Spatial-temporal Data Science in the Real World
Research Seminar Series
-
Date
30 Dec 2025
-
Organiser
Department of Industrial and Systems Engineering, PolyU
-
Time
14:30 - 16:00
-
Venue
CF303
Speaker
Prof. Harry Kai-Ho Chan
Remarks
If you have enquiries regarding E-certificate after the seminar, please contact david.kuo@polyu.edu.hk.
Summary
Recent advances in data science and machine learning for spatial data are reshaping how we model, analyze and understand the world around us. By leveraging rich positioning data and sensor observations, data-driven models can support more informed and context-aware decision-making and more accurate predictions. In this talk, I will share some of my projects in spatial and spatio-temporal data science, including missing data imputation, data mining, and policy-oriented analytics. I will highlight the motivations behind these studies, and show how tackling real-world challenges has led to methodological innovations and practical insights.
Keynote Speaker
Prof. Harry Kai-Ho Chan
Lecturer in Data Science
School of Information, Journalism and Communication, The University of Sheffield, United Kingdom
Harry Kai-Ho Chan received the PhD degree in Computer Science from the Hong Kong University of Science and Technology in 2019. He was a Postdoc researcher at Roskilde University, Denmark, from 2020 to 2022. He is currently the Lecturer in Data Science (equivalent to Assistant Professor) at the University of Sheffield, United Kingdom. His research interests include databases, data mining and analytics, machine learning and data visualization, with a focus on spatial and spatio-temporal data. He has served as the PC members of VLDB, ICDE, KDD, WWW, CIKM, SIGSPATIAL, ICDM etc, and the journal referee of TKDE, VLDBJ, TKDD etc. He is the registration co-chair for PAKDD 2026, and served as Web co-chair for SSTD 2025.
You may also like
