Workshop “Scientific computation using machine-learning algorithms: recent mathematical advances and applications” 25-26 April 2019, University of Nottingham, UK

Workshop “Scientific computation using machine-learning algorithms: recent mathematical advances and applications”, 25-26 April 2019, University of Nottingham UK

Over the past decade machine-learning and neural-network methodologies have matured tremendously in the areas of computer vision, language processing and data science, and have given rise to highly innovative and efficient algorithms for a wide-range of data-intensive applications. Theoretical understanding of this remarkable performance of machine learning methodologies is an emerging topic in mathematical research. On the other hand, it has been recognised only recently that these learning methodologies lead to new solution paradigms for the computational applied sciences, with significantly more efficient algorithms and the potential to cause a step change in designing solution techniques for large-scale problems.

The aim of this workshop is to discuss recent advances in mathematical foundations of machine learning and artificial neural networks as well as the application of these methodologies in computational science. The workshop will bring together experts in such diverse areas as approximation theory, PDEs, scientific computing, networks, computer science, and uncertainty quantification to facilitate the exchange of results and ideas and to initiate new collaborations.

Confirmed speakers:

Martin Eigel (WIAS, Germany)

Ahmed Elsheikh (Heriot Watt University, UK)

Jan Hesthaven (EPFL, Switzerland)

Desmond Higham (University of Strathclyde, UK)

Jakub Marecek (IBM Dublin, Ireland)

Kaj Nystrom (Uppsala University, Sweden)

Ivan Oseledets (Skoltech, Russia)

Philipp Petersen (University of Oxford, UK)

The programme will include a small number of contributed talks. Participants wishing to present a contributed talk are invited to submit a title and a short abstract (maximum 1 page) by sending an email to

Deadline for abstract submission: 31 March 2019

Deadline for registration: 15 April 2019

Detailed information about the meeting is on the web-page:

SIAM UKIE National Student Chapter conference, Manchester, June 2019

SNSCC19_poster-1The University of Manchester SIAM-IMA Student Chapter would like to invite you all to the 2019 SIAM UKIE National Student Chapter Conference (SNSCC19).  The conference will be a two-day event, on the 10th-11th June and will take place at the Alan Turing Building at the University of Manchester.

The aim of this conference is to bring together students working in all areas of applied and industrial mathematics across the UK and Ireland. It will also provide opportunities for students to showcase their research, and to hear talks from distinguished plenary speakers. We are proud to announce that this years speakers are:

Prof. Andrew Wathen (Mathematical Institute, University of Oxford)

Dr Aretha Teckentrup (School of Mathematics, University of Edinburgh)

Prof. Magnus Rattray (Data Science Institute, University of Manchester)

Dr Leonardo Robol (Department of Mathematics, University of Pisa)

We will have sessions for contributed talks and posters, and invite submissions from all students interested in presenting their work. The deadline for speaker and poster applications is Friday 19th April and the link for submission can be found at the conference website here. Successful applicants will be notified by email on Monday 29th April. The deadline for general registration is Friday 24th May.

Thanks to the generous support of our sponsors, we’re excited to announce that the prizes for the best student speaker will be a HP laptop and for the best student poster will be a Fitbit Blaze. Runners up will each receive a £150 Amazon voucher. We can also offer a limited number of hardship bursaries (each worth £50) to help student speakers attend the SNSCC. More information on how to apply for a bursary can be found on the conference website.

If you require further information or for general enquiries, please contact the organising committee at

We look forward to welcoming you in June!

Report on the 23rd Annual Meeting of the SIAM UK and Republic of Ireland Section

The 23rd Annual Meeting of the SIAM UK and Republic of Ireland Section was held on Friday 11th of January 2019 at the Mathematical Institute at the University of Oxford. Around 90 participants attended the meeting.

The invited speakers were: Lisa Fauci (Tulane University, Incoming SIAM President), Des Higham (Strathclyde University), Carola-Bibiane Schoenlieb (IMA sponsored speaker, University of Cambridge), Kirk Soodhalter (Trinity College Dublin)and Konstantinos Zygalakis (University of Edinburgh), and brief summaries of their lectures are given below.

The meeting also included a poster session for PhD students and postdocs, held over lunchtime, and a preceeding `poster blitz’ where each poster presenter gave a brief summary of their work.

