Philippe Fournier-Viger (Ph.D.) is a professor at University of Moncton (Canada). He received a Ph.D. in Cognitive Computer Science at the University of Quebec in Montreal (2010). His research interests include data mining, e-learning, intelligent tutoring systems, knowledge representation and cognitive modeling. He is currently working on several data mining projects related to frequent pattern mining. He has published more than 45 conference/journal papers. He is author of the SPMF data mining software.

Fournier-Viger, P. & Tseng, V. S. (2011). Mining Top-K Sequential Rules. Proceedings of the 7th Intern. Conf. on Advanced Data Mining and Applications (ADMA 2011). LNAI 7121, Springer, pp.180-194.

Fournier-Viger, P., Nkambou, R. & Tseng, V. S. (2011). RuleGrowth: Mining Sequential Rules Common to Several Sequences by Pattern-Growth. Proceedings of the 26th Symposium on Applied Computing (ACM SAC 2011). ACM Press, pp. 954-959.

Fournier-Viger, P., Faghihi, U., Nkambou, R. & Mephu Nguifo, E. (2010). CMRules: An Efficient Algorithm for Mining Sequential Rules Common to Several Sequences. Proceedings of the 23th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2010). AAAI press, pp. 410-415.

Fournier-Viger, P., Nkambou, R. & Mephu Nguifo, E. (2010). Building Intelligent Tutoring Systems for Ill-Defined Domains. In Nkambou, R., Mizoguchi, R. & Bourdeau, J. (Eds.). Advances in Intelligent Tutoring Systems, Springer, p.81-101.

ADMA 2012 (The 8th International Conference on Advanced Data Mining and Applications): program committee member

FLAIRS 2012 (25th International Florida Artificial Intelligence Research Society Conference): program committee member

BI 2012 (2012 International Conference on Brain Informatics): program committee member