AWMA virtual Seminar n°4

AWMA virtual Seminar n°4


The speaker,  Sophie Dabo-Niang  is full professor of Applied Mathematics at University of Lille (North of France), chair of EMS-CDC (European Mathematical society-Committee of developing countries) and scientific officer of CIMPA

She is Senegalese and French, married with 4 children. She completed a 3-year PhD in Statistics from the Sorbonne University (Paris, Pierre and Marie Curie) in 2002.

The research program of Sophie Dabo-Niang is focused on the representation of time and space in random environments through the use of stochastic space and time changes driven by real problems in various areas as medical, epidemiology, physics, environmental and hydrological studies. She published about sixty scientific articles and edited two books. She is engaged in several national and international research projects, societies, associations.

She supervised many M.S and PhD thesis students and has taught Data sciences courses in many different countries, in particular in Africa. She has led several statistical scientific events worldwide and gave different oral communications. Another important achievement is her deep involvement and commitment to promotion of Mathematics and women in Mathematics in Africa, Europe and in the developing world. She is co-founder of the Senegalese Women in Mathematics Association (SWMA).


 Conference online Link

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Date Thursday,  January 07, 2021
Time 14:00-15:00 (UTC)
Speaker Prof. Sophie Dabo-Niang
Affiliation  Université de Lille
Domain Data Sciences
Title Spatial statistical modeling and applications

Spatial statistics includes any (statistical) techniques which study phenomenons observed on spatial sets. Such phenomenons appear in a variety of fields: epidemiology, environmental sciences, agriculture, physics, image processing and many others.

The modeling of this type of data is among the most interesting research topics in dependent data analysis. This is motivated by the increasing number of situations from different fields where the data is of spatial nature.

Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current researches.

We are interested in this talk to spatial modeling and some domains of application.

Thursday, January 7, 2021