Dr Zhou Zhou
Lecturer
Engineering
Dr Zhou Zhou is a Lecturer in Data-Centric Engineering at the University of Exeter. Before this appointment, he was a Postdoctoral Research Associate in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. He earned his PhD in Electrical Engineering from Xi’an Jiaotong University in 2021. He was also a visiting researcher at the Leiden Institute of Advanced Computer Science of Leiden University in 2019.
Research Interests
Dr Zhou’s research focuses on advancing machine learning algorithms for spatiotemporal data analytics, especially on creating actionable insights and accurate predictions that address real-world challenges. By integrating statistical, mathematical, and machine-learning approaches, he aims to solve complex engineering problems across fields like Energy, Transportation, and Earth Science, promoting impactful, cross-disciplinary collaborations. His research has led to prototypes tested and verified in practical operational systems, such as power grids, weather forecasting systems, and autonomous vehicles.
Key Application Areas
- Traffic Forecasting
- Extreme Weather Prediction
- Renewable Energy Generation Prediction
- Power Load Forecasting and Monitoring
- Predictive Maintenance for Power Equipment
Methodological Expertise
- Time-series data mining: Segmentation, Representation, Clustering, Forecasting, Anomaly Detection
- Spatiotemporal data modeling: Spatiotemporal Graph Neural Networks, Recurrent Neural Networks, Generative Models
- Learning paradigms: Continuous Learning, Physics-informed ML, Privacy-preserving ML
Current Projects
- Machine Learning For Extreme Weather Prediction, EPSRC-IAA
Previous projects
- Extreme Weather Prediction using Self-supervised Pre-training and Exemplar-based Fine-tuning of Deep Learning Models, Innovation and Technology Fund, HK.
- Spatiotemporal Graph Neural Networks for Trend Forecasting: Theory and Applications for Forecasting Weather and Electric Power Load, Research Impact Fund, HK.
PhD Opportunities
Potential candidates who are interested in themes similar to those outlined above are encouraged to apply. Both domestic and international students are welcome to enquire.
