Page - v - in Differential Geometrical Theory of Statistics

v About the Guest Editors Frédéric Barbaresco received his State Engineering degree from the French Grand Ecole CENTRALE- SUPELEC, Paris, France, in 1991. Since then, he has worked for the THALES Group where he is now Senior Expert in the Advanced Radar Concept Business Unit of Thales Air Systems and Representative at the Board of KTD PCC (Key Technology Domain: Processing, Cognition and Control) for the Global Business Unit Thales Land & Air Systems. He has been an Emeritus Member of SEE since 2011 and he was awarded the Aymé Poirson Prize (for application of sciences to industry) by the French Academy of Sciences in 2014, the SEE Ampere Medal in 2007, the Thévenin Prize in 2014 and the NATO SET Lecture Award in 2012. He is President of SEE Technical Club ISIC “Engineering of Information and Communications Systems” and a member of the SEE administrative board. He is member of the administrative board of SMAI and GRETSI. He was an invited lecturer for UNESCO on “Advanced School and Workshop on Matrix Geometries and Applications” in Trieste at the ITCP in June 2013. He is the General Co-chairman of the new international conference GSI “Geometric Sciences of Information”. He was co-editor of MDPI Entropy Book “Information, Entropy and Their Geometric Structures”. He has co-organized the CIRM seminar TGSI’17 “Topological and Geometrical Structures of Information”. Frank Nielsen received his PhD (1996) on computational geometry and his habilitation in visual computing (2006) from the university of Nice-Sophia Antipolis (France). After the french national service, he joined Sony CSL (Japan) in 1997. He is currently professor in the computer science department of Ecole polytechnique (France). He co-organizes with Frédéric Barbaresco the biannual Geometric Sciences of Information (GSI, gsi2017.org) conference, and is co-editor of the newly launched Springer journal of Information Geometry and an associate editor of MDPI Entropy. He edited several books including Computational Information Geometry (Springer, 2017), and wrote several textbooks including Introduction to HPC with MPI for Data Science (Springer, 2016). His research interests focus on computational information geometry with applications to machine learning and visual computing.