Jing Yang

Jing Yang is a Research Associate at Core LAB and an Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge. Her research focuses on Computer Vision, particularly deep face analysis, model compression, and the intersection of 3D Computer Vision with generative models. She holds a PhD from the University of Nottingham under Prof. Georgios Tzimiropoulos.

Research Interests: Her work spans facial action unit detection, knowledge distillation techniques, 3D head reconstruction, and generative adversarial networks (GANs). Notable contributions include advancements in neural avatars, robust facial expression analysis, and compact representation learning for image retrieval.

Publications: Recent work includes high-impact publications in ICLR, IJCV, CVPR, and ECCV, focusing on generative models, facial recognition, and efficient neural network training. Examples include 'FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection' (WACV 2023) and 'Gaussian Head & Shoulders' (ICLR 2025).

Affiliations: Active in Core LAB (GenAI research) and affiliated with the University of Cambridge's Computer Science department. Engages in collaborative research with industry and academia, contributing to projects like the Cambridge Ring initiative.