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Diego Hernán Peluffo-Ordóñez

Email: diego.peluffo@sdas-group.com | website: http://diegopeluffo.com/

Was born in Pasto - Colombia in 1986. He received his degree in electronic engineering, M.Eng. and PhD from the Universidad Nacional de Colombia - Manizales, Colombia, in 2008, 2010 and 2013, respectively. In 2012, he undertook his doctoral internship at KU Leuven - Leuven, Belgium. From 2013 to 2014, he worked as a postdoctoral researcher at Université Catholique de Louvain - Louvain la-Neuve, Belgium. From 2014 to 2015, he worked as an assistant teacher at Universidad Cooperativa de Colombia - Pasto, Colombia. From 2015 to 2017, he worked as a researcher/professor at Universidad Técnica del Norte - Ecuador. From 2017 to 2020, he worked as a professor at the School of Mathematical and Computational Sciences from Yachay Tech University - Ecuador. Currently, he is working as an assistant professor at Modeling, Simulation and Data Analysis (MSDA) Research Program from Mohammed VI Polytechnic University - Morocco. Also, he works as a Consultant/Curriculum Author at deeplearning.ai. He is the head and the founder of the SDAS Research Group. He is an external collaborator at Writing Lab from Tecnológico de Monterrey - Mexico. As well, he is an external supervisor of PhD programs at Universidad de Granada - Spain, Universitat Politècnica de València - Spain, and Universidad Nacional de La Plata - Argentina. He has served as an organizing committee member (general chair, session chair, competitions chair) as well as a keynote speaker in several conferences. Also, he has served as a guest editor for the Computers and Electrical Engineering Journal. His main research interests are kernel-based and spectral methods for data clustering and dimensionality reduction. The scope of his topics of interest encompasses complex high-dimensional data, signal, image and video analysis for medical and industry applications.

Research Interests

Applied maths, Data clustering, Dimensionality reduction, Data visualization, Unsupervised analysis and kernel methods, Time-varying data analysis, Biosignals, Electromedical science.