Dr John Bullinaria

Dr John Bullinaria

School of Computer Science
Honorary Senior Lecturer

Contact details

School of Computer Science
University of Birmingham
B15 2TT

John Bullinaria is an Honorary Senior Lecturer in Computer Science.

John’s academic career began in Theoretical Physics, before moving on via Mathematics, Artificial Intelligence  and Psychology to settle on his current role in Computer Science in 2001. He has over 100 refereed research publications spanning those subjects.

For more information, please see John's Computer Science Profile



  • MSc in Artificial Intelligence, Cranfield University, 1991

  • PhD in Theoretical Physics, Southampton University, 1985

  • MASt in Mathematics, Cambridge University, 1982

  • BSc in Physics, Imperial College London, 1981


John Bullinaria’s academic career began as a Theoretical Physicist with a PhD on supergravity and other unified field theories from Southampton University, followed by a post-doctoral research position in the Mathematics Department of Durham University working on superstring theory and quantum gravity. He then spent three years "travelling the world" before returning to academia by retraining in Artificial Intelligence and taking up a series of post-doctoral research fellowships in the Psychology departments of Edinburgh University, Birkbeck College London and Reading University working on various computational modelling projects. He moved to Birmingham to take up a lectureship in Computer Science in 2001 and retired in 2019 but remains an honorary member of staff at Birmingham.


John’s current research interests are mainly in the fields of Computational Intelligence, Cognitive Science, and Artificial Life, particularly those aspects involving Neural and Evolutionary Computation. Major projects in the past have involved models of brain damage (connectionist neuropsychology), language processing (reading, spelling, past tense production, lexical decision), adaptive control (particularly oculomotor control), the optimization of neural information processing architectures (including the emergence of modularity), and the formulation of more biologically realistic evolutionary computation algorithms. Recently he has mainly been working on simulating the evolution of neural systems: exploring the emergence of modularity, the optimization of learning algorithms, critical periods for learning, the interaction of learning and evolution, and aspects of Life History Evolution. He also has an ongoing interest in corpus derived semantic representations, and real-world optimization applications such as vehicle routing and bin packing.


Recent publications


Bullinaria, J 2018, 'Agent-Based Models of Gender Inequalities in Career Progression', Journal of Artificial Societies and Social Simulation, vol. 21, no. 3, 7. <http://jasss.soc.surrey.ac.uk/21/3/7.html>

Bullinaria, JA 2018, 'Evolution of learning strategies in changing environments', Cognitive Systems Research, vol. 52, pp. 429-449. https://doi.org/10.1016/j.cogsys.2018.07.024

Bullinaria, J 2017, 'Imitative and Direct Learning as Interacting Factors in Life History Evolution', Artificial Life, vol. 23, no. 3, pp. 374-405. https://doi.org/10.1162/ARTL_a_00237

Garcia Najera, A, Bullinaria, J & GutiƩrrez-Andrade, M 2015, 'An evolutionary approach for multi-objective vehicle routing problems with backhauls', Computers & Industrial Engineering, vol. 81, pp. 90-108. https://doi.org/10.1016/j.cie.2014.12.029

Bullinaria, J & Alyahya, K 2014, 'Artificial Bee Colony training of neural networks: comparison with back-propagation', Memetic Computing, vol. 6, no. 3, pp. 171-182. https://doi.org/10.1007/s12293-014-0137-7

Bullinaria, JA & Levy, JP 2013, 'Limiting factors for mapping corpus-based semantic representations to brain activity', PLoS ONE, vol. 8, no. 3, e57191. https://doi.org/10.1371/journal.pone.0057191

Bullinaria, J & Levy, JP 2012, 'Extracting Semantic Representations From Word Co-Occurrence Statistics: Stop-Lists, Stemming, and Svd', Behavior Research Methods, vol. 44, no. 3, pp. 890-907. https://doi.org/10.3758/s13428-011-0183-8

Garcia Najera, A & Bullinaria, J 2011, 'An Improved Multi-Objective Evolutionary Algorithm for the Vehicle Routing Problem with Time Windows', Computers & Operations Research, vol. 38, no. 1, pp. 287-300. https://doi.org/10.1016/j.cor.2010.05.004

Chapter (peer-reviewed)

Bullinaria, J & Alyahya, K 2014, Artificial bee colony training of neural networks. in G Terrazas, FEB Otero & AD Masegosa (eds), Nature Inspired Cooperative Strategies for Optimization (NICSO 2013): learning, optimization and interdisciplinary applications. Springer, pp. 191-201, Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), United Kingdom, 2/09/13. <http://www.springer.com/gp/book/9783319016917>

Conference contribution

Levy, JP, Bullinaria, J & McCormick, S 2017, Semantic vector evaluation and human performance on a new vocabulary MCQ test. in G Gunzelmann, A Howes, T Tenbrink & E Davelaar (eds), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017). Cognitive Science Society, Austin, TX, pp. 2549-2554, 39th Annual Meeting of the Cognitive Science Society, London, United Kingdom, 26/07/17. <https://mindmodeling.org/cogsci2017/cogsci17_proceedings.pdf>

Bullinaria, J 2016, Population-Based Simulation of Gender Inequality Issues. in C Gershenson, T Foese, JM Siqueiros, W Aguilar, EJ Izquierdo & H Sayama (eds), Proceedings of the Artificial Life Conference 2016. MIT Press, pp. 452-459, The Artificial Life Conference 2016, Cancun, Mexico, 4/07/16. https://doi.org/10.7551/978-0-262-33936-0-ch073

Levy, JP & Bullinaria, J 2012, Using Enriched Semantic Representations in Predictions of Human Brain Activity. in EJ Davelaar (ed.), Connectionist Models of Neurocognition and Emergent Behavior: From Theory to Applications. World Scientific, pp. 292-308, Connectionist Models of Neurocognition and Emergent Behavior: From Theory to Applications, Proceedings of the 12th Neural Computation and Psychology Workshop, 13/10/11.

Bullinaria, J 2011, Text to Phoneme Alignment and Mapping for Speech Technology: a Neural Networks Approach. in Neural Networks (IJCNN), The 2011 International Joint Conference on. Institute of Electrical and Electronics Engineers (IEEE), pp. 625-632, Proceedings of the International Joint Conference on Neural Networks (IJCNN 2011), 5/07/11. https://doi.org/10.1109/IJCNN.2011.6033279


Landassuri-Moreno, V & Bullinaria, J 2011, 'Biasing the Evolution of Modular Neural Networks', Paper presented at Proceedings of 2011 IEEE Congress of Evolutionary Computation (CEC 2011), 8/06/11 pp. 1958-1965. https://doi.org/10.1109/CEC.2011.5949855

Bullinaria, J 2011, 'Text to Phoneme Alignment and Mapping for Speech Technology: A Neural Networks Approach', Paper presented at 2011 International Joint Conference on Neural Networks (IJCNN 2011 - San Jose), San Jose, CA, USA, 31/07/11 - 5/08/11.

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