Save the date: WOMBAT 2022

Save the dates! The next Workshop on Optimisation, Metric Bounds, Approximation and Transversality (WoMBaT2022) will be held 13–16 December 2022 in beautiful Perth, Western Australia. This iteration of wombat will be hosted at Curtin University by Curtin Centre for Optimisation and Decision Science. The event is expected to take place as an entirely in-person event. Registration will open and plenaries will be announced soon.

In addition, this year WOMBAT in collaboration with ARC Training Centre for Transforming Maintenance through Data Science, will host a special day (16th December 2022) focused on the applications of optimization on planning and scheduling maintenance in the resource industry. We are very excited for this special event!

Save the dates! We look forward to welcoming you to Perth!

On behalf of the local organizing committee

Dr. Hoa T. Bui, Curtin Centre for Optimisation and Decision Science
Dr. Scott B. Lindstrom, Curtin Centre for Optimisation and Decision Science

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MoCaO Lectures: Data Science – Second Announcement

July 11-15, 2022

The MoCaO Lectures in Computation and Optimisation for 2022 we are focusing on Data science and in particular machine learning, its algorithms, mathematical foundations and applications. These lectures are designed to be accessible to novices to the field who have a mathematics and computational background, such as PhD students, postdoc and/or inquisitive academics who wish to have a better understanding of recent advances in this dynamic field. These lectures will be given online via Zoom. Please read the notice below regarding the registration.


Speakers:

Prof. Stephen Wright: is the George B. Dantzig Professor of Computer Sciences at the University of Wisconsin-Madison. He is a past chair of the Mathematical Optimization Society and a SIAM Fellow. Currently he directs the Institute for Foundations of Data Science at the University of Wisconsin Madison. Steve is a world-renowned expert in optimization and the author of several highly cited books in this field.

Prof. Guoyin Li: is a professor in the School of Mathematics and Statistics at University of New South Wales. He was awarded an Australian Research Council Future Fellowship (for mid-career researchers) during 2014-2018. His research interests include optimisation, variational analysis, machine learning and tensor computations.

Dr. Quoc Thong Le Gia: is a Senior Lecturer in the School of Mathematics and Statistics, UNSW, Sydney. His research interests include Numerical Analysis, Approximation Theory; Partial Differential Equations; Machine Learning and Stochastic Processes.


Dates:
The 11th , 12th and 13th of July 12noon-1pm: Speaker Prof Stephen Wright
The 14th July 12noon-1pm: Speaker Dr. Quoc Thong Le Gia
The 15th July 12.30pm-2pm: Prof. Guoyin Li


IMPORTANT: Website and Registration:
Due to unforeseen problems with the registration system, all registrations up till until the date 29/06/2022 have been lost. We encourage those who have already registered to reregister using the new google form the bottom of the webpage (so you may receive the zoom details)


MoCaO Lectures:  Data Science – Mathematics of Computation and Optimisation


We apologies for any inconvenience this issue may cause. If you have any enquiries, please send an email to MoCaO@austms.org.au. Please check the website prior to the lectures for last minute information or announcements.

events, Seminars

MoCaO Lectures:  Data Science


Attention: Due to unforeseen problems with the registration system, all registrations up till until the date 29/06/2022 have been lost. We encourage those who have already registered to re-register using the new google form. We apologies for any inconvenience. If you have any enquiries please send an email to MoCaO@austms.org.au. Please check the website prior to the lectures for last minute information or announcements.

 July 11-15, 2022

 We are pleased to announce the inaugural MoCaO Lectures in Computation and Optimisation. For 2022 we are focusing on Data science and in particular machine learning, its algorithms, mathematical foundations and applications. These lectures are designed to be accessible to novices to the field who have a mathematics and computational background, such as PhD students, postdoc and/or inquisitive academics who wish to have a better understanding of recent advances in this dynamic field.

Speakers:

Prof. Stephen Wright:  is the George B. Dantzig Professor of Computer Sciences at the University of Wisconsin-Madison. He is a past chair of the Mathematical Optimization Society and a SIAM Fellow. Currently he directs the Institute for Foundations of Data Science at the University of Wisconsin Madison. Steve is a world renowned expert in optimization and the author of several highly cited books in this field.

Prof. Guoyin Li: is a professor in the School of Mathematics and Statistics at University of New South Wales. He was awarded an Australian Research Council Future Fellowship (for mid-career researchers) during 2014-2018. His research interests include optimisation, variational analysis, machine learning and tensor computations.

Dr. Quoc Thong Le Gia: is a Senior Lecturer in the School of Mathematics and Statistics, UNSW, Sydney. His research interests include Numerical Analysis, Approximation Theory; Partial Differential Equations; Machine Learning and Stochastic Processes.

For more information and registration, got to

MoCaO Lectures:  Data Science – Mathematics of Computation and Optimisation

events

Research Fellow in Last Mile Van Delivery (UniMelb)

Applications close: 29 Jun 2022 11:55 PM AUS Eastern Standard Time
Role type: Full time; Fixed-term until December 2024
Faculty: Faculty of Engineering and Information Technology
Department/School: School of Electrical, Mechanical, and Infrastructure Engineering
Salary: Level A– $77,171 – $104,717  p.a. plus 17% super

About this role: As the Research Fellow, you will be a part of integrating a variety of transport modes to ensure that they are efficient and safe within contemporary parcel distribution networks. This project will develop procedures for designing delivery routes involving a combination of van and walking tours. In this role, you will develop automated techniques for identifying areas for van and walking routes using spatial analysis and modelling tools. 

