Diarmuid P. O'Donoghue, BSc, PGDHE, MSc, PhD,
Eolas Building - Room 122 (1st Floor)
Department of Computer Science,
Co. Kildare, Ireland.
E-Mail: diarmuidd.oodonoghue @enuimy.tie
Phone: (+353) 1 708 3851
Background I am a lecturer in computer science in Maynooth University, on the outskirts of Dublin, Ireland. My research interests are: 1) Analogy & Blending esepcially for creativity, computational modelling and computational creativity, finding creative analogies and even software reuse . Analogy, and the like page and analogy reference pages. 2) Evolutionary Algorithms focusing on ancestral (Extra-Mendelian) techniques for optimisation and constraint handling. We leverage a small cache of recent ancestors to infrequently augment the diversity in the main population, generally improving results with minimal extra cost. This work was inspired by a controversial biological thoery.
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.
I was senior scientific officer for the Dr Inventor FP7-ICT-2013.8.1 project, discovering creative analogical comparisons between academic publications. See the creative analogies between SIGGRAPH graphics publications.
Online analogies between ICCC creativity papers are also available using a simpler interface. Try our online analogical mapping between 2 raw texts service. See Maynooth's Dr Inventor web-page.
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.
Recent Funding Sources: FP7, Erasmus Mundus, IRCSET, Siti Khadijah was on a Malaysian government PhD scholarship.
Post Doctoral researchers: Dr. Donny Hurley, Dr. Yalimsew Abgaz.
PhD students: Donagh Hatton, Siti Khadijah.
MSc level:Hager Ali, Dmitry Smorodinnikov (DESEM 2015-'16), Rushikesh Sawant (DESEM 2013-'15).
Undergraduate research students: (2017-'18).
Program Committee Membership: IEEE Congress on Evolutionary Computation 2017 IEEE CEC, June, Spain; International Conference on Computational Creativity 2017 ICCC June, Georgia Tech, USA; Knowledge-Intensive Smart Services and Their Applications at ECIS, June 2018.
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.