Associate Professor Joseph Lizier
School of Computer Science
Associate Professor Joseph Lizier leads the Information Dynamics team in the Modelling and Simulation Group of the School of Computer Science in the Faculty of Engineering (Senior Lecturer 2015-18; DECRA Fellow 2016-19; A/Prof 2019-present). Previously he was a Research Scientist and Postdoctoral Fellow at CSIRO ICT Centre (Sydney, 2012-14), and a Postdoctoral Researcher at the Max Planck Institute for Mathematics in the Sciences (Leipzig, Germany, 2010-12). He has also worked as a Research Engineer in the telecommunications industry for 10 years, including at Seeker Wireless (2006-2010) and Telstra Research Laboratories (2001-2006). He obtained a PhD in Computer Science (2010), and Bachelor degrees in Electrical Engineering (2001) and Science (1999), from The University of Sydney.
A/Prof. Lizier and his team study how biological and bio-inspired systems process information, using information theory to characterise information storage and transfer within such systems.
"We examine complex systems - systems made up of a large number of small entities, whose local interactions produce emergent behaviour at the system level. Classic examples are the emergence of consciousness from billions of interactions between neurons, or shock-wave traffic jams emerging from the interaction of many cars."
"In particular, I'm interested how information is processed in these complex systems. This is because the interactions between entities in these systems can be characterised in a generic way -- information-theoretically -- as information transfer. Our work provides 'information sunglasses' that reveal spatiotemporal information flows using transfer entropy, showing us how collective decisions are made in a way that can be applied across many fields - from brain imaging analysis to financial market interactions, and beyond. In a neuroscience setting for example, we can map the neural information networks that underpin cognitive tasks, as well as revealing locations of information processing deficiencies associated with brain disorders."
"At the moment, I'm particularly interested in how the structure of a complex network -- the topology of how the entities are connected to one-another -- influences how that network is able to process information. For example, we see 'small-world' structures in many places in natural and man-made systems (e.g. both in neural networks and in your social network on Facebook) -- what are the information processing properties that make this type of network structure special?"
Research fields
- Complex systems
- Complex networks
- Information theory
- Natural information processing
- Computational neuroscience
- Artificial Life
ARC DECRA (2016-19): "Relating complex network structure to function using information theory"
ARC Discovery (2016-19): "Large-scale computational modelling of epidemics in Australia: analysis, prediction and mitigation"; with M. Prokopenko, P. Pattison, M. Gambhir and M. Piraveenan
Universities Australia / German Academic Exchange Service (DAAD, 2016-17): "Measuring neural information synthesis and its impairment"; with M. Wibral and V. Priesemann (Germany)
- Entropy Best Paper award (2019)
- 2019 - Sydney Accelerator Fellowship Awards (SOAR)
- SUPRA Supervisor of the Year Award (Faculty of Engineering & IT) (2018)
- Faculty of Engineering and IT Dean's Award for Outstanding Teaching Innovation, 2017
- DSTO Award for Best Early Career Researcher Oral Presentation at Australian Workshop on Computational Neuroscience (2014)
- CSIRO ICT Centre Young Scientist of the Year award (2013)
- Best Paper award at IEEE Symposium on Artificial Life (2011, 2013)
- Best Paper award at RoboCup'2013 Symposium (2013)
- Springer Thesis prize (2012)
- Honourable Mention in CORE Doctoral Dissertation awards for most outstanding computer science Ph.D. thesis in Australia (2010).
- University Medal in Electrical Engineering (2000)
Germany | (JW Goethe University) Joint project with Prof. Michael Wibral, "Measuring neural information synthesis and its impairment", funded under Universities Australia / German Academic Exchange Service (DAAD) Australia-Germany Joint Research Cooperation Scheme |
Project title | Research student |
---|---|
On Guided Self-organisation and Collective Intelligence | Qianyang CHEN |
IDENTIFYING AND UNDERSTANDING EFFICIENT STATISTICAL IDENTIFIERS OF TEMPORAL ASYMMETRY IN HUMAN BRAIN DYNAMICS | Teresa DALLE NOGARE |
Statistical and genetic programming frameworks for finding informative time-series features | Trent HENDERSON |
Modelling crisis-induced human mobility with resource distribution dynamics | Christina JAMERLAN |
Measuring the Relative Synchronizability and Stability of Effective Networks in Epilepsy | Jieru LIAO |
Artificial Intelligence in an Artificial Society: Linking Social Psychology and Social Structures | Jaime RUIZ SERRA |
Selected publications
Publications
Books
- Bossomaier, T., Barnett, L., Harre, M., Lizier, J. (2016). An Introduction to Transfer Entropy: Information Flow in Complex Systems. Cham: Springer. [More Information]
- Lizier, J. (2013). The Local Information Dynamics of Distributed Computation in Complex Systems. Berlin: Springer-Verlag. [More Information]
Edited Books
- Lizier, J., Bertschinger, N., Jost, J., Wibral, M. (2018). Information Decomposition of Target Effects from Multi-Source Interactions. Basel, Switzerland: MDPI - Open Access Publishing. [More Information]
- Wibral, M., Vicente, R., Lizier, J. (2014). Understanding Complex Systems Series: Directed Information Measures in Neuroscience. Berlin/Heidelberg: Springer-Verlag.
