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Conor Ryan

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University of Limerick

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TEL: +353-(0)61-202755

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Professor Conor Ryan is Professor of Machine Learning at the University of Limerick. He was awarded his PhD in Genetic Programming, a style of Machine Learning, in 1996, and was the inventor, along with two of his PhD students, of Grammatical Evolution, in 1998. Grammatical Evolution is the most commonly used non-patented Evolutionary Automatic Programming system in the world, and has spawned thousands of publications since its inception. Conor was a Fulbright Scholar at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (CSAIL) in 2013-2014. He holds several granted patents in the use of Machine Learning to extend the life and reliability of Flash Memory and Solid State Disks (SSDs), and was the co-founder of two companies, Evolvability and NVMdurance, both of which are located in Limerick. Conor’s research group, the Biocomputing and Developmental Systems (BDS) group, within Lero conducts research into areas such as Machine Learning, Evolutionary Computation and the application of these techniques to large scale problems, such as mammography.

  • Publications
2018
Ryan C, Murphy F, Mullins M.  2018.  Semiautonomous Vehicle Risk Analysis: A Telematics‐Based Anomaly Detection Approach. Risk Analysis. 39
Ryan C, O'Neill M, Collins JJ.  2018.  Handbook of Grammatical Evolution. Handbook of Grammatical Evolution.
Raja MAdil, Ryan C.  2018.  GELAB - A Matlab Toolbox for Grammatical Evolution. Intelligent Data Engineering and Automated Learning – IDEAL 2018.
2017
Lane F, R. Azad MAtif, Ryan C.  2017.  DICE: A New Family of Bivariate Estimation of Distribution Algorithms Based on Dichotomised Multivariate Gaussian Distributions. Applications of Evolutionary Computation: 20th European Conference, EvoApplications 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings, Part IApplications of Evolutionary Computation: 20th European Conference, EvoApplications 2017, Amsterdam.
Ryan C.  2017.  A rebuttal to Whigham, Dick, and Maclaurin by one of the inventors of Grammatical Evolution: Commentary on ``On the Mapping of Genotype to Phenotype in Evolutionary Algorithms'' by Peter A. Whigham, Grant Dick, and James Maclaurin. Genetic Programming and Evolvable Machines.
Lane F, Azad R, Ryan C.  2017.  DICE: Exploiting All Bivariate Dependencies in Binary and Multary Search Spaces. Memetic Computing.
Fitzgerald B, Hogan D, Ryan C, Sullivan J.  2017.  Endurance prediction and error Reduction in NAND flash using machine learning. 17th Non-Volatile Memory Technology Symposium (NVMTS).
Lane F, R. Azad MAtif, Ryan C.  2017.  DICE: A New Family of Bivariate Estimation of Distribution Algorithms Based on Dichotomised Multivariate Gaussian Distributions. Applications of Evolutionary Computation.
2016
Chennupati G., Azad R.MA, Ryan C.  2016.  Automatic lock-free parallel programming on multi-core processors. 2016 IEEE Congress on Evolutionary Computation (CEC).
Medernach D, Fitzgerald J, R. Azad MAtif, Ryan C.  2016.  A New Wave: A Dynamic Approach to Genetic Programming. GECCO 2016GECCO 2016.

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