Evolutionary and Complex Systems Group

The Evolutionary and Complex Systems Group (ECOS) is a research group of CISUC that aims at exploring the possible cross-fertilization between physical, biological and social systems directed towards solving complex problems in different domains. ECOS comprises researchers, graduate and undergraduate students, whose research activity is structured along different research streams, namely, Evolutionary Computation (EC), Evolutionary Machine Learning (EML) and Data Science (DS).

The EC line of research deals with the development of bio-inspired algorithms with increased effectiveness and robustness to real world optimization problems. The EML line is focused on closing the gap between the areas of ML and EC, through the development of hybrid approaches to overcome challenges that emerges in both areas. The group was quite successful in linking evolutionary computation and machine learning (ML), and recently was involved in the development of a new approach to the automatic design of complex deep learning architectures. In the area of DS, we have been using our knowledge in the fields of EC and ML to extract useful knowledge from different data sources (e.g., biological data), working towards what can be called Evolutionary Data Science.

The group is widely recognized amongst its peers with two of its members were recipients of the prestigious Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe in 2009 and 2018, respectively. The group has a strong tradition for collaborations with national and international research groups and other institutions, including companies, for developing applications that can effectively address real problems arising in different areas.