Dr Fangce Guo is a research fellow in the Urban Systems Laboratory (USL) and Centre for Transport Studies (CTS) at Imperial College London. Her current research interests include short-term traffic forecasting, sensor data analysis, traffic state estimation, traffic data fusion and car park management in Intelligent Transport Systems (ITS).
Fangce holds a BS in Electronic/Information Engineering and a BA from Dalian University of Technology China, an MSc in Communications and Signal Processing and a PhD in Intelligent Transport Systems from Imperial College London.
Fangce is working in the urban health project to reduce health inequalities in cities around the world funded by the Welcome Trust. She recently completed working on the oneTRANSPORT project (onetransport.uk.net), funded by Innovate UK, which developed an IoT platform for predictive analytics in the transport field.
Zhai X, Guo F, Krishnan R, 2023, An Online Optimal Bus Signal Priority Strategy to Equalise Headway in Real-Time, Information, Vol:14
et al., 2022, An analysis of the value of optimal routing and signal timing control strategy with connected autonomous vehicles, Journal of Intelligent Transportation Systems, ISSN:1547-2450, Pages:1-15
et al., 2022, Network-scale traffic prediction via knowledge transfer and regional MFD analysis, Transportation Research Part C-emerging Technologies, Vol:141, ISSN:0968-090X
et al., 2021, Transferability Improvement in Short-term Traffic Prediction using Stacked LSTM Network, Transportation Research Part C: Emerging Technologies, Vol:124, ISSN:0968-090X
et al., 2021, A Domain Adaptation Framework for Short-term Traffic Prediction, IEEE Intelligent Transportation Systems Conference (ITSC), IEEE, Pages:3564-3569, ISSN:2153-0009