Diarmuid P. O'Donoghue, BSc, PGDHE, MSc, PhD,
Department of Computer Science,
Office: Callan Building - Room 2.121 (1st Floor)
E-Mail: diarmuidd.oodonoghue @enuimy.tie
Phone: (+353) 1 708 3851
Background I am a lecturer in computer science and a member of: the Cognitive Science Research Group, ACM's SIGEVO, the Association for the Advancement of Artificial Intelligence (AAAI) and the Internet Society (ISOC).
I have participated in 10 PhD award committees, I have graduated around 20 Masters level students and supervised almost 60 final-year undergraduate projects. I was a Learning Outcomes Fellow 2009-'10.
I am a member of the Cognitive Science Research Group focused on Naturally Inspired Computing. My specific areas of interest are 1) Analogical reasoning, computational modelling of Analogy, computational creativity, conceptual blending. 2) Evolutionary Algorithms focusing on ancestral (Extra-Mendelian) techniques for optimisation and constraint handling. I am also interested in science, education and cognitively aware approaches to creativity. Here is some other personal stuff.
Recent Funding Sources: FP7, Erasmus Mundus, IRCSET, Siti Khadijah is on a Malaysian government PhD scholarship.
My research is focused on developing and applying cognitive models of analogical reasoning (AR), using them to solve complex problems in areas like; finding creative analogies, software retrieval and reuse, computational creativity, conceptual blending, land-cover maps and other areas. I am particularly interested in the role that AR plays in scientific discovery. See my analogy, and the like page or some other analogy reference pages.
I am scientific officer for Dr Inventor: Promoting Scientific Creativity by Utilising Web-based Research Objects (FP7-ICT-2013.8.1). This project is exploring analogical comparisons bewteen academic documents and related sources, to promote sicientific creativity in its users. The role of NUIM in this project is to take the "skeleton" structures representing research objects and to identifying analogical comparisons between them. Or rather, to identify those source skeletons that can form viable analogical comparisons with any presented problems and to assess the implications of that analogical comparison. This is a 2.6 Million EU project - see DrInventor.eu.
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 idetnfiying analogical comparisons between the code-graphsused to represent 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.
Research Group: I am a member of the Cognitive Science Research Group and an associate of the Principles of Programming Research Group.
Post Doctoral researchers: Dr. Donny Hurley, Dr. Yalimsew Abgaz.
PhD students: Donagh Hatton, Siti Khadijah.
MSc level: Rushikesh Sawant (MSc 2013-'15), Felicia Halim (MSc 2013-'15), Fahrurrozi Rahman (MSc 2013-'15) Felicia and Fahrurrozi are under shared supervision with Dr Rosemary Monahan. All three are DESEM Erasmus Mundus Double Masters scholars.
Undergraduate research students: David Kelly (with JP), Agnieszka Skotarska (with JP), William Clifford, Kevin O'Flynn (with RM), Fiona Gubbins (with AM), Fintan Mc Grath (2014-'15), Sian O'Briain (with AM), Amy Wall (with JP), Aisling Conway, Pierrick Lauffenburger (2013-'14)
Conference Program Committee Member: IEEE Congress on Evolutionary Computation (CEC) - Expensive Otpimization 2105, International Conference on Computational Creativity (ICCC) 2015.
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 with UML.