Summary of Research Interests
Researching data-driven smart city governance through applying advanced data analytics such as natural language processing and machine learning to multi-sourced urban big data, including official and crowdsourced data. Specifically studying activity-travel patterns of citizens and public attitudes towards governance issues. Also exploring how data-driven evidence can support smart governance. Current work includes using unsupervised and supervised algorithms to identify patterns and determinants.
Planning support system; data analytics; urban (re)growth and shrinkage; smart city; urban complexity
PhD Thesis Title
Towards smart city and smart transport in English metropolitan areas: enhancing the understanding and governance through multi-sourced data analysis
Supervisors and Advisor
Prof. Elisabete Silva and Dr. Jose Reis (Supervisors); Kelvin MacDonald (Advisor)
Start Date
Michaelmas 2018
End Date
Summer 2022
College
Churchill College
Education
Ph.D. Candidate, University of Cambridge (2018–present)
MPhil in Planning, Growth, and Regeneration, University of Cambridge (2017–2018)
BE in Urban Planning, Sun-Yat Sen University (2012–2017)
Teaching and Research Experience
- MPhil Small Group Teaching, Spatial Analysis and Modelling (RM03), Department of Land Economy, University of Cambridge (2019-2022)
- MPhil Small Group Teaching, Urban and environmental policy (PGR01), Department of Land Economy, University of Cambridge (2019-2020)
- MPhil Small Group Teaching, Mixed research methods (RM01), Department of Land Economy, University of Cambridge (2018-2019)
Representative Publications
Articles and Book Chapters
- Chen, Y., & Silva, E. A. (2021). Smart transport: A comparative analysis using the most used indicators in the literature juxtaposed with interventions in English metropolitan areas. Transportation Research Interdisciplinary Perspectives, 10, 100371.
- Chen, Y., Silva, E.A. and Reis, J., (2020) Measuring policy debate in a regrowing city by sentiment analysis using online media data: a case study of Leipzig 2030, Regional Science Policy & Practice
- Silva, E. A., Liu, L., Kwon, H. R., Niu, H., & Chen, Y. (2020). Hard and soft data integration in geocomputation: Mixed methods for data collection and processing in urban planning. Handbook of Planning Support Science.
- Silva, E.A., Liu, L., Kwon, H.R., Niu, H., Chen, Y., and J. Reis. (2021). What's new in urban data analytics? In Applied Data Analysis for Urban Planning and Management. SAGE Publishing.
Working Papers
- Chen, Y., & Silva, E. A. (2021, April 6). Understanding of representative 24h travel activity sequences of Londoners. 29th Annual GIS Research UK Conference (GISRUK), Cardiff, Wales, UK (Online). https://doi.org/10.5281/zenodo.4665386
- Chen, Y., Niu, H., & Silva, E. A. The Road to Recovery: sensing public opinion towards reopening measures with social media data in post-lockdown cities.
Conference Presentations
- GISRUK conference (Cardiff University and Wales Institute of Social and Economic Research and Data, Wales), “Understanding of representative 24h travel activity sequences of Londoners” (2021)
- International Research Society for Public Management, “Multi-sourced Data Analysis to Support Smart Governance in a Time of Pandemic: A Case of London” (2021)
- Early Career Colloquium (Regional Science Association International British and Irish Section), “Smart transport: A comparative analysis using the most used indicators in the literature juxtaposed with interventions in English metropolitan areas” (2021)
- World Congress of the Regional Science, “How can Complexity Theory and Data Science assist Smart City Governance? A review” (2021)
