Welcome to the UCD Natural Computing Research & Applications Group

We are an interdisciplinary team of researchers motivated by Artificial Intelligence and Complex Adaptive Systems, who are based in the UCD Michael Smurfit Graduate Business School, operating at the intersections of disciplines including Business, Analytics, Computer Science, Statistics & Mathematics, and Biology.


Data-driven time series feature extraction

Stefano Mauceri and co-authors (James Sweeney, Miguel Nicolau and James McDermott) have published their latest research on a data-driven approach to feature extraction from time series for one-class classification in the journal Genetic Programming & Evolvable Machines. The approach, which uses Grammatical Evolution to automatically select both the features to extract and the sub-sequences from …

Better generalisation performance for symbolic regression models

Miguel Nicolau with NCRA alumnus Alexandros Agapitos have published their latest research on function sets, generalisation and symbolic regression in the Genetic Programming & Evolvable Machines journal. Nicolau, M., Agapitos, A. (2020). Choosing function sets with better generalisation performance for symbolic regression models. Genetic Programming and Evolvable Machines. https://doi.org/10.1007/s10710-020-09391-4