Mathematician Mareike Dressler receives ARC Discovery Early Career Researcher Award

Congratulations to Dr Mareike Dressler of the School of Mathematics and Statistics, who has been awarded an Australian Research Council Discovery Early Career Researcher Award (DECRA).

For this current round, the Australian Research Council (ARC) is supporting 200 new early career research projects with more than $86 million in funding. 14 of the 200 projects were awarded to early career researchers at UNSW, and nine allocated to researchers in the mathematical sciences Australia-wide.

"I’m very excited to receive an ARC Discovery Early Career Research Award, and incredibly grateful for this investment in mathematical optimisation", said Dr Dressler. "This fellowship will help me with strengthening my existing international links and forging new scientific collaborations. It provides an excellent opportunity to enrich the scope of optimisation in Australia."

Dr Dressler joined UNSW's School of Mathematics and Statistics as a Lecturer in early 2022. She completed her PhD at the Goethe University Frankfurt/Main in 2018 and has held positions at the Institute for Computational and Experimental Research in Mathematics (U.S.); the University of California, San Diego; and the Max Planck Institute for Mathematics in the Sciences in Germany. 

"ARC DECRAS are one of the most prestigious awards for early career researchers", said Head of Applied Mathematics, Professor Thanh Tran. "Congratulations Mareike for this excellent achievement! Your work on large scale polynomial optimisation, which combines novel theory of algebraic geometry and convex optimisation, will lay a solid mathematical foundation for novel computational methods in polynomial optimisation."

The DECRA supports Dr Dressler's project, New Frontiers in Large-Scale Polynomial Optimisation:
Polynomial optimisation is ubiquitous in many areas of engineering and applied mathematics. The mathematical methods and algorithms used for polynomial problems of large size are not sufficiently developed, limiting their applicability for real-world problems.
This project aims to develop a mathematical foundation and computational methods for large-scale polynomial optimisation. By using an innovative combination of a novel theory of algebraic geometry and convex optimisation, this project expects to generate new knowledge and tools for solving these problems.
Anticipated outcomes include a new generation of large-scale optimisation technologies, providing significant benefit to Australia's industries and international research standing.