Diego Peluffo, Ph.D.
He was born in Pasto – Colombia in 1986. He received his degree in electronic engineering, the M.Eng. and PhD degree in industrial automation from the Universidad Nacional de Colombia, Manizales – Colombia, in 2008, 2010 and 2013, respectively. He undertook his doctoral internship at KU Leuven – Belgium.Afterwards, he worked as a post-doc at Université Catholique de Louvain at Louvain la-Neuve, Belgium. In 2014, he worked as an assistant teacher at Universidad Cooperativa de Colombia – Pasto. From 2015 to 2017, he worked as a researcher/professor at Universidad Técnica del Norte – Ecuador. Currently, he is working as a researcher/professor at Yachay Tech – Ecuador. He is supervisor and external member of ALEPHSYS (Algorithms embedded in Physical Systems) research group from Universitat Rovira i Virgila – Spain. He is
invited lecturer at Universidad de Nariño – Colombia and Corporación Universitaria Autónoma de Nariño – Colombia. He is the head of the SDAS research group.
Summary of Interests
His research interest are: i) time-varying data analysis using unsupervised, spectral and kernel techniques aimed at tracking and automatic motion segmentation, ii) complex-structure data analysis using spectral representation and clustering approaches, iii) multi-labeler learning, iv) interactive data visualization
Current Research projects
- Methodology of information visual analysis in Big Data.
- Dimensionality reduction and data visualization.
- Dynamic data analysis based on non-supervised techniques.
- Intelligence for embedded systems.
- Case-based reasoning (CBR) for medical applications.
- Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure Neurocomputing Journal. J. A. Lee, D. H. Peluffo-Ordóñez, M. Verleysen.
- Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering Computer Methods and Programs in Biomedicine J. L. Rodríguez-Sotelo, D. H. Peluffo-Ordóñez, D. Cuesta-Frau, G. Castellanos-Domínguez.
- Optimal Data Projection for Kernel Spectral Clustering European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN 2014, D. H. Peluffo-Ordóñez, C. Alzate, J. A. K. Suykens, and G. Castellanos-Dominguez.