At the end of the meeting, four prizes for best poster were awarded to Abigail Cocks (University of Nottingham), James Fannon (University of Limerick), Yury Korolev (University of Cambridge) and Carolina Urzua-Torres (University of Oxford).

Attendees of the meeting enjoyed the excellent facilities of the Andrew Wiles Building
at the Mathematical Institute, University of Oxford, and excellent lunch and refreshments. The local organisation was handled most ably by Dr Alberto Paganini and Dr Abdul-Lateef Haji-Ali.

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Des Higham gave a talk with the intriguing title: `Our Friends are Cooler than Us‘. He started by explaining the `Friendship Paradox’ (first identified by Scott Field) which essentially says that `on average our friends have more friends than we do’. This is obtained by analysing graphs which model individuals as nodes and friendships as edges. He went on to explain how this can be applied to any mutual pairwise
interactions, for example the `Happiness paradox’ – which asserts that our friends are happier than us on average, and how the concept is useful as a method of informing immunization strategies. He then went on to describe the abstraction of this idea into the more general concept of node centrality, and the associated `centrality paradox’ and gave examples arising in general principles of linear algebra applied to graphs, such as the eigenvector calculation leading to the Fiedler vector of a graph.

The meeting welcomed Lisa Fauci on one of the first official engagements of her SIAM Presidency. Lisa’s title was`Complex dynamics of fibers in flow at the microscale‘. She started by showing experiments detailing the behaviour of micro-organisms (e.g. sperm cells, E. Coli or diatom chains) immersed in fluids. She described theoretical work on the role of flexibility in diatom chains and explained the difficulty of computation of elastic properties of such complex media in the microscopic context. She then described mathematical work on the modeling of fibers in flow governed by the Navier-Stokes and Stokes equations, in the latter case using boundary potentials and fast summation techniques for speeding up the computation of the composite potential. The talk then went on to present beautiful computational simulations and to describe their relation to lab experiments for several examples including helical swimmers, passive fibers in shear flow and in straining flow.

Kirk Soodhalter talked on `Augmented Arnoldi-Tikhonov Methods for Ill-posed Problems‘. Using a motivating example from image deblurring, the speaker described the ill-posed problem of determining a sharp image from blurred and noisy input data. Given that the problem size of these types of problems is large, the focus was on the use of iterative methods and in particular on projection approaches to update the approximation of the solution vector. Due to the ill-conditioning of the linear systems, some form of regularisation is needed to be able to compute a useful approximation and Tikhonov regularisation was considered. The idea of the augmented approach is to use a low-dimensional user-supplied subspace to augment the projection space. The augmented subspace is constructed from vectors which are able to represent known
features of the desired solution. The talk concluded with a numerical example indicating the improved performance of the augmented method for a problem containing a step discontinuity.

Konstantinos Zygalakis gave a talk on `Explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems‘.  This talk explored how ordinary and stochastic differential equations can be used as a basis for designing algorithms to solve optimisation and sampling tasks in Bayesian inverse problems. These kinds of problems frequently appear in applied mathematics and machine learning, for example
in the context of imaging. Utilising the connection to (stochastic) differential equations allows for the design of novel optimisation and sampling algorithms based on the numerical analysis of differential equations. The talk showed how a gradient flow naturally leads to optimisation algorithms, and how Langevin dynamics can be used for sampling. The focus of the talk was on incorporating sophisticated numerical time stepping methods with good stability properties in order to obtain computationally efficient algorithms. This is of great importance in problems of practical interest, where the objective function is often very high-dimensional and expensive to evaluate.

The final talk of the day was by Carola-Bibiane Schoenlieb (the IMA sponsored speaker), whose title was `Variational models and partial differential equations for mathematical imaging‘. The talk started by framing inverse image analysis problems within a variational context. Such problems are inherently ill-posed and require some form of regularisation. An example using total variation regularisation was given for a problem involving the use of undersampled magnetic resonance tomography data. Further examples were presented including the segmentation and classification of biological cells as they change morphology during the cell cycle. The developed algorithm and software is being used by biologists in the development of anti-mitotic treatments for cancer. The talk also highlighted the myriad of mathematical and numerical challenges in the area of imaging and suggested that future hybrid methods would possibly involve a combination with machine learning.

