Evolutionary Machine Learning:

Research, Applications and Challenges

Mengjie Zhang, Victoria University of Wellington

Abstract: Since the 1990s, evolutionary computation techniques have been widely used to solve machine learning tasks. In this talk, I will firstly provide a brief overview of machine learning and evolutionary computation, then focus on the main paradigms of evolutionary machine learning and their success in classification, feature selection, regression, clustering, computer vision and image analysis, scheduling and combinatorial optimisation, and evolutionary deep learning. The main challenges and applications will be discussed. If time allows, I will provide an overview of our recent work and discuss potential opportunities. 

Professor Mengjie Zhang

Mengjie Zhang is a Fellow of Royal Society of New Zealand, a Fellow of Engineering New Zealand, a Fellow of IEEE, an IEEE Distinguished Lecturer, currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation and Machine learning Research Group. He is the Associate Dean (Research and Innovation) for the Faculty of Engineering, and also leading the strategic initiative for Data Science and Artificial Intelligence at the University.

His research is mainly focused on AI, machine learning and big data, particularly in evolutionary computation and learning, feature selection/construction and big dimensionality reduction, computer vision and image analysis, scheduling and combinatorial optimisation, classification with unbalanced data and missing data, and evolutionary deep learning and transfer learning. Prof Zhang has published over 800 research papers in refereed international journals and conferences. He has been serving as an associated editor for over ten international journals including IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, the Evolutionary Computation Journal (MIT Press), and involving major AI and EC conferences as a chair such as GECCO, IEEE CEC, EvoStar, IJCAI, AAAI, PRICAI, PAKDD. He has also been serving as a steering committee member and a program committee member for over 100 international conferences. Since 2007, he has been listed as one of the top ten (currently No. 4) world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html).

Prof Zhang is currently the Chair of the IEEE CIS PubsCom Strategic Planning (sub)Committee, the Chair of the IEEE CIS Outstanding PhD Dissertation Award (sub)Committee, a past Chair of the IEEE CIS Intelligent Systems Applications Technical Committee, the IEEE CIS Emergent Technologies Technical Committee and the IEEE CIS Evolutionary Computation Technical Committee, and the founding chair of the IEEE Computational Intelligence Chapter in New Zealand.