David Shorten

David Shorten

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology


I am a post-doctoral researcher in Data Science. My interests mostly lie in time series analysis, with a focus on applications in healthcare and satellite orbit data.

  • Journals

    Year Citation
    2023 Shorten, D. P., Yang, Y., Maclean, J., & Roughan, M. (2023). Wide-Scale Monitoring of Satellite Lifetimes: Pitfalls and a Benchmark Dataset. Journal of Spacecraft and Rockets, 60(6), 2003-2007.
    DOI Scopus1
    2022 Shorten, D. P., Priesemann, V., Wibral, M., & Lizier, J. T. (2022). Early lock-in of structured and specialised information flows during neural development. eLife, 11, 1-42.
    DOI Scopus2 Europe PMC2
    2021 Shorten, D. P., Spinney, R. E., & Lizier, J. T. (2021). Estimating transfer entropy in continuous time between neural spike trains or other event-based data. PLoS Computational Biology, 17(4), 45 pages.
    DOI Scopus25 Europe PMC8
  • Conference Papers

    Year Citation
    2020 Shorten, D., & Nitschke, G. (2020). Exploring exploration catastrophes in various network models. In ALIFE 2018 - 2018 Conference on Artificial Life: Beyond AI (pp. 374-381). Online: MIT Press Direct.
    DOI
    2018 Shorten, D., Williamson, A., Srivastava, S., & Murray, J. C. (2018). Localisation of drone controllers from RF signals using a deep learning approach. In Proceedings of 2018 the International Conference on Pattern Recognition and Artificial Intelligence (pp. 89-97). Union, NJ, USA: ACM Press.
    DOI Scopus15
    2017 Shorten, D., & Nitschke, G. (2017). The two regimes of neutral evolution: Localization on hubs and delocalized diffusion. In G. Squillero, & K. Sim (Eds.), Applications of Evolutionary Computation Vol. 10199 (pp. 310-325). Amsterdam, The Netherlands: Springer International Publishing.
    DOI
    2017 Shorten, D., & Nitschke, G. (2017). Neutral network assortativity shapes whether selective pressure promotes or hinders robustness. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Online: IEEE.
    DOI
    2016 Shorten, D., & Nitschke, G. (2016). The evolution of evolvability in evolutionary robotics. In Proceedings of the Artificial Life Conference 2016, ALIFE 2016.
    Scopus1
    2016 Shorten, D., & Nitschke, G. (2016). The relationship between evolvability and robustness in the evolution of boolean networks. In C. Gershenson, T. Froese, J. M. Siqueiros, W. Aguilar, E. J. Izquierdo, & H. Sayama (Eds.), Proceedings of the Artificial Life Conference 2016: ALIFE (pp. 276-283). Cancun, Mexico: MIT Press.
    Scopus2
    2015 Huang, C. L., Nitschke, G., & Shorten, D. (2015). Searching for novelty in pole balancing. In 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings (pp. 1792-1798). IEEE.
    DOI Scopus2
    2015 Shorten, D., & Nitschke, G. (2015). Evolving generalised maze solvers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9028 (pp. 783-794). Springer International Publishing.
    DOI Scopus4
    2014 Shorten, D., & Nitschke, G. (2014). Generational neuro-evolution: Restart and retry for improvement. In GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference (pp. 225-232). ACM.
    DOI Scopus1
    2014 Shorten, D., & Nitschke, G. (2014). How evolvable is novelty search?. In IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - IEEE ICES: 2014 IEEE International Conference on Evolvable Systems, Proceedings (pp. 125-132). IEEE.
    DOI Scopus7

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