Events

We are happy to announce that a Winter School "Foliations, pseudodifferential operators and groupoids" will be held at University of Göttingen from 29. February to 4. March 2022. There will be 3 lectures given by : Claire Debord, Institut de Mathématiques de Jussieu - Paris Rive Gauche, Madeleine Jotz, Universität Würzburg, Victor Nistor, Université de Lorraine. We will also have problem and question sessions led by Iakovos Androulidakis (University of Athens). We kindly ask you to bring this to the attention of interested PhD students and postdocs. This Winter School is funded by the Research Training Group 2491. Partial financial support is available to cover the accommodation of some participants. You can find updated information and the registration link on the webpage of the event: https://www.uni-goettingen.de/rtg2491/winterschool On behalf of the organizers, Jérémy Mougel, Leonid Ryvkin, Thomas Schick.

Discrete mathematics is a branch of the mathematical sciences which poses a wide range of challenging research problems in its own right and gives rise to important applications in other fields. This 3rd IMA conference on discrete mathematics, following on from the previous two at Derby, will consider a range of aspects of discrete mathematics, both pure and applied. It is open to researchers working with mathematical structures and abstract constructs, and to those involved in the theory and practice of discrete mathematics. Results which establish links between different areas of discrete mathematics are welcomed, as are applications and the development of new tools. The purpose of this event is to highlight progress in the field through the development of novel theories, methodologies, and applications accordingly, and to inspire future work.

The main aim of the Conference is to present new theoretical and methodological results and significant applications in Insurance and Finance by means of the capabilities of the interdisciplinary mathematical-statistical approach. The Steering Committee of the Conference would appreciate very much if you could collaborate in the success of the conference by participating in some activities such as the organization of sessions and/or the presentation of contributions (also through a co-author).

Inverse problems are widespread in many varied fields such as medical and satellite imaging, biology, astronomy, geophysics, environmental sciences, computer vision, energy, finance, and defence. These problems are inverse in the sense that they arise from seeking to use a mathematical or physical model “backwards” to indirectly determine a quantity of interest from the effect that this quantity causes on some observed data. A main challenge resulting from using models “backwards” to measure causes from their effects is that solutions are often not well posed, i.e., not unique and/or unstable with respect to small perturbations in the data. This difficulty has stimulated an important amount of research and innovation at the interface of applied mathematics, statistics, engineering, physics, and other fields, leading to great social and economic benefit through impact on science, medicine, and engineering.

Signal processing and machine learning constitutes an important area for the application of mathematical concepts and techniques, in an era where learning algorithms must be transparent, robust, explainable and understandable, and ethical. It is a thriving area, as demonstrated by the success of the UK hosting the recent International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in Brighton in 2019. Signal and information processing is at the heart of our technological world, fuelled by developments in, for example, mobile communications, networks and graphs, multimedia systems, medical image analysis, genomics and bioengineering, neural signal processing, big data processing and internet of things. The aim of the conference is to bring together mathematicians, statisticians and engineers with a view to exploring recent developments in mathematics for signal processing and machine learning and identifying fruitful avenues for further research. It is hoped that the meeting will help to attract more mathematicians into this important and challenging field.

The goals of this conference are to bring together internationally renowned researchers working on various topics related to stochastic analysis and, particularly, to the theory and applications of stochastic partial differential equations, and to expose and attract graduate students and young researchers to this steadily growing area.

This conference on financial mathematics will be focusing on pressing challenges in finance and insurance produced by climate change, demographic developments, and the ever-increasing dominance of data and information. Alongside the challenges, this three-day conference’s goal will devote time to the role and responsibilities financial and insurance mathematics have in developing solutions and in assisting with transitions necessary to mitigate irreversible adverse environmental and socio- economic impact. The aim is to promote interdisciplinary cooperation bridging mathematics, statistics and computer science with finance, climate science, insurance and economics. Industry professionals and members of government agencies will be invited to share their experience and expertise alongside academic experts in the field in order to scope out the most urgent research directions with the highest potential for incisive solutions.

The success of modern codes for large-scale optimization is heavily dependent on the use of effective tools of numerical linear algebra. On the other hand, many problems in numerical linear algebra lead to linear, nonlinear or semidefinite optimization problems. The purpose of the conference is to bring together researchers from both communities and to find and communicate points and topics of common interest. This Conference has been organised in cooperation with the Society for Industrial and Applied Mathematics (SIAM).