Advances in Knowledge Discovery and Management Volume 10

Antoine Cornuejols  is Professor in Computer Science at AgroParisTech, University

of Paris-Saclay. He is head of the Ekinocs research team and co-director of the

H@rvest chair on the role of data sciences in agriculture. He has published a largenumber of research articles in major journals and conferences and is co-author of

two books: one on Machine Learning’s concepts and algorithms (in French, 4th edition)

and one on Phase Transitions in Machine Learning. He has been the general

chair and program chair of several conferences, noticeably of EGC-2020 in Brussels.

He has been thinking and working on artificial intelligence and machine learning since his doctorate studies at UCLA and Orsay University, from which he graduated.

He is specifically interested in on line learning, transfer learning and collaborative

learning, settings where the classical machine learning approach based on the assumption

of a stationary environment must yield to new principles.

Etienne Cuvelier  is an assistant professor at ICHEC Brussels Management

School (Brussels, Belgium), a trainer at CentraleSupélec Executive Education (Paris,

France) and co-founder of the QUARESMI laboratory (Brussels, Belgium). After a

degree in mathematics and a degree in computer science at UMons (Mons, Belgium),he started a first career in secondary, higher and social education. Etienne

Cuvelier then completed a PhD in computer science at the Faculty of Computer Science

of UNamur (Namur, Belgium) in 2009. His main research interests are in the

area of complex data analysis (functional data, symbolic data, graphs).

Arnaud Martin  is full professor at University of Rennes 1 in the team DRUID

of IRISA laboratory. He received a HDR (French ability to supervised research) in

computer sciences (2009), a PhD degree in Signal Processing (2001), and Master

in Probability (1998). Pr. Arnaud Martin joined the laboratory IRISA at the universityof Rennes 1 as full professor in 2010 and co-create the team DRUID in 2012.

He teaches data fusion, data mining, and computer sciences. His research interests

are mainly related to the belief functions with applications on social networks and

crowdsourcing. He is author of numerous papers and invited talks. He supervised

numerous Phd students.

Rakia Jaziri is currently  associate professor  in computer science at Paris 8 University, researcherin the Artificial Intelligence Laboratory of Saint Denis ( Paragraphe ) and  head of master program in   Big Data and data mining. She is a former student of the Ecole Centrale de Lyon, she received the PhD degree in Computer Science in 2013 from the University of Paris Sorbonne in collaboration with the National Audiovisual Institute, then

a post-doctorate in the field of Artificial Intelligence on massive data in particular,

on algorithmsfor detecting aberrant data (suspicious behavior), the discovery of the typology of trajectories, and the prediction of the behavior of Internet users. As a member of the program committees for major conferences in her field, she has regularly

organized French-speaking conferences around AI. Her research topics now focus on machine learning. She is interested in analyzing data from social networks to extract information deemed to be significant for decision support. Her work has been the subject of numerous international publications and she was able to form partnerships with industry from all over the world.

Fabrice Guillet  is a full professor in CS at Polytech’Nantes, the graduate engineering

school of University of Nantes, France, and a member of the ” Data User Knowledge”

team (DUKe) of the LS2N laboratory. He received a PhD degree in CS in 1995

from the ” École Nationale Supérieure des Télécommunications de Bretagne”, andhis Habilitation (HdR) in 2006 from Nantes university. He is a co-founder and vicepresident

of the International French-speaking “Extraction et Gestion des

Connaissances (EGC)” society. His research interests include knowledge quality

and knowledge visualization in the frameworks of Data Science and Knowledge

Management. He has co-edited two refereed books of chapter entitled “QualityMeasures in Data Min-ing” and ” Statistical Implicative Analysis — Theory and

Applications” published by Springer in 2007 and 2008.