Research Group Data Science
Data science, a fast-growing interdisciplinary field of science, is the main driver for innovation in the coming years. The Data Science research group of The Hague University of Applied Sciences is focused on conducting world-class research in the field of human-centered applied data science and artificial intelligence.
Through the use of methods, algorithms, technologies and/or tools we generate insights from data allowing us to discover important patterns and make predictions. These data and the insights gained from them are used to support decision-making, management, governance and policy in a chaotic world from a human perspective.
Career of the future
A position as a data scientist is viewed as the best future career. In several areas decision-makers use data in order to achieve balanced policies. Through the application of various data science methods, our research group conducts applied research aiming provide valid and practically-feasible solutions.
How data science can help tackle modern challenges
The challenges faced in applied data science are very broad. For example:
How can we support policies with the transition towards more sustainable energy resources? How can we use data to make ‘smart mobility’ even smarter? How can we increase participation of civilians and improve the relevant policies? How can we support decision-making - for example, in the case of suddenly occurring pandemics? In the healthcare domain, how can we improve awareness and engagement of patients through the use of data?
Support through data science
How can the applied research of the Data Science research group support society in answering the aforementioned questions? We do this, for example, through the development of new methods for faster and better evaluation of an important vaccine; through prediction of the effects of measures aimed at limiting the spread of contagious diseases; through the prediction of the social readiness of residents to participate in energy transitions; orr through the development of new dynamic planning systems for autonomous vehicles.Team
Carin Hederik
Mathis Mourey
Ester de Jonge
Cor Beyers
Hani Al-Ers
Xiao Peng
Carin Hederik
Mathis Mourey
Dr. Mathis Mourey holds a Bachelor's in Economics from the UGA (France) and the NTNU (Norway), as well as a Master's in Finance from Grenoble Graduate School of Management (France). Additionally, he holds a Ph.D. in Finance from the UGA (France). His thesis work focused on the measurement of Systemic Risk in financial systems. Currently, he teaches at the Haagse Hogeschool a variety of classes on Finance, Accounting and Statistics. He also participates in the development of modules on Data Analytics and Machine Learning methods. His research in the Data Science research group focuses on the application of machine learning methods on educational datasets. The research aims to uncover the determinants of student dropout in the early stage of their academic career. Moreover, he develops web-scraping algorithms aiming at facilitating the use of Open Data. One of his current projects consists in the automatic analyzing of consumer satisfaction in cities.
m.j.f.mourey@hhs.nlEster de Jonge
Cor Beyers
Hani Al-Ers
Publications Hani Al-Ers on Google Scholar
Xiao Peng
Publications Xiao Peng on Google Scholar
About the professor
dr. Lampros Stergioulas
Lampros Stergioulas is also active for the European Commission as an expert in the field of artificial intelligence, data science and research ethics, and a member of the AI4People committee. In various programmes sponsored by the European Union and EU member states, he acts as an expert evaluator.
Lampros studied informatics and physics at the National University of Athens and received a Masters’ and a PhD in Electrical Engineering at the University of Liverpool (UK).
He has published more than 200 scientific publications and supervised and evaluated numerous PhD theses in the field of data science, computer science, health informatics, data-driven social innovation, modelling and simulation and intelligent systems.
He was principal researcher in more than 30 EU projects and coordinator of 4 EU research projects in which he cooperated with public organizations such as the European Centre for Disease Prevention (ECDC), the European Medicine Agency (EMA), the European Commission, the National Health Service (UK) as well as national and regional authorities within Europe.
Lampros’s research interests span the areas of applied AI, data science and analytics, health informatics, data-driven management and innovation, system modelling and simulation, as well as data ethics. Through this he endeavors to achieve real-world impact in the areas of healthcare, wellbeing and sustainability.
“Our mission is to apply scientific expertise to solve real-world problems using data, to support decision and policy making and transform lives and communities for the better and to help both private and public sectors innovate and grow using data science and AI."