Book Chapters
- Wibral, M., Lizier, J., Priesemann, V. (2017). Bits from Brains: Analyzing Distributed Computation in Neural Systems. In Sara I. Walker, Paul C. W. Davies, George F. R. Ellis (Eds.), From Matter to Life: Information and Causality, (pp. 429-467). Cambridge: Cambridge University Press. [More Information]
- Lizier, J., Prokopenko, M., Zomaya, A. (2014). A Framework for the Local Information Dynamics of Distributed Computation in Complex Systems. In Mikhail Prokopenko (Eds.), Guided Self-Organization: Inception, (pp. 115-158). Berlin, Germany: Springer-Verlag. [More Information]
- Miller, J., Wang, R., Lizier, J., Prokopenko, M., Rossi, L. (2014). Measuring Information Dynamics in Swarms. In Mikhail Prokopenko (Eds.), Guided Self-Organization: Inception, (pp. 343-364). Berlin, Germany: Springer-Verlag. [More Information]
Journals
- Taylor, N., Whyte, C., Munn, B., Chang, C., Lizier, J., Leopold, D., Turchi, J., Zaborszky, L., Muller, E., Shine, J. (2024). Causal evidence for cholinergic stabilization of attractor landscape dynamics. Cell Reports, 43(6). [More Information]
- Lizier, J., Bauer, F., Atay, F., Jost, J. (2023). Analytic relationship of relative synchronizability to network structure and motifs. Proceedings of the National Academy of Sciences of the United States of America, 120(37), e2303332120. [More Information]
- Munn, B., Muller, E., Medel, V., Naismith, S., Lizier, J., Sanders, R., Shine, J. (2023). Neuronal connected burst cascades bridge macroscale adaptive signatures across arousal states. Nature Communications, 14(1). [More Information]
Conferences
- Zhu, R., Loeffler, A., Hochstetter, J., Diaz-Alvarez, A., Nakayama, T., Stieg, A., Gimzewski, J., Lizier, J., Kuncic, Z. (2021). MNIST classification using Neuromorphic Nanowire Networks. 2021 International Conference on Neuromorphic Systems (ICONS 2021), New York: Association for Computing Machinery (ACM). [More Information]
- Finn, C., Lizier, J. (2020). Quantifying information modification in cellular automata using pointwise partial information decomposition. 2018 Conference on Artificial Life: Beyond AI, ALIFE 2018, Tokyo: MIT Press.
- Wollstadt, P., Lizier, J., Vicente, R., Finn, C., Martinez Zarzeula, M., Lindner, M., Martinez Mediano, P., Novelli, L., Wibral, M. (2017). IDTxl - The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. Bernstein Conference 2017, Germany: Bernstein Conference. [More Information]
2024
- Taylor, N., Whyte, C., Munn, B., Chang, C., Lizier, J., Leopold, D., Turchi, J., Zaborszky, L., Muller, E., Shine, J. (2024). Causal evidence for cholinergic stabilization of attractor landscape dynamics. Cell Reports, 43(6). [More Information]
2023
- Lizier, J., Bauer, F., Atay, F., Jost, J. (2023). Analytic relationship of relative synchronizability to network structure and motifs. Proceedings of the National Academy of Sciences of the United States of America, 120(37), e2303332120. [More Information]
- Munn, B., Muller, E., Medel, V., Naismith, S., Lizier, J., Sanders, R., Shine, J. (2023). Neuronal connected burst cascades bridge macroscale adaptive signatures across arousal states. Nature Communications, 14(1). [More Information]
- Zhu, R., Lilak, S., Loeffler, A., Lizier, J., Stieg, A., Gimzewski, J., Kuncic, Z. (2023). Online dynamical learning and sequence memory with neuromorphic nanowire networks. Nature Communications, 14(6697), 1-12.
