Professor Jonathan Manton holds the distinguished position of Future Generation Professor in the Department of Electrical and Electronic Engineering at the University of Melbourne. He concurrently serves as an adjunct professor in the Mathematical Sciences Institute at the Australian National University. Manton completed his Bachelor of Science in mathematics and Bachelor of Engineering in electrical engineering in 1995, followed by a Ph.D. in 1998, all at the University of Melbourne. His principal fields of research interest are mathematical systems theory, including signal processing and optimisation; geometry and topology, both differential and algebraic; and learning and computation, encompassing systems biology, neuroscience, and machine learning. As director of MantonLab, he leads transdisciplinary projects applying mathematics and statistics to the analysis of systems and networks—whether living, social, or engineered—with current priorities in optimisation, pulse processing, machine learning, and time-series prediction.

Manton's career includes appointment as full professor in the Research School of Information Sciences and Engineering at the Australian National University in 2005, and a secondment to the Australian Research Council from mid-2006 to mid-2008 as Executive Director, Mathematics, Information and Communication Sciences. He has made significant editorial contributions, serving as Associate Editor for the IEEE Transactions on Signal Processing and Lead Guest Editor for the IEEE Transactions on Selected Topics in Signal Processing. His committee service spans the IEEE Signal Processing for Communications Technical Committee, the IEEE Machine Learning for Signal Processing Technical Committee, the Mathematics Panel for the ACT Board of Senior Secondary Studies, and as Signal Processing Chapter Chair for the IEEE Victorian Section. He was a General Chair for the 2021 IEEE International Workshop on Machine Learning for Signal Processing. Honors include the Queen Elizabeth II Fellowship, Future Summit Australian Leadership Award, Fellowship of the Australian Mathematical Society (FAustMS), and Fellowship of the Institute of Electrical and Electronics Engineers (FIEEE). Key publications comprise 'Optimisation Algorithms Exploiting Unitary Constraints' (IEEE Transactions on Signal Processing, 2002), 'Coordination and Consensus of Networked Agents with Noisy Measurements: Stochastic Algorithms and Asymptotic Behavior' (SIAM Journal on Control and Optimization, 2009), 'Capacity of a Single Spiking Neuron Channel' (Neural Computation, 2009), 'Distributed Principal Subspace Estimation in Wireless Sensor Networks' (Journal of Selected Topics in Signal Processing, 2011), 'Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices' (IEEE Transactions on Information Theory, 2017), and 'A Framework for Generalising the Newton Method and Other Iterative Methods from Euclidean Space to Manifolds' (Numerische Mathematik, 2015).

Professional Email: jmanton@unimelb.edu.au