Research areas

• Data Science
• Data Mining
• Machine Learning
• Big Data
• Applications

Overview: Professor Ricardo Campello's expertise ranges across the disciplines of data science, computer science, applied mathematics/statistics and electrical/computer engineering. He has been teaching and doing research across these disciplines for about 25 years, in Brazil, France, Canada, Australia and Denmark. He has successfully advised an extensive list of postgraduate students, many of which supported by research grants. Over the years, Ricardo continuously secured external funding to support his research group, including highly skilled personnel. He currently holds an appointment supported by a prestigious International Recruit Scheme, with a major associated grant from the Novo Nordisk Foundation (NNF).

Ricardo's research interests fall primarily within the areas of data mining and machine/statistical learning, especially the design of new algorithms and mathematical tools for descriptive and predictive analytics. Particular emphasis is given to unsupervised and semi-supervised machine/statistical learning techniques. Although his work focuses primarily on conceptual, general-purpose methods that can be used in a wide spectrum of application domains, Ricardo has also a track record of interdisciplinary collaborations towards more specialised, application-oriented research. For instance, his current NNF grant focuses on applications in the field of gene-expression data analysis.