Jason Adair is a Lecturer in the Computing Science and Mathematics Division. Jason received a PhD in Computing Science and bachelor's in Computing Science and Psychology from the University of Stirling.
His interests include machine learning, data-analysis, evolutionary computation, feature selection and hyper-heuristics. He is currently working on two projects; Analysis of sensor sata to increase efficiencies and welfare in pork production, and the application of artificial intelligence to improve human-written code.
Innovation Voucher: Huli Route Matching
PI: Dr Sandy Brownlee
Funded by: Scottish Funding Council
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Conference Proceeding
Explaining evolutionary feature selection via local optima networks
Adair J, Thomson SL & Brownlee AEI (2024) Explaining evolutionary feature selection via local optima networks. In: GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion, Melbourne, Australia, 14.07.2024-18.05.2024. ACMDL. https://doi.org/10.1145/3638530.3664183
Conference Proceeding
Under the Hood of Transfer Learning for Deep Neuroevolution
Sarti S, Laurenço N, Adair J, Machado P & Ochoa G (2023) Under the Hood of Transfer Learning for Deep Neuroevolution. In: Applications of Evolutionary Computation. EvoApplications 2023., 12.04.2023-14.04.2023. Springer Nature Switzerland, pp. 640-655. https://doi.org/10.1007/978-3-031-30229-9_41
Conference Proceeding
From Fitness Landscapes to Explainable AI and Back
Thomson S, Adair J, Brownlee A & van den Berg D (2023) From Fitness Landscapes to Explainable AI and Back. In: GECCO '23 Companion. Gecco '23: The Genetic and Evolutionary Computation Conference, Lisbon, 15.07.2023-19.07.2023. New York: ACM. https://doi.org/10.1145/3583133.3596395
Conference Proceeding
Neuroevolution Trajectory Networks of the Behaviour Space
Sarti S, Adair J & Ochoa G (2022) Neuroevolution Trajectory Networks of the Behaviour Space. In: Jiménez Laredo JL, Hidalgo JI & Babaagba KO (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 13224. EvoApplications 2022, Madrid, Spain, 20.04.2022-22.04.2022. Cham, Switzerland: Springer International Publishing, pp. 685-703. https://doi.org/10.1007/978-3-031-02462-7_43
Article
Recombination and Novelty in Neuroevolution: A Visual Analysis
Sarti S, Adair J & Ochoa G (2022) Recombination and Novelty in Neuroevolution: A Visual Analysis. SN Computer Science, 3 (3), Art. No.: 185. https://doi.org/10.1007/s42979-022-01064-6
Conference Proceeding
Exploring the Accuracy - Energy Trade-off in Machine Learning
Brownlee A, Adair J, Haraldsson S & Jabbo J (2021) Exploring the Accuracy - Energy Trade-off in Machine Learning. In: 2021 IEEE/ACM International Workshop on Genetic Improvement (GI). Genetic Improvement Workshop at 43rd International Conference on Software Engineering, Madrid, Spain, 30.05.2021-30.05.2021. Piscataway, NJ: IEEE. https://doi.org/10.1109/GI52543.2021.00011
Conference Proceeding
Local Optima Networks for Continuous Fitness Landscapes
Adair J, Ochoa G & Malan KM (2019) Local Optima Networks for Continuous Fitness Landscapes. In: López-Ibáñez M (ed.) GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO '19 - Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13.07.2019-17.07.2019. New York: Association for Computing Machinery, pp. 1407-1414. https://doi.org/10.1145/3319619.3326852
Conference Proceeding
Rigorous Performance Analysis of State-of-the-Art TSP Heuristic Solvers
McMenemy P, Veerapen N, Adair J & Ochoa G (2019) Rigorous Performance Analysis of State-of-the-Art TSP Heuristic Solvers. In: Liefooghe A & Paquete L (eds.) Evolutionary Computation in Combinatorial Optimization. Lecture Notes in Computer Science, 11452. EVOCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization, Leipzig, Germany, 24.04.2019-26.04.2019. Cham, Switzerland: Springer International Publishing, pp. 99-114. https://doi.org/10.1007/978-3-030-16711-0_7
Conference Proceeding
Adair J, Brownlee A & Ochoa G (2018) Mutual Information Iterated Local Search: A Wrapper-Filter Hybrid for Feature Selection in Brain Computer Interfaces. In: Applications of Evolutionary Computation. EvoApplications 2018. Lecture Notes in Computer Science, 10784. EvoStar 2018, Parma, Italy, 04.04.2018-06.04.2018. Cham, Switzerland: Springer, pp. 63-77. https://link.springer.com/chapter/10.1007/978-3-319-77538-8_5; https://doi.org/10.1007/978-3-319-77538-8_5
Conference Proceeding
Evolving training sets for improved transfer learning in brain computer interfaces
Adair J, Brownlee A, Daolio F & Ochoa G (2018) Evolving training sets for improved transfer learning in brain computer interfaces. In: Nicosia G, Pardalos P, Giuffrida G & Umeton R (eds.) Machine Learning, Optimization, and Big Data. MOD 2017. Lecture Notes in Computer Science, 10710. MOD 2017 - The Third International Conference on Machine Learning, Optimization and Big Data, Volterra, Italy, 14.09.2017-17.09.2017. Cham, Switzerland: Springer, pp. 186-197. https://link.springer.com/chapter/10.1007/978-3-319-72926-8_16; https://doi.org/10.1007/978-3-319-72926-8_16
Conference Proceeding
Evolutionary Algorithms with Linkage Information for Feature Selection in Brain Computer Interfaces
Adair J, Brownlee A & Ochoa G (2016) Evolutionary Algorithms with Linkage Information for Feature Selection in Brain Computer Interfaces. In: Angelov P, Gegov A, Jayne C & Shen Q (eds.) Advances in Computational Intelligence Systems: Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7–9, 2016, Lancaster, UK. Advances in Intelligent Systems and Computing, 513. UKCI 2016 - 16th UK Workshop on Computational Intelligence, Lancaster, 07.09.2016-09.09.2016. London: Springer, pp. 287-307. https://doi.org/10.1007/978-3-319-46562-3_19