Rodrigue is currently a PhD Student in Computer Science. His thesis is named “Evolving and Dynamic Attributed Graphs: Application to the dynamic risk mapping of Leptospirosis in New Caledonia”. It aims to integrate multi-source data (social, economic, demographic, environmental, animal, …) into graph networks in order to mine knowledge to understand which variables contribute the most in the incidence rate of Leptospirosis. The thesis is divided into two major parts: spatial analysis and temporal analysis. The spatial analysis is going to help identifying variables that contribute the most in the risk of Leptospirosis. The temporal analysis is going to help understanding the evolution of variables. This understanding will also allow Rodrigue to use Machine/Deep Learning applied to graph networks in order to predict future risk areas in New Caledonia and prevent people from getting the disease.

Since the thesis is in the field of Computer Science, it makes possible to adapt the modeling to other epidemiological phenomena but also anthropogenic phenomena.

This thesis is under supervision of Pr. Nazha Selmaoui-Folcher, Full Professor in Computer Science at the University of New Caledonia and Pr. Philippe Fournier-Viger, Distinguished Professor in Computer Science at the Shenzhen University (China).

During this thesis, Rodrigue is giving classes to Bachelor students. His main courses involve Advanced programming in Python, Graph Theory, and Database management.

Publications #


[8]	Govan, R., Scherrer, R., Goarant, C., Cannet, A., Fournier-Viger, P., Selmaoui-Folcher, N. (2025, January). Cartographie du risque épidémiologique : Le défi des données déséquilibrées. In 25èmes Journées Francophones Extraction et Gestion des Connaissances, EGC 2025. (Preprint).
[7]	Thibeaux, R., Genthon, P., Govan, R., Selmaoui-Folcher, N., Tramier, C., Kainiu, M., Soupé-Gilbert, M.-E., Wijesuriya, K., Goarant, C. (2024). Rainfall-driven resuspension of pathogenic Leptospira in a leptospirosis hotspot. Science of The Total Environment, 911, 168700.
[6]	Govan, R., Selmaoui-Folcher, N., Giannakos, A., Fournier-Viger, P. (2023). Co-location Pattern Mining Under the Spatial Structure Constraint. In: Strauss, C., Amagasa, T., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2023. Lecture Notes in Computer Science, vol 14146. Springer, Cham.
[5]	Govan, R., Selmaoui-Folcher, N., Giannakos, A., & Fournier-Viger, P. (2023, July). Extraction de co-localisations sous contrainte de la structure spatiale. In CNIA 2023-Conférence Nationale en Intelligence Artificielle, PFIA (No. 53-61).
[4]	Tokotoko, J., Govan, R., Lemonnier, H., Selmaoui-Folcher, N. (2022). Multiscale and Multivariate Time Series Clustering: A New Approach. In: Ceci, M., Flesca, S., Masciari, E., Manco, G., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2022. Lecture Notes in Computer Science(), vol 13515. Springer, Cham.
[3]	Scherrer, R., Govan, R., Quiniou, T., Jauffrais, T., Lemonnier, H., Bonnet, S., & Selmaoui-Folcher, N. (2021, November). Automatic Plankton Detection and Classification on Raw Hologram with a Single Deep Learning Architecture. In CIBB 2021 Computational Intelligence Methods for Bioinformatics and Biostatistics.
[2]	Scherrer, R., Govan, R., Quiniou, T., Jauffrais, T., Lemonnier, H., Bonnet, S., & Selmaoui-Folcher, N. (2022). Real-Time Automatic Plankton Detection, Tracking and Classification on Raw Hologram. In International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (pp. 25-39). Springer, Cham.
[1]	Tokotoko, J., Selmaoui-Folcher, N., Govan, R., Lemonnier, H. (2021). TSX-Means: An Optimal K Search Approach for Time Series Clustering. In: Strauss, C., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2021. Lecture Notes in Computer Science(), vol 12924. Springer, Cham.