Professor Ricardo Campello's expertise ranges across the disciplines of electrical and computer engineering, computer science, and applied mathematics. He has been teaching and doing research across these disciplines for over 15 years, in Brazil, France, Canada, and Australia. He has successfully advised a number of postgraduate students (over 20 MSc/PhD students completed or in progress), undergraduate students (15+ capstone projects and research internships), as well as highly skilled personnel (2 postdoctoral fellows and 1 professor on sabbatical leave).

Research: His current research interests fall mainly within the areas of data mining and machine learning, especially the design of new algorithms and mathematical tools for descriptive and predictive analytics, such as clustering, outlier detection, pattern classification, and regression. Past research projects also involved topics in computational intelligence (neural networks, fuzzy systems, and evolutionary computation) and modelling of dynamic systems.

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, he is or was involved in projects and student supervision in areas such as bioinformatics (gene-expression data analysis), webmedia (recommender systems), medicinal chemistry (compound mining), and automation (control of biochemical processes). He is keen to discuss opportunities for future partnerships, particularly in the realm of data science, big data analytics, and their applications to various fields.

Ricardo has published 100+ research papers in scholarly journals, book chapters, and peer-reviewed conference proceedings, with over 3000 citations detected by the Google Scholar database as of January/2018.

Brief Biography: Prof. Ricardo Campello received his Bachelor degree in Electronics Engineering from the State University of São Paulo, Brazil, in 1994, and his MSc and PhD degrees in Electrical and Computer Engineering from the State University of Campinas, Brazil, in 1997 and 2002, respectively. Among other previous appointments, he was a Postdoctoral Fellow at the University of Nice, France (fall/winter 2002 - 2003), an Assistant/Associate Professor in computer science at the University of São Paulo, Brazil (2007 - 2016), and a Visiting Professor in computer science at the University of Alberta, Canada (2011 - 2013), where he is currently an Adjunct Professor (since June/2017). Since Nov/2016 he is a Full Professor in applied mathematics, College of Science and Engineering, James Cook University, Townsville, QLD, Australia.

Ricardo is a merit scholar of the Brazilian National Research Council (CNPq) since 2005, a distinction held only by a small fraction of Brazilian academics. He is an accredited primary PhD supervisor at the University of São Paulo - Brazil, the best-ranked and most renowned university in Latin America. He is also an accredited primary PhD supervisor (advisor mentor) at JCU, where he has been co-responsible for the development of the professional Master of Data Science online programme. He has served as an Associate Editor for the international journal Computational Intelligence by Wiley since 2015. He has also regularly served as a member of the program committee for major international conferences on Data Science and Big Data Analytics.

Ricardo Campello's short resumé is available here.

Prospective Students and Postdocs

Candidates seeking research positions at honours, MSc, PhD and Postdoctoral levels are welcome to contact me to discuss possible projects and funding/scholarship opportunities from various schemes in Australia and abroad.

People in my group have the opportunity to work with cutting-edge research in data mining, machine learning, data science, big data, and applications, in collaboration with renowned international experts.

Students with a passion for problem solving using a combination of applied mathematics (e.g. optimisation and discrete maths), statistics, and/or computer science (e.g. algorithm analysis and design, programming challenges, data structures) are particularly encouraged to apply.

  • MA3405: Statistical Data Mining for Big Data (Level 3; TSV)
  • SC2209: Quantitative Methods in Science-Advanced (Level 2; TSV)
  • Applied Mathematics
  • Computer Science
  • Electrical/Computer Engineering
  • Data Mining (DM): clustering, outlier detection, classification, regression
  • Machine Learning for DM: unsupervised, semi-supervised, supervised, active, and multi-view
  • Applications: Interdisciplinary applications of data science and big data analytics
  • 2017 to present - Adjunct Professor, University of Alberta (Canada)
  • 2016 to present - Full Professor, James Cook University (Australia)
  • 2011 to 2016 - Associate Professor, University of São Paulo (Brazil)
  • 2011 to 2013 - Visiting Professor, University of Alberta (Canada)
  • 2007 to 2011 - Assistant Professor, University of São Paulo (Brazil)
  • 2003 to 2006 - Invited Lecturer and Research Fellow, State University of Campinas (Brazil)
  • 2003 to 2006 - Assistant Professor, Catholic University of Santos (Brazil)
  • 2002 to 2003 - Postdoctoral Fellow, University of Nice - Sophia Antipolis (France)
Research Disciplines
Socio-Economic Objectives
  • 2017 - ACM Computing Reviews: 21st (2016) Annual Best of Computing - Notable Article
  • 2013 - Merit Scholar of the Brazilian National Research Council (CNPq) - Level 1
  • 2005 - Merit Scholar of the Brazilian National Research Council (CNPq) - Level 2
  • 2017 - Adjunct Professor in Computing Science, University of Alberta, Canada
  • 2015 - Associate Editor: Computational Intelligence (Wiley)
  • 2017 - Senior PC Member: IEEE International Conference on Big Data
  • 2017 - Accredited Primary PhD Supervisor (Advisor Mentor): James Cook University
  • 2008 - Accredited Primary PhD Supervisor: University of São Paulo, Brazil

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles
Conference Papers

ResearchOnline@JCU stores 99+ research outputs authored by Prof Ricardo Gabrielli Barreto Campello from 1998 onwards.


Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

  • Machine Learning Algorithms for Time-Series and their Application to Restoration, Prediction and Quality Control of Oceanographic Data (PhD , Primary Advisor/AM)

The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.

  • 5+ collaborations
  • 4 collaborations
  • 3 collaborations
  • 2 collaborations
  • 1 collaboration
  • Indicates the Tropics (Torrid Zone)

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