Rate My Professor Ying Weng

Ying Weng is Professor in Computer Science and Computer Science Course Director in the School of Computer Science at the University of Nottingham Ningbo China. She received her PhD in Signal and Information Processing from the Chinese Academy of Sciences in Beijing, China, in 2005. Her career trajectory includes serving as Assistant Professor at Bangor University in the UK from 2011, conducting postdoctoral research at Imperial College London, working on international standardisation projects at the British Broadcasting Corporation in London, participating in the European Framework Programme-6 project coordinated by the Fraunhofer Institute in Germany, and contributing to China's Major State Research Development Programme 973 project at the Chinese Academy of Sciences in Beijing.

Professor Weng's research specializations include AI and Machine Learning, Big Data in Image and Video Processing, Computer Vision, Brain Machine Interface, IoT and QoS in Wireless Networks, and Multimedia Forensics. She holds the status of Fellow of the Higher Education Academy (FHEA). With over 55 research outputs—comprising 26 journal articles, 22 conference contributions, 5 review articles, and 1 book chapter—her scholarly impact is evidenced by more than 1000 citations and an h-index of 17 on Scopus across 53 documents. Notable publications encompass "Applications of machine learning for computer-aided diagnosis of Parkinson’s disease: progress and benchmark case study" in Artificial Intelligence Review (2025), "Fractional Tensor Recurrent Unit (fTRU): A Stable Forecasting Model with Long Memory" in IEEE Transactions on Neural Networks and Learning Systems (2025), "Distribution-Based Masked Medical Vision-Language Model Using Structured Reports" in Interpretability of Machine Intelligence in Medical Image Computing proceedings (2026), "A Computer Vision System for Automatic Edge Detection of Magnetic Grain Profile" in Computer Vision – ECCV 2024 Workshops proceedings (2025), and "Machine Learning based Breast Cancer Prognosis Analysis on Multi-Source Big Data" at the 2025 International Conference on Big Data and Artificial Intelligence.