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This programme cross-cuts all other Newton Gateway to Mathematics programmes and and activities and relationships with stakeholders in the area are constantly evolving and developing. The Newton Gateway works as a delivery partner with the Cantab Capital Institute for the Mathematics of Information (CCIMI)  on end-user engagement and interaction. CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data, including in the financial markets. 

Upcoming Events

Updates will be available in due course. 

Previous Activities

Optimisation Training for Industry took place on 3rd, 10th and 17th May 2022. The Newton Gateway is implementing a number of short intensive training courses in mathematical areas of relevance to individuals in industry, business and government. These courses provided technical training in the subject matter with an emphasis on practical applications of mathematics. In collaboration with NATCOR, we developed our second training course which focused on Optimisation for Industry, more specifically, for Data Scientists/Machine Learning. This training course took place over 3 days in a hybrid teaching format. The first day of the course took place physically at the Isaac Newton Institute, followed by 2 virtual sessions.

LMS Invited Lectures on the Mathematics of Deep Learning, 28th February - 4th March 2022. This workshop featured an introductory lecture series across the week, by Professor Gitta Kutyniok (LMU, Munich) on the mathematics of deep learning. Four accompanying lectures have also been given.The workshop aimed to provide a mathematical foundation of deep learning by an introduction to the main mathematical questions and concepts of deep neural networks and their training within two realms -

  • Theoretical foundations of deep learning independent of a particular application
  • Theoretical analysis of the potential and the limitations of deep learning for mathematical methodologies, in particular, for inverse problems and partial differential equations.

Machine Learning Training for Industry took place on 3rd, 10th & 17th November 2021. The Newton Gateway proposes to implement a number of short intensive training courses (2-3 days) in mathematical areas of relevance to individuals in industry, business and government. We envisage that these courses will provide technical training in the subject matter with the emphasis on practical applications of mathematics.

The first training focused on machine learning using Python programming language and took place over 3 days in a hybrid teaching format. The first day of the course, Wednesday 3rd November, took place physically at the Isaac Newton Institute, followed by 2 virtual sessions on Wednesday 10th and Wednesday 17th November 2021. This course provided delegates with essential skills in implementing machine learning algorithms for clustering, classification and predictive analytics using Python programming language and its ecosystem of machine learning libraries including (but not limited to) statsmodels, scikit-learn, h2o and SciPy.

Cantab Capital Institute for the Mathematics of Information – Industry Engagement took place on 24th November 2021. This annual industry engagement event brought together those academics working to advance data science and aimed to showcase the research that is being carried out at the Institute and enable delegates to hear more detail about some of the current project collaborations and industry challenges that CCIMI is exploring. It was held as a hybrid event with some attending at INI and others joining virtually.

5th Edwards Symposium - Future Directions in Soft Matter​ took place from Wednesday 8th September 2021 to Friday 10th September 2021. This was the fifth year in the Edwards Symposium Series, funded in part by ongoing generous support from Unilever, which continues until 2022 (the fifth event having been postponed from 2020). A key aim of the Edwards Symposium Series is to highlight the latest developments in soft matter science with a particular (but not exclusive) emphasis on theoretical and mathematical models, and on how these models can inform industrial processes, materials, and design. Leading academic speakers convey their latest scientific work, aiming to foster collaborative and interdisciplinary discussions across the industry/academia boundary.​

In 2021, the workshop focused on the following soft matter areas:

  • Polymer melt dynamics and process rheology

  • Informatic approaches to soft matter

  • Functional gels

  • Soft matter for sustainable foods.​

The new CMIH Centre for the Mathematics of Information held its first engagement event on 4th - 5th May 2021. The EPSRC Cambridge Mathematics of Information in Healthcare (CMIH) Hub was launched in 2020. It focuses on some of the most challenging public health problems of our time, including Cancer, Cardiovascular Disease and Dementia. There is a core mathematical component that is common to data challenges across these clinical disciplines, which the Hub will evaluate and address through its interdisciplinary collaborations. The overarching objective is to develop data analytics algorithms and provide the associated theory that is directly linked to the requirements in the clinic for healthcare decision making.

