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Prof. Dr. Johan Debayle
Ecole Nationale Supérieure des Mines / Saint-Etienne, France

Johan Debayle received his M.Sc., Ph.D. and Habilitation degrees in the field of image processing and analysis, in 2002, 2005 and 2012 respectively. Currently, he is a Full Professor at the Ecole Nationale Supérieure des Mines de Saint-Etienne (ENSM-SE) in France, within the SPIN Center and the LGF Laboratory, UMR CNRS 5307, where he leads the PMDM Department interested in image analysis of granular media. He is also the Deputy Director of the MORPHEA CNRS GDR 2021 Research Group. In 2015, he was a Visiting Researcher for 3 months at the ITWM Fraunhofer / University of Kaisersleutern in Germany. In 2017 and 2019, he was invited as Guest Lecturer at the University Gadjah Mada, Yogyakarta, Indonesia. He was also Invited Professor at the University of Puebla in Mexico in 2018, 2019 and 2020. He is the Head of the Master of Science in Mathematical Imaging and Spatial Pattern Analysis (MISPA) at the ENSM-SE.

His research interests include image processing and analysis, pattern recognition and stochastic geometry. He published more than 130 international papers in international journals and conference proceedings. He has been invited to give a keynote talk in several international conferences (SPIE ICMV, IEEE ISIVC, SPIE-IS&T EI, SPIE DCS, ICST, CIMA, ICPRS…).

He is the General Chair of the international conferences ISIVC’2020, ICIVP’2021, ECSIA’2021, ICPRS’2022 and served as Program committee member in several international conferences (IEEE ICIP, MICCAI, ICIAR…)

He is Associate Editor for 4 international journals: Pattern Recognition Letters (PRL), Pattern Analysis and Applications (Springer), Journal of Electronic Imaging (SPIE) and Image Analysis and Stereology (ISSIA).

He is a member of the International Society for Optics and Photonics (SPIE), International Association for Pattern Recognition (IAPR), International Society for Stereology and Image Analysis (ISSIA), Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and Vice-Chair Membership of IEE France Section.

Title: Digital twins for image and video analysis of granular media.

Abstract: Granular media are widely used in many industrial applications and fields of science from physics to chemistry, biology or agronomy. In energy, power and chemical engineering systems, in particular, it is generally desired to extract information on geometrical characteristics and on spatial distribution from digital images of the population of particles/grains involved in the process. For example in pharmaceutics, the size and the shape of crystals of active ingredients are known to have a considerable impact on the final quality of products, such as drugs. As another example, the performance of fuel cells (SOFC/SOEC) is mainly related to the electrode microstructure (size and spatial distribution of the solid and porous phases).
The purpose of this talk is then to show different ways (deterministic and stochastic methods using digital twins) of image processing, analysis and modeling to geometrically characterize such granular media from 2-D or 3-D images/videos. The developed methods will be presented by addressing different issues: overlapping, projection, blur... The methods are mainly based on image analysis, pattern recognition and machine learning.
The methods will be particularly illustrated on real applications of crystallization processes (for pharmaceutics industry), multiphase flow processes (for nuclear industry) and fuel cell power systems (for energy industry).

Dr. T. Pawan Fowdur
University of Mauritius, Mauritius

Dr. T.P. Fowdur received his BEng (Hons) degree in Electronic and Communication Engineering with first class honours from the University of Mauritius in 2004. He was also the recipient of a Gold medal for having produced the best degree project at the Faculty of Engineering in 2004. In 2005 he obtained a full-time PhD scholarship from the Tertiary Education Commission of Mauritius and was awarded his PhD degree in Electrical and Electronic Engineering in 2010 by the University of Mauritius. He is also a Registered Chartered Engineer of the Engineering Council of the UK, Vice President of the IEEE Mauritius Section (from January 2022 to date) and member of the Institute of Telecommunications Professionals of the UK. He joined the University of Mauritius as an academic in June 2009 and is presently an Associate Professor at the Department of Electrical and Electronic Engineering of the University of Mauritius. His research interests include 5G Mobile Communications, Multimedia Signal Processing, Networking and Security, Telecommunications Applications Development, Internet of Things and AI. He has published several papers in these areas and is actively involved in research supervision, reviewing of papers and organizing international conferences.

Title: Intelligent Connectivity as an Enabler for the UN Sustainable Development Goals

Abstract: In 2015, the UN General Assembly set forth the Sustainable Development Goals (SDGs) in its resolution 70/1 with 2030 as the target year. These goals have been developed with the community involvement including academia, governments, and private sector. It encompasses three major sustainable community development dimensions (e.g., protection of the environment, social diversity and inclusions, and economic growth). There are 17 SDGs which have become the widely accepted and adopted standard system to attain the aim of sustainable community development. The SDGs are extremely ambitious and wide ranging. They are thus what can be called stretch goals, which may seem close to be impossible to reach, but which are nevertheless pursued in order to inspire and stimulate radical and ground-breaking approaches and efforts to make progress. There are only eight years left to achieve the targets of the UN SDGs by 2030 and achieving these targets appear even more challenging as the world is still struggling to cope with COVID-19. COVID-19 has in fact seriously compromised several SDGs such as SDG 1 (No Poverty) in which significant progress was being made. However, COVID-19 has also propelled the adoption of digital technologies to a much higher a rate. In particular, intelligent connectivity which is the combination of several technological enablers such as mobile communications (5G), Artificial intelligence (AI), Internet of Things (IoT), Cloud and Blockchain, is considered as one of the most impactful technologies that can help achieve the SDGs. While still in its infancy, intelligent connectivity’s ability to boost productivity, spur innovation, and accelerate the development of new business models will affect virtually every aspect of socioeconomic development in ways yet to be imagined. Fast, intelligent internet connectivity enabled by 5G technology is expected to create approximately $3.6 trillion in economic output and 22.3 million jobs by 2035 in the global 5G value chain alone. By expanding connectivity and making new digital services available at the touch of a button, intelligent connectivity has driven significant social, economic and environmental benefits and has contributed to all 17 SDGs, as will be elaborated in this speech.