About Professor Mikhail Prokopenko

The general objective of Mikhail's research is to analyse and model various critical phenomena intrinsic to self-organisation, aiming to increase robustness and resilience of a diverse range of complex systems (from artificial life to digital circuitry to power grids to social networks), by identifying more timely and precise emergency interventions during technological, socio-ecological, and socio-economic crises. The approach is strongly motivated by the search for a fundamental theory of non-equilibrium information thermodynamics in systems capable of complex computation.

Prof. Prokopenko has a strong international reputation in complex self-organising systems, with more than 150 publications, patents and edited books (h-index is 27, as of March 2015). He received a PhD in Computer Science (2002, Australia), MA in Economics (1994, USA), and MSc in Applied Mathematics (1988, USSR). Over the last years, Prof. Prokopenko developed elements of a novel methodology, Information Dynamics, exemplified in diverse complex systems contexts, including cellular automata, collective and swarm behaviour, analysis and optimisation of networks, computational neuroscience, modular robotics, genetic regulatory networks, artificial life, multi-agent simulation, computational Intelligence, and machine learning. Prof. Prokopenko is one of the pioneers of the new cross-disciplinary field of Guided Self-Organisation (GSO) which combines quantitative approaches drawn from Information Theory, Statistical Mechanics, and Complex Dynamical Systems, while interpreting findings via physics concepts, such as phase transitions, percolation and critical behaviour.

In 2014, Prof. Prokopenko joined the University of Sydney, after 20 years with CSIRO.   Prof. Prokopenko is the Director of Complex Systems Research Group (School of Civil Engineering), a Steering Committee member of The International Association for Guided Self-Organization, and a Senior Member of IEEE.      Over the last decade, Prof. Prokopenko was a keynote speaker at  The 2013 IEEE Symposium on Artificial Life (Singapore, 2013);  The 3rd International Workshop on Computation in Cyber-Physical Systems (Mexico, 2012);  The NeFF–Workshop on Non-linear and model-free Interdependence Measures in Neuroscience (Frankfurt, Germany, 2012);   The GSO-2010 (Bloomington, Indiana, USA);  and other international events.      Mikhail is the Specialty Chief Editor for Computational Intelligence section of Frontiers Robotics and AI journal, having served in the past as an editor of special issues on Complex Networks, and Guided Self-Organization, and a section editor for Encyclopaedia of Machine Learning (Evolutionary Computation).  

Prof. Prokopenko is an Executive Committee member of the international RoboCup Federation, and the team leader of Gliders, the world vice-champion team in RoboCup-2014 Simulation League 2D. 

Selected publications

  1. M. Prokopenko, J.T. Lizier, Transfer Entropy and Transient Limits of Computation.Nature: Scientific Reports, 4: 5394, 2014.   
  2. M. Prokopenko, J.T. Lizier, O. Obst, X.R. Wang. Relating Fisher information to order parameters, Physical Review E, 84, 041116, 2011.   
  3. M. Prokopenko, F. Boschetti, A. Ryan. An information-theoretic primer on complexity, self-organisation and emergence, Complexity, 15(1), 11-28, Wiley, 2009.   
  4. M. Prokopenko, J.T. Lizier, D.C. Price, On thermodynamic interpretation of transfer entropy, Entropy, 15(2), 524–543, 2013.  
  5. J.T. Lizier, M. Prokopenko, A.Y. Zomaya. Local information transfer as a spatiotemporal filter for complex systems, Physical Review E, 77, 026110, 2008.   
  6.  J.T. Lizier, M. Prokopenko, A.Y. Zomaya, Information modification and particle collisions in distributed computation, Chaos, 20(3): 037109, 2010.   
  7. M. Prokopenko, N. Ay, O. Obst, D. Polani. Phase Transitions in Least-Effort Communications, Journal of Statistical Mechanics: Theory and Experiment, 2010(11): P11025, 2010.   
  8. X.R. Wang, J.M. Miller, J.T. Lizier, M. Prokopenko, L.F. Rossi, Quantifying and Tracing Information Cascades in Swarms, PLoS ONE, 7(7): e40084, 2012.   
  9. J. T. Lizier, S. Pritam, M. Prokopenko, Information dynamics in small-world Boolean networks, Artificial Life, special issue on Complex Networks, 17(4), 293-214, 2011  
  10. M. Piraveenan, M. Prokopenko, A. Y. Zomaya. Local assortativeness in scale-free networks, Europhysics Letters, 84, 28002, 2008.