This was the first external event of the CMIH Hub and aimed to bring together those working in mathematical healthcare data analytics across the UK, including academic, clinical, and industrial users with mathematicians working in similar areas.The event included talks that highlighted open challenges and successes from CMIH Hub researchers and presented other potential collaborative opportunities, as well as projects being developed elsewhere related to healthcare data analytics.

The Flip Side of the Pandemic: Recent Advances in the Mathematics of Information  took place on 20th May 2021.This half day conference brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI specifically related to understanding and modelling the Coronavirus pandemic and associated challenges. Additionally, it highlighed other potential collaborative opportunities, as well as projects being developed elsewhere related to data analysis.There will be a session of short “elevator pitches” from next generation researchers as well as a poster session by some registered delegates which took place using GatherTown. 

Unlocking Data Streams on 16th March 2021 highlighted a number of exciting research activities and outline some of the successful collaborations within the DataSıg Programme – which looks to address this key challenge of data science, to better understand multimodal data streams.
Sequential streams of information are pervasive; things happen and are recorded. These streams can be regular with all channels updating at once like sound. Alternatively, channels can update one at a time and maybe not at all, as things happen. An example of this is an electronic health record – which might capture hospital admission, a blood test, or perhaps a continuing ECG measurement. Managing this heterogeneous stream of data is a challenge. Often there is important information in the order of events that links the channel behaviour together. The Programme seeks to further develop signature-based mathematical tools for dealing with complex streamed data, and connect with partners who have the capability and the challenges to benefit from and achieve significant outcomes with the methodology. Details about the event are on the webpage.

UK Graduate Modelling Camp, 29th - 31st March 2021 aimed to provide participants with hands-on experience of mathematical modelling under the guidance of experienced instructors and mentors. The challenges that students work on are inspired by real-world challenges that have arisen in industry or science. Starting with presentations from the mentors, the participants then formed teams to work on each problem. Scientific communication was an important part of the camp and all participants were expected to make presentations.
The camp was open to all PhD students and designed to promote a broad range of problem-solving skills, such as mathematical modelling & analysis, scientific computation & critical assessment of solutions. It was an excellent preparation ground for early career researchers to get hands-on modelling experience before usually going on to attend the five-day European Study Group with Industry (ESGI) which always takes place annually shortly after the modelling camp. This year the ESGI was hosted by Durham University on the 12th-16th April 2021. More information about the modelling camp is on the webpage.

Privacy Enhancing Technologies in Practice took place as a series of short workshops- starting on 19th November 2020 and finishing on 19th January 2021.
Companies have been repeatedly told that data is one of their most valuable commodities, but realising the full value of that data may require re-mixing, comparison, or computation against data held by others.  Unfortunately, sharing data is one of the hardest things for companies to do, because of the perceived commercial and legal risks. Even within a single organisation, sharing data can be considered to create large security or privacy risks. Developed with academic partners and in collaboration with the Digital Catapult, these sessions recognisde the need to help business and industry find effective ways to utilise these new privacy enhancing technologies.

Mathematics and Statistics for Effective Regulation took place on Tuesday 17th November 2020 virtually and in partnership with the Royal Statistical Society in London. The reliability and accuracy of reporting is key to ensuring confidence in the financial sector, yet there is limited regulation on data quality and the software used, a lack of consistency and no agreed documentation of modelling. This is in contrast to medicines and medical devices, where there are auditable processes in place with the requirement to demonstrate the source of data used and the need to show documentation of the workings of the software. 

As well as providing a useful comparison of standards and approaches to regulation in the medical and financial sectors, this workshop provided an overview of the different expectations of regulatory bodies. It looked at approaches to assessing the quality and validity of data, statistics, computing and mathematics in the financial sector which differ substantially from those in the health sector.  Speakers will explore these issues, with a focus on pensions, investments and fraud.

