The VUB Data Lab is a cross-disciplinary research lab at the Solvay Business School of the Vrije Universiteit Brussel (VUB) in Belgium. We focus on developing and adapting analytical tools and algorithms which retrieve valuable insights from data while taking into account the specific operational context, domain expertise, and business requirements of the application at hand. This approach differs from the typical statistical or IT perspective. Moreover, we exploit the connection between data analysis and the properties of complex systems. In doing so, we develop data analysis tools based on information theory, nonlinear dynamics, ergodic theory, and statistical physics.
The key technologies we currently focus on are data analytics, pattern mining, machine learning, deep learning, combinatorial optimization and process mining. These technologies are leveraged to solve problems originating from a range of application domains such as demand forecasting, mobility pattern mining, credit risk modeling, fraud detection, preference learning in vehicle routing, data-driven logistics, inverse design of complex systems, and healthcare.
The lab is headed by prof. Vincent Ginis, prof. Sam Verboven, prof. Filip Van Droogenbroeck, and Prof. Marie-Anne Guerry. We have strong ties with the MOBI research center on Mobility, Logistics, and Electric vehicles, with the AI research center, doing interdisciplinary research on Artificial Intelligence, as well as with the Applied Physics research group. The lab performs both fundamental and applied research, always in close collaboration with a wide network of (inter)national academic and industrial partners.