Oscar Cordón

Leandro Pecchia

	Oscar Cordón PhD & Professor Member of the Data Science and Computational Intelligence Research Institute University of Granada, Spain
	Leandro Pecchia Ph.D & Professor University of Warwick, UK

Abstract:Skeleton-based forensic identification (SFI) techniques are a sound alternative to other kinds of primary human identification methods when there is not enough ante-mortem (AM) or post-mortem (PM) information as the skeleton usually survives both natural and non-natural decomposition processes. Two of the most important SFI techniques are craniofacial superimposition (CFS) and comparative radiography (CR). CFS aims to overlay a skull with some AM images of a candidate in order to determine if they correspond to the same person. CR considers the AM and PM comparison of other bones and cavities (skull frontal sinuses, clavicles, patellae, …) which have been reported as useful for positive identification based on their individuality and uniqueness.Designing systematic and automatic methods to support the forensic anthropologist when applying CFS and CR, avoiding the use of subjective, error-prone, and time-consuming manual procedures, is mandatory to enhance forensic identification. The use of computational intelligence (evolutionary algorithms, fuzzy sets and deep learning) and computer vision (3D-2D image registration and image processing) is a natural way to achieve this aim. This talk is devoted to present two intelligent systems for CFS and CR developed in collaboration with the University of Granada’s Physical Anthropology Lab within a fifteen years long research project. One of those systems is protected by an international patent, exploited by Panacea Cooperative Research, and is under commercialization in Mexico.

Bio-Sketch:Prof. Oscar Cordón is Full Professor with the University of Granada (UGR) in Spain. He was the founder and leader of the Virtual Learning Centre (2001-05) and Vice-President for Digital University (2015-19) at the UGR. He also was one of the founding researchers of the European Centre for Soft Computing (2006-2011). Prof. Cordón received the IEEE Computational Intelligence Society Outstanding Early Career Award in its 2011 edition, the first such award conferred; the IFSA Award for Outstanding Applications of Fuzzy Technology also in 2011; the Spanish National Award on Computer Science ARITMEL by the Spanish Computer Science Scientific Society (SCIE) in 2014; the IEEE Fellow grade for his contributions to genetic and evolutionary fuzzy systems in 2018, and the International Fuzzy Systems Association Fellow in 2019. He has published more than 370 peer-reviewed scientific publications, including 107 JCR-SCI-indexed journals (36 in D1, 63 in Q1) and a co-authored book published by World Scientific in 2001 with more than 1350 citations in Google Scholar. He is an IEEE fellow. He has also been involved in the organization of many different conferences: IPC chair of IEEE EFS2006, GEFS2008 and ESTYLF2008; international co-chair of HIS2008; publicity co-chair of IEEE SCCI2009; finance co-chair of IFSA-EUSFLAT 2009; advisory board member of ISDA'09; evolutionary algorithms IPC area chair of IPMU2010; special session co-chair of 2010 IEEE CEC 2010 (WCCI 2010); Fuzzy image, speech, vision and signal processing IPC area chair of Fuzz-IEEE 2011; special session chair of Fuzz-IEEE 2013; program committe co-chair of IFSA2015, program committe co-chair of IEEE CEC 2015, Conference Chair of Fuzz-IEEE 2016 (WCCI 2016), and technical co-chair of IEEE CEC 2017, 2019, and Fuzz-IEEE 2020 (WCCI 2020).His current research lines are on computational intelligence for forensic identification (with the UGR Physical Anthropology lab and several international forensics and security forces) and agent-based modeling and social network analysis for marketing (with R0D Brand Consultants in projects for BBVA, CAPSA, Mercedes, Rover, Nutrexpa, Coca Cola Europe, …).

Abstract:After briefly introducing the research activity of his lab, Dr Pecchia will provide an overview of his research activities in the area of machine learning and remote health monitoring for the management of chronic conditions. In this talk, Dr Pecchia will present the results of more than 10 years of experience, demonstrating how the evolution of methods and tools have enhanced the application of machine learning in real-life for the control of several conditions, including congestive heart failure, hypertension, mental stress and hypoglycemia.Finally, Dr Pecchia will provide a quick overview of his current projects on the application of machine learning for enhancing healthcare services in lower-income countries.

Bio-sketch:Leandro Pecchia graduated in Biomedical Engineering in 2005 the University “Federico II” of Naples, where he also received the PhD in Biomedical Engineering in 2009. After a fellowship at the University of Nottingham, in 2013 he joined The University of Warwick, UK, where he is Reader of Biomedical Engineering. In 2014, he founded the Applied Biomedical Signal Processing and Intelligent eHealth Lab (ABSPIE), which he is directing. The lab has fast grown, counting now 5 Senior Research Fellows and 9 PhD students. The lab has successfully been financed with National, European and international competitive research grants, in the area of IoT, AI, big data for health. Dr Pecchia authored more than 150 publications, including peer-reviewed journal articles, book chapters, patent applications and conference papers in the fields of Health Technology Assessment (HTA), clinical engineering, machine learning and biomedical signal processing. Dr Pecchia researches focused on healthy ageing, chronic disease management and adverse events’ prediction, medical device design, regulation, maintenance and assessment, with a particular focus to low-resource settings.Dr Pecchia is Secretary General of the IUPESM, Treasurer of the IFMBE Clinical Engineering Division, and Elected President of the EAMBES. He also served the IFMBE Healthcare Technology Assessment Division as Chair (2015-18) and Treasurer (2012-15).