I am a PhD student from Prof. Dr. Ulf Brefeld.
I am working on the QQM project : a joint project between the Leuphana University and the DIPF.
I am interested in user analysis and recommender system. I also worked on educational problematics and psychometrics models.
I received both of my B.Sc. and M.Sc degrees in pure Mathematics (algebraic geometry) from the University Pierre et Marie Curie, Paris 6, France. You can find my resume here.
Topic of interest
Recommender System, Graph Propagation, Pattern Analysis, Computational Geometry, Archetypes Analysis, Psychometrics, Popular Science and nice plots!
- Einführung in die Künstliche Intelligenz / Introduction to Artificial Intelligence (S16)
- Hamid Zafartavanaelmi, Master Thesis at TU Darmstadt, Germany
- Shailee Jain, DAAD intern from National Institute of Technology Karnataka, Surathkal, India
- Mischa Rohleder, Master Thesis at TU Darmstadt, Germany
- Louis Filstroff, Intern from Ecole Centrale de Lille, France
- Clemens Möckel from Universität Tübingen, Germany
- A. Boubekki, S. Jain, and U. Brefeld. Mining User Trajectories in Electronic Text Books. Proceedings of Educational Data Mining, 2018.
- J. Reubold, A. Boubekki, T. Strufe, and U. Brefeld. Infinite Mixtures of Markov Chains. New Frontiers in Mining Complex Patterns, LNAI 10785, Springer, 2018 (accepted)
- J. Reubold, A. Boubekki, T. Strufe, and U. Brefeld. Bayesian User Behavior Models. Proceedings of the ECML/PKDD Workshop on New Frontiers in Mining Complex Patterns, 2017.
- S. Mair, A. Boubekki, and U. Brefeld. Frame-based Matrix Factorizations (abstract). Proceedings of the LWDA Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), 2017.
- S. Mair, A. Boubekki, and U. Brefeld. Frame-based Data Factorizations. Proceedings of the International Conference on Machine Learning, 2017.
- A. Boubekki, C. L. Lucchesi, U. Brefeld, and W. Stille. Propagating Maximum Capacities for Recommendation. Proceedings of the German Conference on Artificial Intelligence, 2017.
- A. Boubekki, U. Kröhne, F. Goldhammer, W. Schreiber, and U. Brefeld. In S. Michaelis, N. Piatkowski, and M. Stolpe (Eds.): Data-Driven Analyses of Electronic Text Books. Solving Large Scale Learning Tasks. Challenges and Algorithms -- Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday. Lecture Notes in Artificial Intelligence 9580, Springer, 362-376, 2016. [link]
- Delacroix T., Boubekki A., Lenca P. and Lallich S., Constrained Independence for Detecting Interesting Patterns, Proceedings of the International Conference on Data Science and Advanced Analytics (DSAA), 2015.
- Boubekki A., Kröhne U., Goldhammer F., Schreiber W., Brefeld U., Toward Data-Driven Analyses of Electronic Text Books, Proceedings of the International Conference on Educational Data Mining, 2015.
- Boubekki A., Brefeld U. and Delacroix T., Generalising IRT to Discriminate Between Examinees, Proceedings of the International Conference on Educational Data Mining, 2015.
- Boubekki A., Bengs D., Mining Implications From Data, Proceedings of the LWA 2014 Workshops: KDML, IR, FGWM, Aachen, Germany, September 8-10 2014,
- Delacroix T., Boubekki A., An application of multiple behavior SIA for analyzing data from student exams, in The SIA Approach for Semantic and non-Symmetric Data Analysis, Régnier, Almouloud & Gras (Eds), Educaçao Matematica Pesquisa, Sao Paulo, v.16, n.3, pp.773-794, 2014.