AMS Achilleas Psyllidis

Social Urban Data Lab / Social Glass

Dr. Achilleas Psyllidis

Delft University of Technology
Department of Software Technology / Web Information Systems group

Achilleas works on Spatial Data Science & GeoComputation for intelligent urban infrastructures (within the Connected City research line of AMS). He acts as research and project lead for the Social Urban Data Lab (SUDL); a new initiative within the AMS Institute, established together with Dr Alessandro Bozzon. SUDL aims to harness the power of urban big data to help city stakeholders better understand and predict the dynamics of cities and metropolitan regions. In SUDL there is substantive interest in understanding and predicting how human interactions evolve within urban systems and their hierarchies, at various spatial, social, and temporal scales. In facilitating these ambitions, SUDL researchers have developed SocialGlass; an online system for real-time urban big data analytics and forecasting. SocialGlass offers a pioneering toolbox that helps governments, planners, entrepreneurs, and wider communities plan the future of cities in a truly data-driven fashion.
His research finds applications in various domains relating to cities and metropolitan regions, including human mobility dynamics, understanding and prediction of traffic incidents, energy consumption behaviour, placement of new urban functions, and urban attractiveness, among others.  

Relevant links
Article in De Ingenieur on SocialGlass August, 2017 (In Dutch)
deingenieur.nl/artikel/stad-regelen-via-social-media


Download full article in pdf

Contact
achilleas.psyllidis@ams-institute.org

PI
Geert-Jan Houben

Bio
Achilleas Psyllidis is a Postdoctoral Researcher in Urban Data Science within the Web Information Systems group at Delft University of Technology (TU Delft) and an AMS Research Fellow, acting as research and project lead for the Social Urban Data Lab (SUDL). His expertise lies in the areas of GeoComputation, spatial data science, statistical spatial analysis, and GIScience, with applications in urban and regional contexts. His current research focus is on the application of Machine Learning to spatial data analysis and modelling for the understanding and forecasting of urban dynamics. Driven by the paradigm of GeoComputation in spatial analysis, he uses big geo-social data from a variety of sources to revisit problems relating to regionalisation, social area analysis, place characterisation (quantification and prediction of urban attractiveness, safety, human activity etc.), energy consumption behaviour, the semantic enrichment of traffic incidents, the placement of future urban functions, among others. He designs and develops pioneering spatial data science methods and tools for the creation, enrichment, integration, analysis, and visualisation of dynamic geo-social data. A prominent example is SocialGlass, an online system that harnesses the power of urban big data to help city stakeholders better understand and forecast the dynamics of cities.
He holds a PhD degree in Spatial Data Science from Delft University of Technology, having received prestigious scholarships from the A. S. Onassis Foundation, the Greek State Scholarships Foundation (IKY) and the European Social Fund of the EU, as well as individual research grants from the Foundation for Education and European Culture, and the A. G. Leventis Foundation. His dissertation was the first one to be completed within the context of the AMS Institute. His research on urban big data integration and interlinkage has been awarded the 1st Prize for Linked Open Data for Smart Cities (2015).