Fernando Otero

Fernando has extensive research experience in machine learning and data mining, including the evaluation and interpretation of classification models. His research interests involve the design of new machine learning algorithms that create interpretable models and data pre-processing methods for feature selection and construction. His  recent work has focused on machine learning techniques that incorporate domain knowledge to extract knowledge that is both accurate and useful for the user. He also has expertise in optimising the creation of machine learning models using computational intelligence techniques.

Fernando received his PhD in 2010 from the University of Kent, working on ant colony optimisation (ACO) algorithms for data mining, in particular the creation of ACO algorithms for the bioinformatics problem of predicting protein functions. He was a Post-Doctoral Research Associate working on the EPSRC-funded project "Refactoring and Neutrality in Genetic Programming" (EP/H020217/1) at the University of Kent (2010-2012) and obtained his BSc in Computer Science from Pontificia Universidade Catolica do Parana (Brazil) in 2002.

Fernando belongs to the following research groups:

• Artificial Intelligence and Data Science Group

Fernando's main research interests include:

• Data Mining and Knowledge Discovery, in particular classification and regression – focusing on the creation of interpretable models – and more recently clustering
• Bio-inspired algorithms, mainly ant colony optimization and genetic programming
• Application of data mining algorithms in bioinformatics (e.g., protein function prediction) and financial forecasting
• Large-scale data mining ("Big Data")

Fernando is always happy to discuss research ideas with potential research students and postdocs. In terms of funding, the School of Computing runs an annual PhD scholarship competition. The University has also put together a useful list of funding opportunities for postdoctoral research.

Current Modules

I teach on (or am otherwise involved with) the following modules:

• CO551 - Data Structures and Algorithms
• CO553 - Agile Development and Software Security
• CO554 - Computing Theory and Concurrent Programming
• CO600 - Project
• CO649 - Data Mining
• CO650 - IT Consultancy Project
• CO655 - Software Project
• CO656 - Computational Intelligence in Business, Economics and Finance
• CO880 - Project and Dissertation

Past Modules

• CO334 - People and Computing
• CO546 - Information Systems Analysis
• CO816 - eHealth

Fellow of the Higher Education Academy