Head of the Group
Email: diego.peluffo@sdas-group.com | website: https://diegopeluffo.com/
Was born in Pasto - Colombia in 1986. He received his degree in electronic engineering, Master's in industrial automation and PhD in engineering from the Universidad Nacional de Colombia, Manizales - Colombia, in 2008, 2010 and 2013, respectively. In 2012, he undertook his doctoral internship at KU Leuven - Belgium.From 2013 to 2014, he worked as a post-doc at Université Catholique de Louvain at Louvain la-Neuve - Belgium. From 2014 to 2015, he worked as a lecturer at Universidad Cooperativa de Colombia - Pasto.From 2015 to 2017, he worked as a researcher/professor at Universidad Técnica del Norte - Ecuador. From 2017 to 2020, he worked as a researcher/professor at Yachay Tech - Ecuador. From 2020 to 2022, he worked as a Consultant/Curriculum Author at deeplearning.ai. From 2022 to 2023, he worked as a Master's thesis advisor with the Artificial Intelligence Master's program from Universidad Internacional de La Rioja (UNIR) - Spain. Currently, he is working as an assistant professor at the College of Computing from Mohammed VI Polytechnic University - Morocco. He is the founder and head of the SDAS Research Group. As well, he works as an invited lecturer and an external researcher at Corporación Universitaria Autónoma de Nariño - Pasto, Colombia, and is a member of SEDMATEC Research Group. Also, 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. He has worked on various medical, biological, and education applications involving complex, high-dimensional data processing, and signal, image, and video analysis. At the theoretical research level, his main interests are spectral and kernel-based methods for exploratory analysis and data representation.
Research Interests
Applied mathematics, data clustering, dimensionality reduction, data visualization, unsupervised analysis and kernel methods, time-varying data analysis, biosignals, electromedical science.