Sofie Van Hoecke

Associate professor at IDLab, UGent - imec and lead of the PreDiCT team

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About Me

I graduated from the Engineering Department from the Ghent University in 2003. Following up on my studies in computer science, I achieved a PhD in computer science engineering at the Department of Information Technology at the same university. After being a postdoctoral research engineer at the Department of Information Technology, I started as lecturer ICT and ICT research coordinator at the University College West-Flanders. Currently, I am associate professor semantic intelligence at IDLab, Ghent University-imec. My research focuses on combining machine learning and semantic technologies for predictive maintenance and predictive healthcare. For more info, please visit my team website.
In my free time, I learn kids working with Scratch, Makey Makey, and more.

Education and employment

2017 - present Associate professor at Ghent University
2013 - 2017 Assistant professor at Ghent University
Awards and Promotions
2009 - 2013 Lecturer ICT and research coordinator at University College West-Flanders
2003 - 2009 PhD in Computer Science Engineering
Awards and References
  • S. Van Hoecke , J. Decruyenaere, C. Danneels, K. Taveirne, K. Colpaert, E. Hoste, B. Dhoedt, F. De Turck, Service-oriented subscription management of medical decision data in the Intensive Care Unit, Methods of Information in Medicine, 2008, Volume 47, 4: 364 - 380. Selected as best paper for the 2009 IMIA Yearbook of Medical Informatics.
  • PhD Dissertation "Efficient Service Management in Healthcare"
1997 - 2003 Master of Science, Computer Science Engineering

Teaching @ UGent

Ontwerp van cloud- en mobiele toepassingen

Principes, technieken en best-practices voor het ontwerpen en implementeren van cloud en mobiele applicaties, alsook hands-on ervaring met dergelijke applicaties.

Data analytics for health and connected care

Overview of how data from medical devices, wearables and databases can be acquired, processed and visualized, to provide insights for medical doctors, nurses and paramedics. Focus is on distributed applications that combine software technologies, network technologies, semantic technologies and/or machine learning for usage in hospitals, nursing homes, but also in residential context for healthy living applications.

Applied machine learning

Principes, best-practices en hands-on ervaring met clustering-, classificatie- en regressiemethoden.