Diarmuid P. O'Donoghue, BSc, PGDHE, MSc, PhD,
Eolas Building - Room 122 (1st Floor)
Department of Computer Science,
E-Mail: diarmuidd.oodonoghue @enuimy.tie
Phone: (+353) 1 708 3851
Background I am a lecturer in computer science, a member of ACM's SIGEVO, the AAAI and the Internet Society (ISOC). I have participated in 10 PhD award committees, graduated around 23 Masters level students (9 co-supervised) and supervised over 65 final-year undergraduate research projects. I was a Learning Outcomes Fellow 2009-'10. Here is some personal stuff.My research interests are: 1) Analogy & Blending esepcially for creativity, computational modelling, computational creativity, conceptual blending. developing and applying cognitive models of analogical reasoning (AR), using them to solve complex problems in areas like; finding creative analogies, software reuse, computational creativity, conceptual blending, land-cover maps and other areas. Analogy, and the like page and analogy reference pages.
Recent Funding Sources: FP7, Erasmus Mundus, IRCSET, Siti Khadijah is on a Malaysian government PhD scholarship.
I am senior scientific officer for Dr Inventor: Promoting Scientific Creativity by Utilising Web-based Research Objects (FP7-ICT-2013.8.1) that is exploring analogical comparisons between academic documents and related sources, to promote scientific creativity in its users. The role of NUIM is to generate and use semantic structures representing research objects and to identifying analogical comparisons between them. This is a €2.6Million EU project - see DrInventor.eu. See a recent article Dr Inventor Simulates and Stimulates Creative Thinking from from Irish Tech News (October, 2016).
Aris: Analogical Reasoning for the reuse of Implementations and Specifications uses analogical comparisons between source code methods to support the generation of new and useful formal specifications. Aris supports the identification of functionally similar source code. Aris works by identifying analogical comparisons between the code-graphs that represent each method. These code-graphs are derived from the parse tree formed by that method. See Aris details or jump straight to Aris online (using a smaller data set).
Evolutionary Optimisation with Extra-Mendelian Inheritance. We are successfully exploring ancestor-based extensions to various evolutionary algorithms. A "cache" of recent ancestors can are successfully being used to improve the performance of two types of evolutionary algorithm 1) for combinatorial optimisation and 2) for differential evolution. We are evaluating how, when and why such an ancestral strategies might be are most effective. Our original inspiration came from a controversial paper in Nature by Lolle et al (2005) and top of the All Time top 10 rankings of the prestigious Faculty of 1000.
Post Doctoral researchers: Dr. Donny Hurley, Dr. Yalimsew Abgaz.
PhD students: Donagh Hatton, Siti Khadijah.
MSc level: Ekaterina Ageeva (DESEM 2016-'17), Hager Ali, Dmitry Smorodinnikov (DESEM 2015-'16), Rushikesh Sawant (DESEM 2013-'15), Felicia Halim (MSc 2013-'15), Fahrurrozi Rahman (MSc 2013-'15) Felicia & Fahrurrozi invovlve shared supervision with Dr Rosemary Monahan. All are DESEM Erasmus Mundus Double Masters scholarship holders.
Undergraduate research students: (2015-'16) Anya Ball, Gareth Ronan Sheehan, Jeanette Moran, Laura Fitzmaurice; (2014-'15) David Kelly (with JP), Agnieszka Skotarska (with JP), William Clifford, Kevin O'Flynn (with RM), Fiona Gubbins (with AM), Fintan Mc Grath.
Program Committee Membership: IEEE Congress on Evolutionary Computation 2017 IEEE CEC, June, Spain; International Conference on Computational Creativity 2017 ICCC June, Georgia Tech, USA; World Congress on Computational Intelligence IEEE (WCCI), International Conference on Computational Creativity 2016 ICCC Vancouver, Canada.
Undergraduate courses I currently teach (in bold) or have taught:
CS101- Introduction to Programming, CS130- Databases, CS142- Introduction to Computer Science, CS401- Machine Learning and Neural Networks, CS404- Artificial Intelligence and Natural Language Processing, CS355- Artificial Intelligence, CS430 - Advanced Concepts: Computational Creativity, CS335 Software Engineering, Expert Systems, CS120 - End User computing, CS102 - Introduction to Computer Systems, Digital Logic Design.
MSc in Computer Science (Software Engineering) - M. Sc. (Software Engineering) courses I teach :
CS607 Requirements Engineering and Systems Design using UML.