Link to the details: https://jobs.unimelb.edu.au/caw/en/job/909097?lApplicationSubSourceID=

positions , ,

Senior Lecturer in Applied Mathematics (Newcastle)

Closing date: 16 June 2022
Campus: The University of Newcastle; School of Engineering
Remuneration: $126,446 FTE + 17% superannuation
Status: Permanent

The School of Information and Physical Sciences at the University of Newcastle (Australia) has an open position in Applied Mathematics at Level C (Senior Lecturer).

More details can be found here: https://www.timeshighereducation.com/unijobs/listing/294232/senior-lecturer-in-applied-mathematics/

positions , , , ,

VA & OPT: Alberto De Marchi 

Title: Constrained Structured Optimization and Augmented Lagrangian Proximal Methods

Speaker: Alberto De Marchi (Universität der Bundeswehr München)

Date and Time: Wed May 25 2022, 17:00 AEST (Register here for remote connection via Zoom)

Abstract:

In this talk we discuss finite-dimensional constrained structured optimization problems and explore methods for their numerical solution. Featuring a composite objective function and set-membership constraints, this problem class offers a modeling framework for a variety of applications. A general and flexible algorithm is proposed that interlaces proximal methods and safeguarded augmented Lagrangian schemes. We provide a theoretical characterization of the algorithm and its asymptotic properties, deriving convergence results for fully nonconvex problems. Adopting a proximal gradient method with an oracle as a formal tool, it is demonstrated how the inner subproblems can be solved by off-the-shelf methods for composite optimization, without introducing slack variables and despite the appearance of set-valued projections. Illustrative examples show the versatility of constrained structured programs as a modeling tool and highlight benefits of the implicit approach developed. A preprint paper is available at arXiv:2203.05276.

Seminars

Lecturer, Analytics and Statistics – applications close on Sunday, 5th of June (RMIT)

An opportunity now exists to join RMIT’s School of Science and contribute to the teaching and research growth within the Mathematical Sciences Discipline, in the School of Science and specifically within the field of Mathematics and Statistics.

•            Lecturer, Analytics and Statistics – applications close on Sunday, 5th of June

RMIT External

https://rmit.wd3.myworkdayjobs.com/en-US/RMIT_Careers/job/Melbourne/Lecturer-Senior-Lecturer–Analytics-and-Statistics_JR7401

•            Lecturer, Mathematics – applications close on Sunday, 5th of June

RMIT External

https://rmit.wd3.myworkdayjobs.com/en-US/RMIT_Careers/job/Melbourne/Lecturer–Mathematics_JR10721

news, positions

VA & OPT: Mareike Dressler 

Title: Algebraic Perspectives on Signomial Optimization

Speaker: Mareike Dressler (University of New South Wales)

Date and Time: Wed May 11 2022, 17:00 AEST (Register here for remote connection via Zoom)

Abstract:

Signomials are obtained by generalizing polynomials to allow for arbitrary real exponents. This generalization offers great expressive power, but has historically sacrificed the organizing principle of “degree” that is central to polynomial optimization theory. In this talk, I introduce the concept of signomial rings that allows to reclaim that principle and explain how this leads to complete convex relaxation hierarchies of upper and lower bounds for signomial optimization via sums of arithmetic-geometric exponentials (SAGE) nonnegativity certificates. In the first part of the talk, I discuss the Positivstellensatz underlying the lower bounds. It relies on the concept of conditional SAGE and removes regularity conditions required by earlier works, such as convexity of the feasible set or Archimedeanity of its representing signomial inequalities. Numerical examples are provided to illustrate the performance of the hierarchy on problems in chemical engineering and reaction networks. In the second part, I provide a language for and basic results in signomial moment theory that are analogous to those in the rich moment-SOS literature for polynomial optimization. That theory is used to turn (hierarchical) inner-approximations of signomial nonnegativity cones into (hierarchical) outer-approximations of the same, which eventually yields the upper bounds for signomial optimization. This talk is based on joint work with Riley Murray.

Seminars

VA & OPT: Lars Grüne

Title: The turnpike property: a classical feature of optimal control problems revisited

Speaker: Lars Grüne (University of Bayreuth)

Date and Time: Wed May 04 2022, 17:00 AEST (Register here for remote connection via Zoom)

Abstract:

The turnpike property describes a particular behavior of optimal control problems that was first observed by Ramsey in the 1920s and by von Neumann in the 1930s. Since then it has found widespread attention in mathematical economics and control theory alike. In recent years it received renewed interest, on the one hand in optimization with partial differential equations and on the other hand in model predictive control (MPC), one of the most popular optimization based control schemes in practice. In this talk we will first give a general introduction to and a brief history of the turnpike property, before we look at it from a systems and control theoretic point of view. Particularly, we will clarify its relation to dissipativity, detectability, and sensitivity properties of optimal control problems in both finite and infinite dimensions. In the final part of the talk we will explain why the turnpike property is important for analyzing the performance of MPC.

Seminars
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