About Dr Mahendra Piraveenan

Piraveen’s research work focuses on complex networks in various domains, including social, biological and technical networks. In particular, he is interested in analysing the mixing patterns in these networks, and the mixing patterns influence, the structure, dynamics, evolution, and functionality of these networks. He works with a range of application domains within this context, from analysing the evolution of internet autonomous systems networks, to the evolution of neural networks within artificial life forms and agents; from recognizing functionally important genes in a gene regulatory networks, to recognizing important actors in a co-authorship network; from analysing load balance in a power grid, to analysing risk levels of individuals in a social network vulnerable to infection. He is interested in discovering underlying theoretical motifs in all these contexts. He also analyses how the networks can be best defended from random or targeted attacks, and what factors and features of nodes influence the vulnerability or robustness of networks.

Piraveen has developed the theory of local assortativity, which can be used to analyse the local level mixing patterns of complex networks, and has been applied by himself and other researchers across the world to study networks. Currently he is working on a number of projects, including (i) analysing risk levels of individual nodes in complex social networks in an epidemic scenarios, and (ii) studying robustness of complex social networks under sustained targeted attacks that follow specific patterns. The research is applicable in a number of areas including responsiveness of fire fighting and hospital networks, robustness of defence networks, infection-spearing in networks of patients, the affect of advertising and verbal communication in social networks, and the topological importance of genes and proteins in biological networks.

Piraveen is a computer systems engineer by training and obtained his B. Eng (hons) from the University of Adelaide in 2004. He obtained his Ph.D from the University of Sydney in 2010. He has also worked for CSIRO.

Selected publications

  • M. Piraveenan, M. Prokopenko, P. Wang, A. Zeman, “Decentralised multi-agent clustering in scale-free sensor networks,” book chapter, in J. Fulcher and L. C. Jain (eds.), Studies in Computational Intelligence (SCI), 115, 485-515, Springer, Berlin, 2008.
  • M. Piraveenan, M. Prokopenko, A. Y. Zomaya. Local assortativeness in scale-free networks, Europhysics Letters, 84, 28002, 2008. * (impact factor 2.893, ranked A in the ERA exercise)
  • M. Piraveenan, M. Prokopenko, A. Y. Zomaya. Assortativeness and information in scale-free networks, European Physical Journal B, 67, 291–300, 2009. * (impact factor 1.568, ranked A in the ERA exercise)
  • M. Piraveenan, M. Prokopenko, A. Y. Zomaya, Local Assortativity and Growth of Internet, European Physical Journal B, 70, 275–285, 2009. * (impact factor 1.568, ranked A in the ERA exercise)
  • M. Piraveenan, M. Prokopenko, A. Y. Zomaya. Assortative mixing in directed biological networks, IEEE Transactions on Computational Biology and Bioinformatics, to appear, 2010. * (impact factor 1.80, ranked A* in the ERA exercise)
  • M. Piraveenan, M. Prokopenko, A. Y. Zomaya. Local assortativeness in scale-free networks – Addendum, Europhysics Letters, 89, 49901, 2010. * (impact factor 2.893, ranked A in the ERA exercise)
  • M. Piraveenan, M. Prokopenko, and A. Y. Zomaya, "Classifying complex networks using unbiased local assortativity, 12th International Conference on the Synthesis and Simulation of Living Systems (ALIFE) , 2010 , (ranked A in the ERA exercise)
  • J. T. Lizier, M. Piraveenan, D. Pradhana, M. Prokopenko, and L. S. Yaeger, "Functional and structural topologies in evolved neural networks," in Advances in Artificial Life: 10th European Conference on Artificial Life (ECAL -2009), ser. LNCS/LNAI. Springer, vol. 5777-5778, 2009 * (ranked B in the ERA exercise)
  • M.Piraveenan, D.Polani, M.Prokopenko, 'Emergence of genetic coding: An information theoretic view'. The 9th European Conference on Artificial Life, ECAL-07, Portugal, September 2007 (ranked B in the ERA exercise)
  • M.Piraveenan, M. Prokopenko, P. Wang, D.Price. 'On Decentralized Clustering in Self Monitoring Networks', short paper. The 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-05), The Netherlands, July 2005. (ranked A in the ERA exercise)