Gilles Vandewiele graduated magna cum laude as a computer science engineer in June 2016 at Ghent University. Later that year, in August, he joined the Internet and Data Science Lab (IDLab) research group in the Department of Information Technology (INTEC). There he is currently active as a Ph.D. student, conducting research in the domain of white-box machine learning for critical domains and (semantic) knowledge models. Other research interests are bio-inspired algorithms and sport-related data science in general.

If you cannot find Gilles sitting behind his desk, he is most likely doing a code golf in Python, competing in a data science competition or out playing football with friends or colleagues.

This website contains a collection of my most significant contributions during the course of my PhD. Please note that this website is not updated frequently and that most of this information can be found elsewhere.


ir. Gilles Vandewiele


gilles.vandewiele (at) ugent.be

Internet and Data Science Lab (IDLab)
Department of Information Technology (INTEC)
University Ghent
Belgium

Changelog

  • December 2017: Created this website
  • January 2019: Updated information

Publications

Journal Papers
Conference Proceedings
Miscellaneous

Education

Courses

  • System Programming (C/C++) (2017): This course is given to second year computer science engineers and third year electronical engineers. They learn how to program in both C and C++. I assisted in 4 lab sessions, created one lab session myself and corrected it. In this lab session, the students had to create a morse encoder and decoder, by using dynamic programming. Moreover, I corrected the exercise part of the exam.
  • Big Data Science (2017): I created one lab session, in which students had to go through the entire machine learning pipeline: loading and processing data, exploratory data analysis, feature extraction, feature selection, model selection and hyper-parameter tuning. The given dataset contained occupancy informations of trains in Belgium. The task was to predict the occupancy (defined by three classes) for future trains.
  • Informatics (Python) (2017): In this course, the first year engineers take their first coding steps by learning to program in Python. I assisted a lot of different lab sessions: spanning from their first print function, object-oriented programming to implementing their own BCH codes. Moreover, an AI video game bot platform was set up, where the students had to write a bot that played the game connect four. I competed in the competition myself, the details of my solution can be found here.
  • Informatics (Python) (2018): Very similar to the year before that. Again, I assisted many different lab sessions and created an AI competition with three fellow colleagues.

Thesis students

Master
Bachelor
  • Run4Music: four bright students (3 CS engineers, 1 electrical engineer) created an application that both picks suited music according to your running pace and adjusts this music slightly such that the beats of the song are synchronized with your steps. A tweet about their result went trending on Twitter and one of the four students had the opportunity to present their work on one of the most popular radio stations in Belgium: QMusic.

Funding

I am funded by a strategical basis-research grant, awarded by the Fonds Wetenschappelijk Onderzoek (FWO). My application number is 1S31417N.