We warmly invite researchers and students working in optimisation theory, algorithms, and applications to present their work in the Optimisation Session at the 70th Annual Meeting of the Australian Mathematical Society (AustMS2026).

Location: University of Western Australia, Perth

Dates: 1-4 December 2026

Early-bird registration deadline: 26 October 2026

Abstract submission deadline: 1 November 2026

Registration and further information: https://austms2026.org.au/registration/

Announcements about the session’s keynote speakers will follow soon. Attendees can also look forward to a plenary lecture by our very own Vera Roshchina.

The session “Modern Optimisation at Scale: Theory, Computation, and Applications” will be held as part of the 23rd Biennial Computational Techniques and Applications Conference (CTAC 2026). The session will showcase recent theoretical, algorithmic, and computational advances in optimisation.

Important information:

• When: 8–11 December 2026
• Where: University of Sydney
• Talk length: 25 minutes
• Expressions of interest: Researchers interested in presenting are invited to contact the session organisers by 11 September 2026, briefly indicating their affiliation and proposed topic.

Session organisers: Dmytro Matsypura (dmytro.matsypura@sydney.edu.au), Guoyin Li (g.li@unsw.edu.au), and Neil Dizon (n.dizon@unsw.edu.au).

For further information about the conference, please visit: https://www.sydney.edu.au/science/schools/school-of-mathematics-and-statistics/research/computational-techniques-and-applications-conference-2026.html

Dear MoCaO members.

The timetable for MoCaO lectures (July 27–31, 2026) is as follows:

• Lindon Roberts: Mon, Tues & Wed at 2pm AEST, slides: Lecture 1, Lecture 2, Lecture 3
• Zaikun Zhang: Thurs 11am AEST (Wed 9pm in the US), slides
• Sara Shashaani: Fri 11am AEST (Thurs 9pm in the US)

https://unimelb.zoom.us/j/83296305688?pwd=pGe6NdAVKxOCwgVFYa85LjrfUp6fUm.1
Password: 867212

Title: Model-Based Derivative-Free Optimization: Algorithms and Approximation Theory

Abstract:

Derivative-free optimization (DFO) refers to nonlinear optimization algorithms that do not rely on the availability of gradient or Hessian information. It is primarily designed for settings when functions are black-box, expensive to evaluate and/or noisy, relevant to applications including climate science and quantum computing. A widely used and studied class of DFO methods for local optimization is model-based DFO (MBDFO), where the general principles from nonlinear optimization algorithms are followed, but with local approximations to the objective constructed by polynomial interpolation (rather than, e.g. Taylor series). In these lectures, we will cover the foundational approximation theory and algorithms behind MBDFO, and look at recent extensions to constrained and noisy problems. The lecture by Zaikun Zhang (Sun Yat-sen University) will consider MBDFO in subspaces to handle high-dimensional problems, and Sara Shashaani (North Carolina State University) will discuss adaptive sampling MBDFO methods for stochastic problems.

Other presenters: Dr. Lindon Roberts, The University of Melbourne

Numerical Computations: Theory and Algorithms

The 5th International Conference and Summer School

June 21 – 27, 2026

NUMTA 2026 – NUMTA Conference on Numerical Computations: Theory and Algorithms. Explore program details, plenary speakers, deadlines, registration, and publications for the upcoming edition.

Falkensteiner Garden Calabria, Italy

In cooperation with

SigmaOpt, the optimisation special interest group of ANZIAM, is
holding a one-day workshop on the day after the 2026 ANZIAM
Conference. The workshop will feature talks from five invited
speakers as well as the Winner of the Student Best Paper Prize.
Friday February 13, 2026, Australian National University, Canberra
Registration $50

Invited speakers:
Hoa Bui (Curtin)
Philipp Braun (ANU)
Bethany Caldwell (UNSW)
Mahdi Abolghasemi (QUT)
James Nichols (Macquarie Bank/ANU)
The Winner of the Student Best Paper Prize (TBA) – see call below
SigmaOpt/MoCaO Student Best Paper Prize

SigmaOpt and MoCaO call for nominations for the joint SigmaOpt/MoCaO Student Best
Paper Prize for an exceptional paper in the field of mathematical optimisation, optimal
control, operations research or related field published in the last 18 months. The winner of
this prize will be awarded $300 and invited to present the paper at the workshop. For
information on submitting a nomination, visit:

https://www.anziam.org.au/SIGMAOPT

Workshop poster