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Postdoc position, University of Edinburgh

Applications are invited for a 3-year postdoctoral position as part of an EPSRC project in the area of numerical linear algebra for PDE-constrained optimisation problems, with applications to data science. The successful candidate will join the research group of Dr John Pearson in the School of Mathematics, University of Edinburgh.

The project is funded by the EPSRC Grant “Modern Linear Algebra for PDE-Constrained Optimisation Models for Huge-Scale Data Analysis”, and by the University of Edinburgh. The successful candidate will contribute to the development of numerical methods and iterative solvers for huge-scale matrix systems arising from optimisation problems with PDE constraints, and will apply their techniques to cutting-edge problems from data science. Experience with PDE-constrained optimisation/inverse problems, and/or numerical methods for PDEs (including numerical linear algebra for solving matrix systems), is desirable. Expertise in a relevant programming language (e.g., Python, C++, MATLAB) is essential.

The position should be taken up in September 2019, or an alternative date by mutual agreement. Further particulars, as well as the application link, may be found at

Informal enquiries are encouraged, and may be made to John Pearson at The closing date for applications is 5pm on 22 January 2019.

InFoMM 2018 UK Graduate Modelling Camp, Mathematical Institute, University of Oxford, 2-5 April, 2019

The EPSRC Centre for Doctoral Training in Industrially Focused Mathematical Modelling (InFoMM CDT) is now accepting applications for the InFoMM 2018 UK Graduate Modelling Camp, Mathematical Institute, University of Oxford, 2-5 April, 2019.

The UK Graduate Modelling Camp is a 4-day workshop that aims to provide participants with hands-on experience of mathematical modelling under the guidance of experienced instructors.

The Camp is open to PhD students in numerate disciplines and is designed to promote a broad range of problem-solving skills, such as mathematical modelling & analysis, scientific computation, and critical assessment of solutions.

The mentors for the 2019 edition of the event will be

Radu Cimpeanu, Oxford

Susana Gomes, Warwick

Huaxiong Huang, Toronto

Katerina Kaouri, Cardiff

Nicos Pavlidis, Lancaster

For further information, and to apply, please visit

Applications close on 31 January 2019, and we have a number of Oxford-funded bursaries to cover up to 50% of the residential attendee charge.

Registration now open for 2019 SIAM-UKIE annual meeting

Registration is now open for the 23rd  Annual Meeting of the SIAM UKIE Section, taking place at

The Mathematical Institute, University of Oxford on Friday 11th of January 2019.

The meeting features five invited speakers and a poster session. We will also have a “poster blitz” session and offer travel support to students and postdocs presenting posters.

The confirmed invited speakers are:

Lisa Fauci, Tulane University, Incoming SIAM President

Des Higham,  Strathclyde University

Carola-Bibiane Schoenlieb, University of Cambridge

Kirk Soodhalter, Trinity College Dublin

Konstantinos Zygalakis, University of Edinburgh

To register, please visit

Heilbronn Fellowships in Mathematics at Manchester (3 positions)

The School of Mathematics at the University of Manchester has three Helibronn Fellowships in Mathematics available, in association with the Heilbronn Institute for Mathematical Research. Experience in Algebra or Numerical Linear Algebra, interpreted broadly, is preferred. The Fellowships last for three years, starting in October 2019 or at a mutually agreed alternative date. The The salary is £37,345 to £42,036 per annum (according to relevant experience) plus a supplement of £3500 per annum, and at least £2,500 per annum is available for research expenses.

The Heilbronn Institute for Mathematical Research (HIMR) is a major national centre which works in collaboration with universities and Government Communication Headquarters (GCHQ) to support mathematics research. It employs more than 30 Heilbronn Fellows, who divide their time between academic research and work for GCHQ. The Institute also runs a highly successful programme of events to promote and further the cause and understanding of advanced mathematical research. These include conferences, focused research groups and workshops. It is named after Professor Hans Heilbronn FRS, who was a major contributor to UK mathematics.

The Heilbronn Fellowship holders will divide their time equally between their own academic research (in the School of Mathematics at the University) and the research programme of the Heilbronn Institute. The Institute’s work offers opportunities to engage in collaborative work as well as individual projects.

The closing date is November 11, 2018. More information about the Heilbronn Fellowship in Mathematics is available in the advert and further particulars here, which also describe security requirements attached to these posts.