Doctor Oliver Obst

Doctor Oliver Obst

Director, Research Quality and Innovation,
Deans Unit School of Computing, Engineering & Math

Associate Professor in Data Science,
Deans Unit School of Computing, Engineering & Math



  • PhD University of Koblenz Landau


  • Artificial intelligence (AI)
  • Information Theory
  • Machine Learning
  • Neural Networks

Organisational Unit (School / Division)

  • Deans Unit School of Computing, Engineering & Math
  • Deans Unit School of Computing, Engineering & Math


Phone: (02) 9685 9429
Location: EN.1.34

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Previous Teaching Areas

  • 200411 Advanced Topics in Mathematics, 2017
  • 301034 Predictive Modelling, 2016
  • 301034 Predictive Modelling, 2017
  • 301117 Predictive Analytics, 2016
  • 301117 Predictive Analytics, 2017
  • 301119 Advanced Machine Learning, 2017



  • Akiyama, H., Obst, O., Sammut, C. and Tonidandel, F. (2018), 'RoboCup 2017: Robot World Cup XXI', : Springer 9783030003074.

Chapters in Books

  • Obst, O. and Boedecker, J. (2014), 'Guided self-organization of input-driven recurrent neural networks', Guided Self-Organization: Inception, Springer 9783642537332.
  • Jurdak, R., Wang, X., Obst, O. and Valencia, P. (2011), 'Wireless sensor network anomalies : diagnosis and detection strategies', Intelligence-Based Systems Engineering, Springer 9783642179303.
  • Dylla, F., Ferrein, A., Lakemeyer, G., Murray, J., Obst, O., Rofer, T., Schiffer, S., Stolzenburg, F., Visser, U. and Wagner, T. (2008), 'Approaching a formal soccer theory from behaviour specifications in robotic soccer', Computers in Sport, WIT Press 9781845640644.

Journal Articles

  • Cliff, O., Lizier, J., Wang, X., Wang, P., Obst, O. and Prokopenko, M. (2017), 'Quantifying long-range interactions and coherent structure in multi-agent dynamics', Artificial Life, vol 23, no 1 , pp 34 - 57.
  • Lagerstrom, R., Arzhaeva, Y., Szul, P., Obst, O., Power, R., Robinson, B. and Bednarz, T. (2016), 'Image classification to support emergency situation awareness', Frontiers in Robotics and AI, vol 3 .
  • Prokopenko, M., Barnett, L., Harre, M., Lizier, J., Obst, O. and Wang, X. (2015), 'Fisher transfer entropy : quantifying the gain in transient sensitivity', Proceedings of the Royal Society of London. Series A : Mathematical, Physical and Engineering Sciences, vol 471, no 2184 .
  • Budden, D., Wang, P., Obst, O. and Prokopenko, M. (2015), 'RoboCup simulation leagues : enabling replicable and robust investigation of complex robotic systems', IEEE Robotics and Automation Magazine, vol 22, no 3 , pp 140 - 146.
  • Obst, O. (2014), 'Distributed fault detection in sensor networks using a recurrent neural network', Neural Processing Letters, vol 40, no 3 , pp 261 - 273.
  • Zeman, A., Obst, O. and Brooks, K. (2014), 'Complex cells decrease errors for the Mu?ller-Lyer illusion in a model of the visual ventral stream', Frontiers in Computational Neuroscience, vol 8 .
  • Zeman, A., Obst, O., Brooks, K. and Rich, A. (2013), 'The Muller-Lyer illusion in a computational model of biological object recognition', PLoS ONE, vol 8, no 2 .
  • Obst, O., Trinchi, A., Hardin, S., Chadwick, M., Cole, I., Muster, T., Hoschke, N., Ostry, D., Price, D. and [and two others], .. (2013), 'Nano-scale reservoir computing', Nano Communication Networks, vol 4, no 4 , pp 189 - 196.
  • Boedecker, J., Obst, O., Lizier, J., Mayer, N. and Asada, M. (2012), 'Information processing in echo state networks at the edge of chaos', Theory in Biosciences, vol 131, no 3 , pp 205 - 213.
  • Prokopenko, M., Lizier, J., Obst, O. and Wang, X. (2011), 'Relating Fisher information to order parameters', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol 84, no 4 .
  • Prokopenko, M., Ay, N., Obst, O. and Polani, D. (2010), 'Phase transitions in least-effort communications', Journal of Statistical Mechanics: Theory and Experiment, vol 2010, no 11 .
  • Boedecker, J., Obst, O., Mayer, N. and Asada, M. (2009), 'Initialization and self-organized optimization of recurrent neural network connectivity', HFSP Journal, vol 3, no 5 , pp 340 - 349.

