Dr Pengyuan LIU

Postdoctoral Researcher of The Sea-City Interface research module

I'm Pengyuan Liu, currently serving as a Postdoctoral Researcher and Coordinator for the Sea-City Interface Project at Future Cities Laboratory (FCL). My expertise lies in the field of quantitative urban geography, where I specialize in GeoAI and urban digital twin research. I hold a PhD in Geography from the University of Leicester, UK. Before joining FCL Global, I contributed as a Lecturer in Human Geography and Urban Planning at Nanjing University of Information Science and Technology. My journey also includes valuable postdoctoral research experiences at the NUS Urban Analytics Lab and the University of Helsinki.

I am deeply passionate about integrating geospatial analytics, artificial intelligence, and digital twins within urban studies. My work focuses on developing theories, algorithms, and models that advance this integration. Additionally, I am an advocate for the open data initiative in academia, demonstrated by my role in organizing international academic conferences for OpenStreetMap, including the 2022 State of the Map (Academic Track) and 2023 OSMScience. My aim is to foster innovation in urban studies through cutting-edge research and collaboration, contributing to the development of smarter, more sustainable urban environments.

Publications

Stefano De Sabbata, Pengyuan Liu, 2023. A graph neural network framework for spatial geodemographic classication. In International Journal of Geographical Information Science. external pageDOI: 10.1080/13658816.2023.2254382.
Pengyuan Liu, Yan Zhang and Filip Biljecki, 2023. Explainable Spatially-explicit GeoAI for Urban Analytics. In Environment and Planning B: Urban Analytics and City Science. external pageDOI: 10.1177/23998083231204689.
Pengyuan Liu, Tianhong Zhao, Junjie Luo, Binyu Lei, Mario Frei, Clayton Miller and Filip Biljecki, 2023. Towards Human-centric Digital Twin: Leveraging Volunteered Geographic Information and Spatio-Temporal-explicit GeoAI to Predict Human Comfort on Urban Sidewalks. In Sustainable Cities and Society. external pageDOI: 10.1016/j.scs.2023.104480.
Yan Zhang, Pengyuan Liu and Filip Biljecki 2023. Knowledge and Topology: A Two Layer Spatially Dependent Graph Neural Networks to Identify Urban Functions with Time-series Street-level Imagery. In ISPRS Journal of Photogrammetry and Remote Sensing. external pageDOI: 10.1016/j.isprsjprs.2023.03.008.
Pengyuan Liu and Filip Biljecki, 2022. A Review of Spatially-explicit GeoAI Applications in Urban Geography. In International Journal of Applied Earth Observation and Geoinformation. external pageDOI: 10.1016/j.jag.2022.102936.
Pengyuan Liu, et al., 2022. Extracting Locations from sport and exercise-related Social Media Messages using a Neural Network-based Bilingual Toponym Recognition Model. In Journal of Spatial Information Science. external pageDOI: 10.5311/JOSIS.2022.24.167.
Pengyuan Liu and Stefano De Sabbata, 2021. A Graph-Based Semi-supervised Approach to Classification Learning in Digital Geographies. In Computers, Environment and Urban Systems. external pageDOI: 10.1016/j.compenvurbsys.2020.101583.