Description: Urban computing is an emerging field that aims to address the challenges of rapid urbanization, such as pollution, energy consumption, and traffic congestion. Urban computing involves acquiring, integrating, and analyzing large and heterogeneous data generated by a variety of sources in urban spaces, including sensors, devices, vehicles, buildings, and people, to tackle major urban challenges.

The course will introduce

1) urban data management, including urban data, spatial data indexing, spatial data query processing, and learned spatial indexes;

2) urban data mining, including spatial data mining, spatiotemporal prediction, and reinforcement learning;

3) geospatial entity representation for point objects, trajectories, and regions and their applications, including speed inference, region population estimation, etc.;

4) foundation models for geospatial applications.

Prerequisites: Bachelor’s and master’s degrees in computer science or software engineering, including knowledge on machine learning and data management as introduced in typical undergraduate courses.

Learning objectives: The objective of the course is to provide students with a working understanding of basic knowledge, as well as research problems and solutions of urban computing.

Organizer: Christian S. Jensen

Lecturers: Professor Gao Cong, Nanyang Technological University, Singapore

ECTS: 2 ECTS

Time: June 19 – 20, 2025

Place: Aalborg University

Zip code: 9220

City: Aalborg

Maximal number of participants: 15

Deadline: May 29, 2025

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