About Me


I am a senior postdoc researcher focusing on Educational Data Mining and Learning Analytics. My research interests covers machine learning, signal processing, and R. My current position is with the “Didaktik der Informatik / Informatik und Gesellschaft” research group at Humbold-University of Berlin. My primary responsibilities cover the research project Learning Analytics für Diversity-Inspired Adaptive Learning, which focuses on the diversity aspects of Learning Analytics. I am leading the student research projects and thesis related to my research interests. Besides the LA-DIVA, I am involved in several other collaborations within Germany and the middle Europe region.

Between 2015 - 2020, I worked at Czech Institute of Cybernetics, Robotics and Informatics. I led the Learning Analytics project focusing on the retention of first-year students. My team build up the solution for supporting the students by combining analytics and predictive modelling with the intervention framework. However, my first Learning Analytics experience was with the Knowledge Media Institute at Open University (UK), where I helped to start and develop OU Analyse project led by professor Zdenek Zdrahal. In this project, we supported approximately 200,000 students of the Open University using our developed system for early identification of students at risk of failing their studies. The project is still running, supports the day-to-day business at Open University and supports its students and teachers.

I hold a PhD degree in Biocybernetics and artificial intelligence from Faculty of Electrical Engineering, CTU in Prague, where I focused on machine learning and signal processing applications in the medical domain. In particular, on applications of Independent Component Analysis for processing of ECG signals.

Research Interests

Learning Analytics
Educational Data mining
Machine learning
Signal processing

Selected Publications

Kuzilek, J., Zdrahal, Z., & Fuglik, V. (2021). Student success prediction using student exam behaviour. Future Generation Computer Systems.

Paaßen, B., et. al. (2021). Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks. In Proceedings of the 15th International Conference on Educational Data Mining (EDM 2021).

Schumacher, C., Reich-Stiebert, N., Kuzilek, J., Burchart, M., Raimann, J., Voltmer, J.-B., & Stürmer, S. (2021). Group perceptions vs. group reality: Exploring the fit of self-report and log file data in the process of collaboration. In Companion proceedings of Conference on Learning Analytics and Knowledge 2021, Virtual Conference, 15-04-2021.

Kuzilek, J., Hlosta, & Zdrahal, Z. (2017). Open University Learning Analytics dataset. Scientific Data, 4.

Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., Vaclavek, J., & Wolff, A. (2015). OU Analyse: analysing at-risk students at The Open University. LACE: Learning Analytics Review, 1–16.

Kuzilek, J., Kremen, V., Soucek, & Lhotska, L. (2014). Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising. PLoS ONE, 9(6), 1–16.

Kuzilek, J., & Lhotska, L. (2013). Electrocardiogram Beat Detection Enhancement Using Independent Component Analysis. Medical Engineering & Physics, 35(6), 704–711.

Kuzilek, J., Lhotska, & Hanuliak, M. (2011). An Automatic Method for Holter ECG Denoising Using ICA. In In ACM Digital Library: Proceedings of 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies (pp. 1–5). Best paper award.

Chudacek, V., Zach, L., Kuzilek, J., Spilka, & Lhotska, L. (2011). Simple Scoring System for ECG Signal Quality Assessment on Android Platform. In Computing in Cardiology (pp. 449–451). Second place in CINC Challenge 2011.