Mathematical Foundations of Optimisation in Data Science took place on Tuesday 24th November 2020 -  the annual academic engagement event from the Cantab Capital Institute for the Mathematics of Information.

This one day conference brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to data analysis. Talks covered the applications of optimisation methods in engineering and science; algorithm design, analysis and implementation for linear and nonlinear non convex smooth optimisation​, regularisation and optimisation for machine learning. More details are on the event webpage

Innovative Mathematics for the Modern Industrial Strategy took place at INI from Monday 3rd February 2020 - Friday 14th February 2020. For many decades there has been a need for mathematical innovation in industry, especially in our largest R&D intensive companies. This case was made clear in the 2018 Bond Review and with the UK  Government's Modern Industrial Strategy there is an opportunity to do as the Bond Review suggests and  link together the providers of mathematics with senior business leaders,  and provide resources for long-term industry-driven collaboration in areas that can benefit from innovative mathematics. In 2019 a workshop related to the Industrial Strategy Challenge Fund was held at ICMS. This meeting scoped possible mathematical topics and identified some key areas that could both stimulate mathematical innovation and offer exciting possibilities of adding value to industry.

Working with the KTN, INI and the Gateway delivered 2 workshops in February 2020 - Network Theory and Optimal Control for the Circular Economy and Physical Modelling for Formulation. 
They brought academics and those from industry together to discuss particular challenges and the sessions covered a number of different topics and challenges in each week. ​Outputs from the events will be available in due course and for more information contact Matt Butchers. ​

Advances in Numerical Modelling​- Applications of Geometric and Structure Preserving Methods took place on Tuesday 3rd December 2019. Geometric and structure preserving methods are a special class of numerical algorithms used to compute solutions to differential equations that preserve the underlying geometry and structure of the system. The key advantage of these methods is that they are not only computationally fast, but they also improve the accuracy of the computation since they are both quantitatively and qualitatively precise.

This workshop showcased recent applications of geometric and structure preserving methods to models of real-world systems, as well as highlighted where advances in these types of numerical methods are most needed.

Cantab Capital Institute for the Mathematics of Information - Connecting with Industry took place on Wednesday 27th November 2019 at INI. This annual industry engagement day from CCIMI aimed to showcase the research that is being carried out at the Institute and enabled delegates to hear more detail about some of the current project collaborations and industry challenges that CCIMI is exploring.

This event followed the previous industry and academic engagement events delivered since 2016 and more information is available on the Gateway initiatives webpage.The main focus of this one day industrial engagement event was to provide an update on research and collaborations taking place at the CCIMI, as well as presenting interesting research being developed elsewhere.​

The Future of Distributed Ledger Technology took place on Wednesday 6th November 2019. Distributed Ledger Technology (DLT), and its numerous potential applications, has gained increased attention in recent years. The UK showed early interest in the technology and through strong research effort is now recognised as a global player.
This workshop was a collaboration with GCHQ, the Digital Catapult and the Engineering and Physical Sciences Research Council (EPSRC). In recognition of the potential and possibilities of DLT as a technology for both Government and the UK as a whole, it aimed to support appropriate use cases and promote research into scalable DLT. It served to bring together stakeholders (researchers and end users) from multiple communities, to help connect people and build closer links and collaborations to strengthen the community.

Industrial Applications of Complex Analysis took place on Wednesday 30th October 2019. It showcased the state of the art in complex analysis methods and highlighted their current application in industrial settings, as well as where mathematical advances in this area are most needed. Complex analysis is a branch of mathematics that studies analytical properties of functions of complex variables. It lies on the intersection of several areas of mathematics, both pure and applied, and has important connections to asymptotic, harmonic and numerical analysis.

The programme for the day reflected the breadth of application areas where complex analysis methods are important and included talks representing both academic research and end-user perspectives from a range of different industrial areas. These also highlighted recent advances in complex analysis methods which have the potential to significantly improve a number of areas including understanding of aeroacoustics, medical imaging methods, tissue engineering approaches and fluid dynamics.