2022
- Rosas, F., Mediano, P., Luppi, A., Varley, T., Lizier, J., Stramaglia, S., Jensen, H., Marinazzo, D. (2022). Disentangling high-order mechanisms and high-order behaviours in complex systems. Nature Physics, 18, 476-477. [More Information]
- Shorten, D., Priesemann, V., Wibral, M., Lizier, J. (2022). Early lock-in of structured and specialised information flows during neural development. eLife, 11, e74651. [More Information]
2021
- Cliff, O., Novelli, L., Fulcher, B., Shine, J., Lizier, J. (2021). Assessing the significance of directed and multivariate measures of linear dependence between time series. Physical Review Research, 3(1), 13145. [More Information]
- Shorten, D., Spinney, R., Lizier, J. (2021). Estimating transfer entropy in continuous time between neural spike trains or other event-based data. PLoS Computational Biology, 17(4), e1008054. [More Information]
- Novelli, L., Lizier, J. (2021). Inferring network properties from time series using transfer entropy and mutual information: Validation of multivariate versus bivariate approaches. Network Neuroscience, 5(2), 373-404. [More Information]
2020
- Novelli, L., Atay, F., Jost, J., Lizier, J. (2020). Deriving pairwise transfer entropy fromnetwork structure and motifs. Proceedings of the Royal Society A, 476(2236), 1-19. [More Information]
- Finn, C., Lizier, J. (2020). Generalised measures of multivariate information content. Entropy, 22(2), 1-34. [More Information]
- Finn, C., Lizier, J. (2020). Quantifying information modification in cellular automata using pointwise partial information decomposition. 2018 Conference on Artificial Life: Beyond AI, ALIFE 2018, Tokyo: MIT Press.
2019
- Wilson, A., Burns, A., Crosato, E., Lizier, J., Prokopenko, M., Schaerf, T., Ward, A. (2019). Conformity in the collective: Differences in hunger affect individual and group behavior in a shoaling fish. Behavioral Ecology, 30(4), 968-974. [More Information]
- Wollstadt, P., Lizier, J., Vicente, R., Finn, C., Martinez-Zarzuela, M., Mediano, P., Novelli, L., Wibral, M. (2019). IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. The Journal of Open Source Software, 4(3), 1-4. [More Information]
- Novelli, L., Wollstadt, P., Martinez Mediano, P., Wibral, M., Lizier, J. (2019). Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testing. Network Neuroscience, 3(3), 827-847. [More Information]
2018
- Lizier, J., Harre, M., Mitchell, M., DeDeo, S., Finn, C., Lindgren, K., Lizier, A., Sayama, H. (2018). An Interview-Based Study of Pioneering Experiences in Teaching and Learning Complex Systems in Higher Education. Complexity, 2018, 1-11. [More Information]
- Spinney, R., Lizier, J. (2018). Characterizing information-theoretic storage and transfer in continuous time processes. Physical Review E, 98(1), 012314-1-012314-22. [More Information]
- Ward, A., Schaerf, T., Burns, A., Lizier, J., Crosato, E., Prokopenko, M., Webster, M. (2018). Cohesion, order and information flow in the collective motion of mixed-species shoals. Royal Society Open Science, 5(12), 1-14. [More Information]
2017
- Wibral, M., Lizier, J., Priesemann, V. (2017). Bits from Brains: Analyzing Distributed Computation in Neural Systems. In Sara I. Walker, Paul C. W. Davies, George F. R. Ellis (Eds.), From Matter to Life: Information and Causality, (pp. 429-467). Cambridge: Cambridge University Press. [More Information]
- Erten, E., Lizier, J., Piraveenan, M., Prokopenko, M. (2017). Criticality and information dynamics in epidemiological models. Entropy, 19(5), 1-11. [More Information]
- Wollstadt, P., Lizier, J., Vicente, R., Finn, C., Martinez Zarzeula, M., Lindner, M., Martinez Mediano, P., Novelli, L., Wibral, M. (2017). IDTxl - The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. Bernstein Conference 2017, Germany: Bernstein Conference. [More Information]
2016
- Lizier, J., Spinney, R., Rubinov, M., Wibral, M., Priesemann, V. (2016). A nearest-neighbours based estimator for transfer entropy between spike trains. 25th Annual Computational Neuroscience Meeting (CNS 2016). BMC Neuroscience. [More Information]
