Ndèye Niang is Associate Professor in data analysis at CNAM, member of the research team MSDMA “Statistical Methods for Data Mining and Learning” at CEDRIC (Centre de Recherches en Informatique et Communication) and senior lecturer at Institut de Statistique de l’Université Paris VI (ISUP). She earned a BSc in Mathematics, MSc. in Applied Mathematics, MSc. in Computational Methods and Mathematical Models from the University Paul Sabatier Toulouse. She has a PhD in Statistics from the University of Paris IX Dauphine.
Ndèye Niang is a specialist in data analysis, data mining, and big data analytics. After completing her thesis on multidimensional methods for statistical process control, she has worked on the application of multiple table analysis methods to quality control and on the analysis of qualitative variables in data mining, in particular on correspondence analysis and several discrimination methods, as well as variables clustering prior to association rules mining in large databases. Through several Master’s thesis and PhD supervision, she collaborates with many companies and research centres for the application of advanced statistical methods to real-life problems in automotive industries, indoor air quality, customer feedback management, and drug side effects among others. She is currently working on the development of unsupervised and supervised methods for multi-block data.