Artificial Intelligence Developments in Healthcare Imaging took place on 23rd & 24th Oct 2019 at the INI. The EPSRC Centre for Mathematical Imaging in Healthcare (CMIH) held an engagement event in October 2019. This aimed to showcase the research being carried out at the Centre and presented an opportunity to hear in detail about some of the current project collaborations, other industry challenges and explore new potential collaborations.This event follows previous industry and academic engagement events delivered over the past three years.

This user engagement event focused on artificial intelligence and provided an update on some of the research projects and collaborations taking place in the CMIH. It featured presentations from CMIH researchers and Industry Partners, as well as other academics and end users in the public sector and industry. A number of industry challenges and collaborations were highlighted in an elevator pitch session.

Geometric and Topological Approaches to Data Analysis took place on Thursday 13th June 2019. This Research Conference of the Cantab Capital Institute for the Mathematics of Information (CCIMI)  brought together those academics working to advance data science and will provide an update on the research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to data analysis.This event was of interest to participants including social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied and computational analysis; quantum computing; cryptography; communication and security;  and those from data processing.

On 23rd May 2019, the Mathematics of Deep Learning and Data Science  took place at INI and was attended by nearly 100 delegates. Data science is a fast growing academic discipline incorporating many interdisciplinary areas in engineering, physics and mathematics. Deep learning is now established as a main tool in large parts of modern data science. However, the understanding of deep learning, both from a mathematical and engineering point of view, is somewhat limited. This event explored both the existing theory and the big unanswered questions regarding the science and mathematics of deep learning. The Programme included talks that looked at medical imaging and inverse problems; approximation theory and properties of neural networks; optimisation in deep learning and data science & secure and safe use of deep learning methods.

On Thursday 14th March 2019Quantum Computing in the Pharmaceutical Industry took place in collaboration with the Innovate UK Knowledge Transfer Network. The past two years have seen rapid advances in building scalable quantum computers. It is now widely expected that a device that cannot be simulated by any classical computer (so-called ‘quantum computational supremacy’) will emerge in 2019. The prospect of a relatively near-term device capable of a quantum advantage has sparked a huge amount of excitement in academia, industry and government funding.The workshop brought together experts in quantum computing, the pharmaceutical industry and (classical) computational methods to discuss if this is realistic and explore other potential applications in the pharmaceutical industry.

Novel Computational Paradigms took place on Tuesday 30th October 2018 & Wednesday 31st October 2018 delivered by the TGM in partnership with GCHQ. Many of today’s interesting problems stem from the ability to generate and process large volumes of data, such as for instance, intelligent power grids and smart cities that form part of the Internet of Things. But the ability to work with all this data has to match the demand and if the speed of processing power is to continue to develop to meet such demands, new forms of computing need to be found; new algorithms need to be developed to make efficient use of these new forms of computation; and new mathematical challenges arise in the design and analysis of these new algorithms.
The workshop aimed to investigate potential next-generation advances in novel computational paradigms and brought together relevant stakeholders from across various UK research communities and industry. It is hoped that this activity helped to build closer links and collaborations and aid the establishment of a joined up multi-disciplinary UK community for this area.

On Thursday 14th November 2018, TGM delivered the third Cantab Capital Institute for the Mathematics of Information – Connecting with Industry day. The main focus of this event was as an industrial engagement day that provided an update on research and collaborations taking place at the CCIMI, as well as presenting research being developed elsewhere.The talks highlighted research taking place at CCIMI, with associated industrial engagements and looked to explore the big questions in data science where mathematics is most suited to help provide answers.There was also a session hosted by CCIMI students which they developed and delivered as a group.

On Tuesday 27th November 2018Understanding Multi-Modal Data for Social and Human Behaviour  took place in Cambridge. In an era of data deluge - sensors, cameras, computers and smart phones capture and store an unending torrent of data about human activity. The data is high-dimensional, sequential, complex, heterogeneous and multimodal in nature; but the sample size is woefully small in comparison.  Real benefits to many areas of modern society arise if one can analyse, model and predict different aspects of social and human behaviours.  Techniques, such as those offered by rough paths theory, increase the range of potential successes to include recognising human actions and understanding changing facial expressions.This workshop aimed to increase awareness of what is possible, whether it be better mitigation of risks, management of outcomes, or supporting individuals in their daily lives, across the spectrum of social and human behaviour.