- Bossomaier, T., Barnett, L., Harre, M., Lizier, J. (2016). An Introduction to Transfer Entropy: Information Flow in Complex Systems. Cham: Springer. [More Information]
- Rudelt, L., Lizier, J., Priesemann, V. (2016). Influences of embedding and estimation strategies on the inferred memory of single spiking neurons. 25th Annual Computational Neuroscience Meeting (CNS 2016). BMC Neuroscience. [More Information]
2015
- Wibral, M., Lizier, J., Priesemann, V. (2015). Bits from brains for biologically inspired computation. Frontiers in Robotics and AI, 2, 1-25. [More Information]
- Prokopenko, M., Barnett, L., Harre, M., Lizier, J., Obst, O., Wang, X. (2015). Fisher Transfer Entropy: Quantifying the gain in transient sensitivity. Proceedings of the Royal Society A, 471(2184), 1-14. [More Information]
- Wang, X., Lizier, J., Berna, A., Bravo, F., Trowell, S. (2015). Human breath-print identification by E-nose, using information-theoretic feature selection prior to classification. Sensors and Actuators B: Chemical, 217, 165-174. [More Information]
2014
- Lizier, J., Prokopenko, M., Zomaya, A. (2014). A Framework for the Local Information Dynamics of Distributed Computation in Complex Systems. In Mikhail Prokopenko (Eds.), Guided Self-Organization: Inception, (pp. 115-158). Berlin, Germany: Springer-Verlag. [More Information]
- Wang, X., Lizier, J., Nowotny, T., Berna, A., Prokopenko, M., Trowell, S. (2014). Feature selection for chemical sensor arrays using mutual information. PloS One, 9(3), 1-17. [More Information]
- Nowotny, T., Berna, A., Binions, R., Wang, X., Lizier, J., Prokopenko, M., Trowell, S. (2014). Feature selection in Enose applications. 1st International Workshop on Odor Spaces, United Kingdom: BioMed Central. [More Information]
2013
- Cupac, V., Lizier, J., Prokopenko, M. (2013). Comparing dynamics of cascading failures between network-centric and power flow models. International Journal of Electrical Power and Energy Systems, 49(1), 369-379. [More Information]
- Lizier, J., Rubinov, M. (2013). Inferring effective computational connectivity using incrementally conditioned multivariate transfer entropy. Twenty Second Annual Computational Neuroscience Meeting: CNS*2013, United Kingdom: BioMed Central. [More Information]
- Barnett, L., Lizier, J., Harre, M., Seth, A., Bossomaier, T. (2013). Information Flow in a Kinetic Ising Model Peaks in the Disordered Phase. Physical Review Letters, 111(17), 1-4. [More Information]
2012
- Lizier, J., Prokopenko, M., Zomaya, A. (2012). Coherent information structure in complex computation. Theory in Biosciences, 131(3), 193-203. [More Information]
- Bauer, F., Lizier, J. (2012). Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: A walk counting approach. EPL, 99(6), 68007-p1-68007-p6. [More Information]
- Boedecker, J., Obst, O., Lizier, J., Mayer, N., Asada, M. (2012). Information processing in echo state networks at the edge of chaos. Theory in Biosciences, 131(3), 205-213. [More Information]
2011
- Lizier, J., Pritam, S., Prokopenko, M. (2011). Computational capabilities of small-world Boolean networks. The Eleventh European Conference on the Synthesis and Simulation of Living Systems (ECAL 2011), Cambridge, Massachusetts: Massachusetts Institute of Technology. [More Information]
- Wang, X., Lizier, J., Prokopenko, M. (2011). Fisher information at the edge of chaos in random boolean networks. Artificial Life, 17(4), 315-329. [More Information]
- Lizier, J., Piraveenan, M., Pradhana, D., Prokopenko, M., Yaeger, L. (2011). Functional and structural topologies in evolved neural networks. 10th European Conference of Artificial Life, ECAL 2009, Berlin, Heidelberg: Springer. [More Information]
2010
- Wang, X., Lizier, J., Prokopenko, M. (2010). A Fisher Information Study of Phase Transitions in Random Boolean Networks. The Twelfth International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2010, Denmark: MIT Press.
