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Dr Matthew Deems Egbert

DPhil Department of Informatics, University of Sussex; MSc (hons) Evolutionary and Adaptive Systems, University of Sussex; BSc Computer Science St Andrews University


Recent placements:

July 2014 – January 2016
Harvard University, Cambridge, Massachusetts, USA
Post-doctoral Fellow, Department of Earth and Planetary Sciences

October 2013 – July 2014
University of Hertfordshire, Hatfield, UK
Research Associate, School of Computer Science

October 2012 – October 2013
Friedrich Schiller University, Jena, Germany 
Research Associate, Bio Systems Analysis Group, Institute of Computer Science

May 2011 – December 2011
University of Sussex, UK
Research Associate, Sackler Centre for Consciousness Science, Dept. of Informatics

Research | Current

I am an interdisciplinary scientist who uses computational models to study complex biological systems. A prominent theme in my research is the metabolic, self-constructing organisation of biological systems, and how this relates to their impressive adaptability. This interest draws me toward the investigation of synthetic protocells and the origin of life, where mechanisms of behaviour are at their simplest, as well as computational and mathematical models of cognitive systems, where fundamental concepts of adaptive behaviour can be clearly defined, examined, and tested.

Areas of expertise

Computational Modelling and Simulation, Artificial Life and Non-Symbolic Artificial Intelligence, Minimal forms of life and mind

Selected publications and creative works (Research Outputs)

  • Shitut, S., Ahsendorf, T., Pande, S., Egbert, M., & Kost, C. (2019). Nanotube-mediated cross-feeding couples the metabolism of interacting bacterial cells. Environmental microbiology, 21 (4), 1306-1320. 10.1111/1462-2920.14539
  • Egbert, M. D., & Pérez-Mercader J (2016). Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations. Scientific Reports, 610.1038/srep18963
  • Egbert, M. D., & Barandiaran, X. E. (2014). Modeling habits as self-sustaining patterns of sensorimotor behavior. Frontiers in Human Neuroscience, 8.10.3389/fnhum.2014.00590
  • Egbert, M., & Cañamero L (2014). Habit-Based Regulation of Essential Variables. In H. Sayama, J. Rieffel, S. Risi, R. E. Doursat, H. Lipson (Eds.) Artificial Life 14. Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, 168-175. New York, NY: The MIT Press. 10.7551/978-0-262-32621-6-ch029
  • Barandiaran, X. E., & Egbert, M. D. (2014). Norm-Establishing and Norm-Following in Autonomous Agency. Artificial Life, 20 (1), 5-28. 10.1162/ARTL_a_00094
  • Ibrahim, B., Henze, R., Gruenert, G., Egbert, M., Huwald, J., & Dittrich, P. (2013). Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore. Cells, 2 (3), 506-544. 10.3390/cells2030506
  • Egbert, M. D. (2013). Bacterial Chemotaxis: Introverted or Extroverted? A Comparison of the Advantages and Disadvantages of Basic Forms of Metabolism-Based and Metabolism-Independent Behavior Using a Computational Model. PLoS ONE, 8 (5)10.1371/journal.pone.0063617
  • Egbert, M., Grünert G, Escuela, G., & Dittrich, P. (2013). Synthetic signalling protocell networks as models of neural computation. Paper presented at ECAL 2013: 12th European Conference on Artificial Life, Taormina, Italy. 2 September - 6 September 2013. Advances in Artificial Life, ECAL 2013. Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems. 10.7551/978-0-262-31709-2-ch037


Contact details

Primary office location

Level 4, Room 491
New Zealand

Web links