Complex Systems and Data Science group

School of Mathematics and Statistics and School of Physics, The University of Sydney, Australia

Group leaders:	Prof. Eduardo G. Altmann (Maths & Stats) A/Prof. Tristram Alexander (Physics)
Post-docs:	Dr. Karina Arias Calluari Dr. Oscar Fajardo Fontiveros
PhD students:	Lachlan Burton Cathy Liu Justin Miller Alexey Vlaskin
Master, Honours, & undegrad students:	Allan Wu Nicholas Newman Christine Pei Jamie Tyler Kathrin Fenz

We collaborate across different disciplines within the University of Sydney and beyond, in particular with colleagues from the School of Mathematics and Statistics, Computational Social Science Lab, and the Centre for Complex Systems. Students interested in joining the group are encouraged to get in touch after looking at these references.

Research Interests:

We are interested in understanding the complexity of different natural and social systems through the application of mathematical models and computational techniques. We build on the traditions of Complex Systems, non-linear Dynamics, and Statistical Physics, to explore opportunities opened by the widespread availability of data on a variety of systems of scientific and societal relevance, ranging from time series of activities of honey-bee hives to the beahaviour of users on social-media networks. Specific areas of research include [see references here]:

• Complex Systems: complex networks, computational social sciences, collective behavior, and extreme events.
  

• Data Science: statistical properties of natural language, information theory, social-media models and data, topic modelling.
  

• Non-linear dynamics: computational methods, time-series analysis, transient chaos, billiards, and chaos in Hamiltonian systems.
  

Outputs:

• List of publications
• Theses supervised (past students)
• Maintained repositories:
• An inferential approach to Urban Scaling Laws
• TopSBM: Topic Models based on Stochastic Block Models