- Lizier, J., Prokopenko, M. (2010). Differentiating Information Transfer and Causal Effect. European Physical Journal B, 73(4), 605-615. [More Information]
- Lizier, J., Prokopenko, M., Zomaya, A. (2010). Information modification and particle collisions in distributed computation. Chaos, 20(3), 1-13. [More Information]
2009
- Lizier, J., Haynes, J., Heinzle, J., Prokopenko, M. (2009). Directed information structure in inter-regional cortical interactions in a visuomotor tracking task. 12th Annual Computational Neuroscience Meeting, Stockholm: BioMed Central Ltd. [More Information]
- Lizier, J., Prokopenko, M., Cornforth, D. (2009). The information dynamics of cascading failures in energy networks. European Conference on Complex Systems 2009 (ECCS’09), Warwick, United Kingdom: European Conference on Complex Systems.
2008
- Lizier, J., Prokopenko, M., Tanev, I., Zomaya, A. (2008). Emergence of Glider-like Structures in a Modular Robotic System. Eleventh International Conference on the Simulation and Synthesis of Living Systems (ALIFE XI), Cambridge, Massachusetts & London, UK: The MIT Press.
- Lizier, J., Prokopenko, M., Zomaya, A. (2008). Local information transfer as a spatiotemporal filter for complex systems. Physical Review E, 77(2), 026110-1-026110-11. [More Information]
- Wang, X., Lizier, J., Obst, O., Prokopenko, M., Wang, P. (2008). Spatiotemporal Anomaly Detection in Gas Monitoring Sensor Networks. 5th European Conference on Wireless Sensor Networks (EWSN 2008), Germany: Springer. [More Information]
2007
- Lizier, J., Prokopenko, M., Zomaya, A. (2007). Detecting Non-trivial Computation in Complex Dynamics. 9th European Conference on Artificial Life ECAL 2007, Germany: Springer. [More Information]
- Lizier, J., Prokopenko, M., Zomaya, A. (2007). Information Transfer by Particles in Cellular Automata. Third Australian Conference on Artificial Life (ACAL 2007), Berlin, Germany: Springer. [More Information]
2005
- Lizier, J., Dawson, T. (2005). On the Periodicity of Time-series Network and Service Metrics. Tencon 2005 - 2005 IEEE Region 10, Melbourne: Swinburne Press. [More Information]
2001
- Town, G., Lizier, J. (2001). Splice Losses in Holey Optical Fibers. IEEE Photonics Technology Letters, 13(8), 794-796. [More Information]
- Town, G., Lizier, J. (2001). Splite losses in holey optical fibres. OECC/IOOC 2001 Conference, : UNSW Australian Defence Force Academy.
2000
- Brand, G., Lizier, J. (2000). Bragg Scattering of Surface Waves by a Photo-Induced Array. Journal of Infrared, Millimeter and Terahertz Waves, 21(5), 717-724. [More Information]
Selected Grants
2024
- Virtual-DBS: Using Next-generation computational modelling to advance deep brain stimulation outcomes for freezing of gait in Parkinsons disease., Lizier J, Faculty of Engineering & Information Technology/FMH-Engineering Healthcare Innovation Initiative: Sprint to Create
2023
- Evaluating the Network Neuroscience of Human Cognition to Improve AI, Shine J, Lizier J, Fulcher B, Australian Research Council (ARC)/Discovery Projects (DP)
Organising committee memberships:
- IEEE Symposium on ALife (IEEE ALife) 2022 (chair), 2020 (chair), 2019, 2017 (chair), 2015;
- Workshop on Methods of Information Theory in Computational Neuroscience (satellite of CNS*2016-22), 2022 (chair), 2021, 2020 (chair), 2019, 2018 (chair), 2017 (chair), 2016 (chair),
- Information Processing in Cognition (IPCog-2013) -- co-chair;
- Symposium on Non-linear and model-free Interdependence Measures in Neuroscience 2012;
- Guided Self-Organisation (GSO) 2012.
International collaboration
Goethe University[Germany]
Prof. Michael Wibral, MEG Unit, Brain Imaging Centre, Frankfurt
Max Planck Institute for Dynamics and Self-organization[Germany]
Dr. Viola Priesemann, Neural Dynamics and Information Processing group
Max Planck Institute for Mathematics in the Sciences[Germany]
Prof. Juergen Jost, Director
University of Sussex[United Kingdom]
Dr. Lionel Barnett, Sackler Centre for Consciousness Science
Domestic collaboration
Prof. Terry Bossomaier, Faculty of Business
Dr. Oliver Obst, School of Computing, Engineering and Mathematics
Industry engagement
Dr. Rosalind Wang, Data 61