معرفی
Dr. Yang Long is an Associate Professor in the Department of Computer Science at Durham University. He holds dual roles as an MRC Innovation Fellow and IEEE Senior Member (SMIEEE), specializing in scalable AI solutions for healthcare and interdisciplinary applications. His research focuses on Computer Vision, Machine Learning, and their integration with fields like physical activity analysis, mental health, design, education, and security.
Dr. Long earned his PhD in 2017 from the University of Sheffield, where his work laid the foundation for his current research in Zero-Shot Learning and generative models. His academic journey includes postgraduate studies and contributions to top-tier conferences/journals such as IEEE TPAMI, CVPR, and ACM MM.
Research Interests:
- Development of interpretable AI systems
- Zero-Shot Learning for unseen class recognition
- Healthcare AI applications (e.g., medical image segmentation, wearable sensor data analysis)
- Generative models including VAEs, GANs, and neural radiance fields
- Optimization of visual-semantic feature consistency
- Efficient architecture design for multimedia processing
Recent Work Trends: His articles emphasize interdisciplinary AI innovations, particularly in medical imaging and dynamic scene understanding. Notable focuses include generative models for 3D reconstruction (Neural Radiance Fields), causal inference for action recognition, and scalable solutions for imbalanced datasets in healthcare.
- MRC Innovation Fellow
- IEEE Senior Member (SMIEEE)
Advising & Grants: Supervises 17 postgraduate students, including PHD candidates like Yara Jubran. His MRC fellowship supports healthcare AI projects, while IEEE membership enables collaborative research in multimedia and computer vision.
Labs & Teams: Collaborates with interdisciplinary teams across Durham University's healthcare, engineering, and computer science domains, though specific lab affiliations are not explicitly detailed in the provided text.
