Dr David Shorten
School of Mathematical Sciences
College of Science
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.
| Date | Position | Institution name |
|---|---|---|
| 2022 - ongoing | Grant-Funded Researcher | The University of Adelaide |
| Date | Institution name | Country | Title |
|---|---|---|---|
| 2018 - 2022 | University of Sydney | Australia | Ph.D |
| Year | Citation |
|---|---|
| 2025 | Shorten, D. P., Humphries, M., Maclean, J., Yang, Y., & Roughan, M. (2025). Optimal proposal particle filters for detecting anomalies and manoeuvres from two line element data. Acta Astronautica, 228, 709-723. WoS1 |
| 2025 | Karunarathne, W., Shorten, D. P., & Roughan, M. (2025). An intelligent conversational agent for querying satellite manoeuvre detections: a case study. Discover Artificial Intelligence, 5(1). |
| 2025 | Shorten, D. P., Priesemann, V., Wibral, M., & Lizier, J. T. (2025). Inferring effective networks of spiking neurons using a continuous-time estimator of transfer entropy. Plos Computational Biology, 21(10), e1013500. |
| 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), 1-5. Scopus5 |
| 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. Scopus4 Europe PMC7 |
| 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. Scopus47 Europe PMC36 |
| Year | Citation |
|---|---|
| 2024 | Shorten, D. P., Karunarathne, W., & Roughan, M. (2024). How Is Starlink Manoeuvring? An Analysis of Patterns in the Manoeuvres of Starlink Satellites. In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security (IoTBDS 2024) (pp. 174-184). Online: SCITEPRESS. DOI Scopus2 |
| 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 Scopus23 |
| 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 (pp. 1-6). 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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