Conference Papers

  • Michael, O., Obst, O., Schmidsberger, F. and Stolzenburg, F. (2018), 'Analysing soccer games with clustering and conceptors', RoboCup (Conference), Nagoya, Japan.
  • Nakashima, T., Mifune, S., Henrio, J., Obst, O., Wang, P. and Prokopenko, M. (2015), 'Kick extraction for reducing uncertainty in RoboCup logs', International Conference on Human-Computer Interaction, Los Angeles, Calif..
  • Budden, D., Wang, P., Obst, O. and Prokopenko, M. (2015), 'Simulation leagues : analysis of competition formats', RoboCup (Conference), Joao Pessoa, Brazil.
  • Cliff, O., Lizier, J., Wang, X., Wang, P., Obst, O. and Prokopenko, M. (2014), 'Towards quantifying interaction networks in a football match', RoboCup International Symposium , Eindhoven, Netherlands.
  • Hartmann, C., Boedecker, J., Obst, O., Ikemoto, S. and Asada, M. (2013), 'Real-time inverse dynamics learning for musculoskeletal robots based on echo state Gaussian process regression', Robotics: Science and Systems Conference , Sydney, N.S.W..
  • Obst, O. and Riedmiller, M. (2012), 'Taming the reservoir : feedforward training for recurrent neural networks', International Joint Conference on Neural Networks, Brisbane, Qld..
  • Obst, O., Polani, D. and Prokopenko, M. (2011), 'Origins of scaling in genetic code', European Conference on Artificial Life, Budapest, Hungary.
  • Mayer, N., Obst, O. and Yu-Chen, C. (2010), 'Time series causality inference using echo state networks', LVA/ICA, St. Malo, France.
  • Obst, O., Boedecker, J. and Asada, M. (2010), 'Improving recurrent neural network performance using transfer entropy', International Conference on Neural Information Processing, Sydney, N.S.W..
  • Boedecker, J., Obst, O., Mayer, N. and Asada, M. (2009), 'Studies on reservoir initialization and dynamics shaping in echo state networks', European Symposium on Artificial Neural Networks, Bruges, Belgium.
  • Wang, X., Lizier, J., Obst, O., Prokopenko, M. and Wang, P. (2008), 'Spatiotemporal anomaly detection in gas monitoring sensor networks', EWSN (Conference), Bologna, Italy.
  • Obst, O., Wang, X. and Prokopenko, M. (2008), 'Using echo state networks for anomaly detection in underground coal mines', IPSN (Conference), St. Louis, Mo..

Current Projects

Title: Deep Conceptors for Temporal Data Mining
  • University of Western Sydney
  • German Academic Exchange Service (DAAD)
Western Researchers: Oliver Obst
Years: 2017-01-01 - 2018-12-31
ID: P00023581
Title: Capital Markets CRC (CMCRC) PhD Scholarship - Geoffrey Cheng Kang Chang - Developing a Predictive Model for Credit Demand using Machine Learning and Big Data Models
  • Capital Markets CRC Limited
Western Researchers: Kathy Tannous and Oliver Obst
Years: 2017-05-01 - 2020-04-30
ID: P00024161


Current Supervision

Thesis Title: Fraud Detection for Financial Products.
Field of Research:
Thesis Title: Developing a Predictive Model for Credit Demand using Machine Learning and Big Data Models
Field of Research:

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