On Friday 15th June 2018, the TGM delivered  Uncertainty Quantification for Complex Systems – Development in Theory and Methodologies. Uncertainty quantification (UQ) is a modern inter-disciplinary science that cuts across traditional research groups and combines statistics, numerical analysis and computational applied mathematics. UQ methodologies are useful for taking account of uncertainties when mathematical and computer models are used to describe real-world phenomena. This helps to better inform decisions, assess risk and formulate policies across multiple areas as diverse as climate modelling, manufacturing, energy, life sciences, finance, geosciences and more.

This event took place as part of an INI Research Programme and featured a number of talks from academia as well as end users. It provided the opportunity for those from industry and the public sector, to access state-of-the-art theory and methods, as well as learning about best practice and helping to foster links between the various communities. It helped to further consolidate opportunities for collaboration between statisticians and applied mathematicians. 

A short introductory talk provided an overview of the Uncertainty Quantification Research Programme. This was followed by a number of academic talks that reviewed progress made over the duration of the Programme, in relation to some of the key research. Two end-user sessions included talks from the environment and energy infrastructure sectors, where speakers described how uncertainty is managed at present in their organisations and the challenges they face.

On 24th May 2018, the TGM delivered The Mathematics of Machine Learning - A Research Conference of the Cantab Capital Institute for the Mathematics of Information. This was the second annual academic conference from CCIMI and focused on the academic interactions taking place related to the mathematics of machine learning.

This one day conference brought together those academics working to advance data science and provided an update on research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to machine learning. 

On Wednesday 14th - Thursday 15th March 2018, the TGM helped to deliver Algorithms and Software for Quantum Computers in partnership with the Knowledge Transfer Network. This aimed to initiate development of quantum computer algorithms and software by bringing together real-world problem owners (for example in drug discovery or meteorology), mathematicians, algorithm experts, and academic quantum computer hardware experts to explain what code developers need to know to create software, without getting bogged down in the underlying physics. Discussion was in sufficient detail to spark immediate cooperation and collaboration. 

On Wednesday 28th February 2018, the TGM hosted  Big Data and the Role of Statistical Scalability, as part of the wider INI Research Programme and in partnership with StatsScale. A major challenge of working with Big Data is that the volume can exceed what is feasible to compute with and traditional methods can fail to scale up. There has also been a tendency to focus purely on algorithmic scalability, eg, developing versions of existing statistical algorithms that scale better with the amount of data. This event explored these issues and end-user sessions featured speakers from the health, energy and communications sectors.

On 1st February 2018, the TGM delivered Taming Uncertainty in Mathematical Models Used in the Private and Public Sectors as part of the six month Programme at the INI on Uncertainty Quantification for Complex Systems: Theory and Methodologies. This event concentrated on how to handle uncertainty arising from the use of computer models and featured three end-user sessions including talks from the engineering, financial and healthcare sectors. These described how uncertainty is managed at present in a number of organisations and explored if we can cross-fertilise, for example, between engineering, finance and medicine.

On Wednesday 22nd November 2017, the TGM delivered Cantab Capital Institute for the Mathematics of Information - Connecting with Industry. The main focus of this event was as an industrial  engagement day that provided an update on research and collaborations taking place at CCIMI, as well as highlighting projects being developed elsewhere. 

The TGM has facilitated 3 satellite workshops that were run as part of the Variational Methods and Effective Algorithms for Imaging and Vision Research Programme
These took place on Thursday 28th September 2017 - Large-Scale Optimisation Algorithms and its Applications,  Friday 27th October 2017 - Application of Optimal Transport and Thursday 7th December 2017 - Machine Learning for Acquisition Systems.

