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Background

Professor Jonathan Manton holds a Distinguished Chair at the University of Melbourne with the title Future Generation Professor. He is also an adjunct professor in the Mathematical Sciences Institute at the Australian National University, a Fellow of the Australian Mathematical Society (FAustMS) and a Fellow of the Institute of Electrical and Electronics Engineers (FIEEE).

He received his Bachelor of Science (mathematics) and Bachelor of Engineering (electrical) degrees in 1995 and his Ph.D. degree in 1998, all from The University of Melbourne, Australia.

In 2005 he became a full Professor in the Research School of Information Sciences and Engineering (RSISE) at the Australian National University. From mid-2006 till mid-2008, he was on secondment to the Australian Research Council as Executive Director, Mathematics, Information and Communication Sciences.

He has served as an Associate Editor for the IEEE Transactions on Signal Processing and a Lead Guest Editor for the IEEE Transactions on Selected Topics in Signal Processing. He has been a Committee Member of the IEEE Signal Processing for Communications (SPCOM) Technical Committee, and a Committee Member on the Mathematics Panel for the ACT Board of Senior Secondary Studies in Australia. Currently he is a Committee Member of the IEEE Machine Learning for Signal Processing (MLSP) Technical Committee, and is the Signal Processing Chapter Chair for the IEEE Victorian Section.

Awards include a prestigious Queen Elizabeth II Fellowship and a Future Summit Australian Leadership Award.

Principal Fields of Interest

• Mathematical Systems Theory, including Signal Processing and Optimisation
• Geometry and Topology, both Differential and Algebraic
• Learning and Computation, including Systems Biology, Neuroscience and Machine Learning.

Work Address

Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria 3010 Australia.
j.manton@unimelb.edu.au

Selected Articles

• Manton, J. H. (2002). Optimisation Algorithms Exploiting Unitary Constraints. IEEE Transactions on Signal Processing, 50(3), pp. 635–650.
• Huang, M. and Manton, J. H. (2009). Coordination and Consensus of Networked Agents with Noisy Measurements: Stochastic Algorithms and Asymptotic Behavior. SIAM Journal on Control and Optimization, 48(1), pp. 134–161.
• Ikeda, S. and Manton, J. H. (2009). Capacity of a Single Spiking Neuron Channel. Neural Computation, 21(6), pp. 1714–1748.
• Li, L., Scaglione, A. and Manton, J. H. (2011). Distributed Principal Subspace Estimation in Wireless Sensor Networks. Journal of Selected Topics in Signal Processing, 5(4), pp. 725–738.
• Said, S., Bombrun, L., Berthoumieu, Y. and Manton, J. H. (2017). Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices. IEEE Transactions on Information Theory, 63(4), pp. 2153–2170.
• Manton, J. H. (2015). A Framework for Generalising the Newton Method and Other Iterative Methods from Euclidean Space to Manifolds. Numerische Mathematik, 129(1), pp. 91–125.