Workshop’s Topic: The rapid development and widespread adoption of mobile devices, sensors, IoT, and communication technology have led to the generation of vast volumes of multi-source, high-dimensional data in various systems within the broader framework of smart cities, including transportation, logistics, e-commerce, healthcare, etc. Consequently, numerous data-driven methods have been developed and implemented to address research challenges related to the design and operations of these systems. In this talk, we will briefly discuss several research cases on the applications of data-driven methods in smart cities. These cases include: (1)Descriptive methods for mobile transaction digits distribution and crowd-sourcing food delivery operations; (2)Predictive methods for ICU patient condition evaluation and freelance platform service quality prediction; (3)Prescriptive method for multi-objective matching optimization in ride-sourcing transportation. Through these cases, we aim to showcase the diverse applications of data-driven methods in addressing some key challenges in smart cities.

Time and Location: 14:00 PM (GMT+8), Room A523 (School of Management)

Language: Bilingual (Chinese and English)