On Tuesday 5th September, the TGM  delivered Computational Challenges in Image Processing. This an Open for Business event was part of the INI Programme on Variational Methods and Effective Algorithms for Imaging and Vision.The afternoon event highlighted both some of the challenges and potential novel solutions for computational image processing. Talks discussed possible new mathematical models which are needed to address the ever growing challenges in applications and technology, generating new demands that cannot be met by existing mathematical concepts and algorithms.

Working with University College London (UCL), the TGM hosted Data Sharing and Governance on 27th June 2017 at the Institute of Child Health in London. This afternoon workshop embedded within the UCL Theory of Big Data conference  explored the area of big data and data sharing. The programme was targeted at a broad audience of users who deal with personal data and are looking for ways to share this data. The talks highlighted experiences and challenges from collaborative research and data sharing, such as effective practices for interagency working which can lead to effective interventions, as well as opportunities for new cross-industry collaborations.

In June 2017. the TGM hosted High Dimensional Mathematics - A Research Conference of the Cantab Capital Institute for the Mathematics of Information. This was the Institute's s first annual academic conference and brought together those academics working to advance data science and provided an update on research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere.

As part of a week long New Developments in Data Privacy Research Programme at the Isaac Newton Institute, the TGM developed and delivered 2 separate events to engage with industry and the public sector in December 2016.
New Approaches to Anonymisation  helped to disseminate the latest advances in the area of anonymisation. Data confidentiality and privacy is an increasingly challenging topics in the new data environment in which there are growing numbers of large databases describing people, their characteristics and their behaviours. It featured a session on end user perspectives which included short talks from data holders in the transport, telecoms, finance, energy and health areas. The facilitated panel session was a forum for questions and discussion around the challenges in the context of various applications with perspectives from both researchers and end-users.

Engaging People in Data Privacy  explored new ways in which data subjects can take an active part in how their data are shared. Presentations and discussion explored how people think about privacy and how this interacts with the use of personal data. They investigated the mechanisms which need to be implemented to improve privacy of data and how the Big Data community can potentially help to address such issues.

Big Data, Multimodality and Dynamic Models in Biomedical Imaging was a one day workshop at the Isaac Newton Institute, Cambridge being held on 9th March 2016 and in partnership with Cambridge Big Data.

Following on from the very successful Coping with Big Data event in London in January 2015, the TGM partnered with UCL to run a half-day workshop Big Data Analytics for Financial Services which was embedded within the 2nd UCL Theory of Big Data Conference in January 2016. This event covered some of the issues around using the breadth and depth of data available to address regulatory and systemic risk challenges.

The Alan Turing Institute provided funding for a number of scientific scoping workshops in 2015. These workshops have helped to define the research programme at the Alan Turing Institute, whose mission is to undertake data science research at the intersection of computer science, mathematics, statistics and systems engineering. It aims to provide technically informed advice to policy makers and enable researchers from industry and academia to work together towards practical applications and solutions. The TGM was pleased to assist with the development and delivery of one of these Data-Rich Phenomena - Modelling, Analysing and Simulations using Partial Differential Equations , which ran between 14th - 16th December 2015, at the Centre for Mathematical Sciences, Cambridge.This four day scientific research scoping workshop brought together expert mathematicians and statisticians, working on nonlinear, nonlocal, and stochastic PDE models and on large, complex network problems, with industrial and academic data science users.

The Techniques for Data Linkage and Anonymisation workshop took place on 23rd October 2014. This investigated techniques for the safer linkage/merging of data, as well as those for more effective anonymisation in order to preserve privacy and confidentiality of personal information.

In the area of Cyber Security, the TGM is working with GCHQ to develop and broaden the Post-Quantum Research community in the UK. A 2-day workshop in May 2014 kicked off a programme of activities, with a second workshop in September 2014. There is a realistic possibility that in the medium term the power of quantum computation will have the potential to compromise some cyber security systems. Therefore, there is a current need to develop classical cryptographic security into schemes that are resistant to quantum computer attack. Activities will seek to identify future challenges and directions for post-quantum cyber-security research and to generate ideas for developing UK research and teaching in the area.