Bio

I am an assistant professor in  in the Cognitive Science and Artificial Intelligence department at Tilburg University. My research interests in general are network analysis, graph structured data, and data mining.  I have a mathematical background,  my thesis  involved algebraic graph theory and combinatorics.  I also worked in the industry for a period of four years in banking and consultancy environments as a quant and a data analyst, working with financial and trade data mainly.  Data science projects with a social aspect motivates me a lot.  This interest is effectuated in multiple research projects I am involved in utilising AI to create a more inclusive and accessible world. Some examples are  the 'Child Growth Monitor' by Zero hunger lab;  focusing on malnutrition detection in children,  Ilustre, a project  to support the energy transition efforts in the Caribbean, and the Icon project of Zero poverty lab, linking brain networks and poverty.

Courses

Recent publications

  1. Image-based body shape estimation to detect malnutrition

    Mohammedkhan, H., Güven, Ç., Balvert, M., & Postma, E. (2023). Image-based body shape estimation to detect malnutrition. Paper presented at Intelligent Systems Conference, Amsterdam.
  2. Feature Importance for Clustering

    Nápoles, G., Griffioen, N., Khoshrou, S., & Güven, Ç. (Accepted/In press). Feature Importance for Clustering. In Lecture Notes in Computer Science (LNCS) series Springer.
  3. The unique coclique extension property for apartments of buildings

    Brouwer, A., Draisma, J., & Güven, Ç. (Accepted/In press). The unique coclique extension property for apartments of buildings. Innovations in Incidence Geometry — Algebraic, Topological and Combinatorial, 1-16.
  4. School Dropout Prediction and Feature Importance Exploration in Malaw…

    Çolak, H., Güven, Ç., & Nápoles, G. (2022). School Dropout Prediction and Feature Importance Exploration in Malawi Using Household Panel Data: Machine Learning Approach. Journal of Computational Social Science.
  5. Which is the best model for my data?

    Nápoles, G., Grau, I., Güven, Ç., Özdemir, O., & Salgueiro, Y. (2022). Which is the best model for my data? arXiv.

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