architectures such as H-DenseUNet for improved accuracy. Her work also extends to 3D point cloud segmentation, real-time semantic segmentation, and generative models for image manipulation and fake face detection. Qi's research emphasizes the integration of geometric and semantic understanding in AI-driven vision tasks.