STAFF PROFILE
Professor Xiaodong Li
Position:
Professor
College / Portfolio:
School of Science Cluster
School / Department:
Computer Science and Software Engineering
Phone:
+61 3 9925 9585
Email:
xiaodong.li@rmit.edu.au
Campus:
Melbourne City Campus
Contact me about:
Research supervision
Xiaodong Li received his B.Sc. degree from Xidian University, Xi'an, China, and Ph.D. degree in information science from University of Otago, Dunedin, New Zealand, respectively. Currently, he is an Associate Professor at the School of Computer Science and Information Technology, RMIT University, Melbourne, Australia. His research interests include evolutionary computation, machine learning, neural networks, complex systems, multiobjective optimization, data analytics, and swarm intelligence. He serves as an Associate Editor for the journal of IEEE Transactions on Evolutionary Computation, the journal of Swarm Intelligence (Springer), and International Journal of Swarm Intelligence Research. He has received several ARC grants in the past 5 years (Discovery and Linkage), He is the recipient of 2013 SIGEVO Impact Award. Further information can be found from his personal website.
- PhD in Artificial Intelligence, 1998
- Dip.Com in Information Science, 1992
- B.Sc. in Information Science, 1988
- Senior Member, Institute of Electrical and Electronics Engineers (IEEE).
- Member, IEEE Computational Intelligence Society.Vice Chair, Computational Intelligence Chapter, IEEE Victorian Section, Melbourne, Australia
- Member, Steering committee of Simulated Evolution And Learning (SEAL).
- Marzocca, P.,Li, X.,Carrese, R. (2017). Surrogate-assisted multi-swarm particle swarm optimization of morphing airfoils In: Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017), Melbourne, Australia, 31 January-2 February 2017
- Xie, J.,Mei, Y.,Ernst, A.,Li, X.,Song, A. (2017). (In Press) A bi-level optimization model for grouping constrained storage location assignment problems In: IEEE Transactions on Cybernetics, , 1 - 14
- Tamassia, M.,Zambetta, F.,Raffe, W.,Mueller, F.,Li, X. (2017). (In Press) Learning options from demonstrations: A Pac-Man case study In: IEEE Transactions on Computational Intelligence and AI in Games, , 1 - 7
- Li, N.,Cheung, C.,Li, X.,Tu, J. (2017). (In Press) Multi-objective optimization of HVAC system using NSPSO and Kriging algorithms-A case study In: Building Simulation, , 1 - 13
- Zheng, J.,Yu, G.,Zhu, Q.,Li, X.,Zhou, J. (2017). On decomposition methods in interactive user-preference based optimization In: Applied Soft Computing, 52, 952 - 973
- Tang, K.,Wang, J.,Li, X.,Yao, X. (2017). A scalable approach to capacitated arc routing problems based on hierarchical decomposition In: IEEE Transactions on Cybernetics, , 1 - 13
- Qi, Y.,Yu, J.,Li, X.,Wei, Y.,Miao, Q. (2017). Reservoir flood control operation using multi-objective evolutionary algorithm with decomposition and preferences In: Applied Soft Computing, 50, 21 - 33
- Qi, Y.,Guo, H.,Li, X. (2017). Extending the Delaunay triangulation based density measurement to many-objective optimization In: Proceedings of the 3rd Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017), Geelong, Australia, 31 January - 2 February 2017
- Mei, Y.,Omidvar, M.,Li, X.,Yao, X. (2016). A competitive divide-and-conquer algorithm for unconstrained large-scale black-box optimization In: ACM Transactions on Mathematical Software, 42, 1 - 24
- Schellenberg, S.,Li, X.,Michalewicz, Z. (2016). Benchmarks for the coal processing and blending problem In: Proceedings of the 2016 Genetic and Evolutionary Computation Conference, Denver, Colorado, 20-24 July 1016
- An integrated and real-time passenger travel and public transport service information system. Funded by: ARC Linkage Grant pre-2014 Round 2 from (2013 to 2016)
- Enhancing the Australian theme park experience by harnessing virtual-physical play. Funded by: ARC Linkage Grant 2013 from (2013 to 2016)
- Developing an Integrated Optimization Platform for Innovative Design of Composite Fabrication Process. Funded by: ARC Linkage Grant 2013 from (2013 to 2016)
- Novel decomposition methods for large scale optimization. Funded by: ARC Discovery 2012 from (2012 to 2015)
- Improving Genetic Programming for Classification based on a Multiobjective Approach. Funded by: VPAC Expertise Grant pre-2014 from (2004 to 2005)
Note: Supervision projects since 2004
12 PhD Current Supervisions8 PhD Completions
Artificial intelligence; learning algorithms; neural networks; connectionist learning models; evolutionary computation; genetic algorithms; parallel GA; genetic programming; artificial life; complex systems; adaptive systems; emergent behaviours; cellular automata; multi-agent simulation; intelligent agents; swarm intelligence; ant colony algorithms; percolation; self-organized criticality; phase transition.