Matthew K. Tam

Matthew K. Tam is an Associate Professor at the School of Mathematics and Statistics, The University of Melbourne, specializing in Operations Research. He is also an investigator at the Melbourne Centre for Data Science and an associate investigator in the ARC Training Centre OPTIMA.

• PhD in Mathematics (2016) from University of Newcastle under Jonathan Borwein
• Postdoctoral research at University of Göttingen with RTG-2088 and Alexander von Humboldt Foundation
• Junior Professor at University of Göttingen (2017-2020)

His research focuses on continuous optimization, monotone operator theory, and variational analysis, with applications in wavelet construction and inverse problems. Key trends include distributed algorithms, resolvent splitting, and convergence analysis for feasibility problems.

• Discovery Early Career Researcher Award (DECRA)
• Alexander von Humboldt Fellowship

He collaborates with institutions like ANZIAM, Springer, and IEEE, with publications spanning mathematical optimization, harmonic analysis, and computational mathematics. His work emphasizes algorithmic design for complex data systems and real-world applications in imaging and industrial modeling.