Alex Freitas
Alex Freitas is Professor of Computational Intelligence at University of Kent. He is currently teaching Data Mining and Knowledge Discovery (a master-level module) and Natural Computation (evolutionary algorithms and swarm intelligence). Alex A. Freitas received the PhD degree in computer science from the University of Essex, United Kingdom, in 1997, in the area of data mining, and a research-oriented masters’ degree (MPhil) in biological sciences from the University of Liverpool, United Kingdom in 2011, doing research on ageing with data mining and bioinformatics methods.
His main research interests are the development of new classification (supervised learning) methods for data mining and knowledge discovery, as well as the application of such methods to biology (particularly the biology of ageing) and pharmaceutical sciences.
This involve: 1) Data Mining (or Machine Learning) and Knowledge Discovery, focusing on developing new classification methods that produce interpretable models (e.g., decision trees, if-then rules and Bayesian network classifiers); 2) Applications of classification methods in the Life Sciences, mainly in the Biology of Ageing, but also in Pharmaceutical Sciences; and 3) Biologically-inspired algorithms: mainly Evolutionary Algorithms and Ant Colony Optimisation.
His main research interests are the development of new classification (supervised learning) methods for data mining and knowledge discovery, as well as the application of such methods to biology (particularly the biology of ageing) and pharmaceutical sciences.
This involve: 1) Data Mining (or Machine Learning) and Knowledge Discovery, focusing on developing new classification methods that produce interpretable models (e.g., decision trees, if-then rules and Bayesian network classifiers); 2) Applications of classification methods in the Life Sciences, mainly in the Biology of Ageing, but also in Pharmaceutical Sciences; and 3) Biologically-inspired algorithms: mainly Evolutionary Algorithms and Ant Colony Optimisation.
Country:
UK