Bristol Data Science Seminar Series

Heilbronn Data Science Seminar Series

Last October 2019, The Jean Golding Institute teamed up with the Heilbronn Institute for Mathematical Research to bring the latest research in Data Science to our community as part of an exciting series of data science talks and seminars. Over the past few months we have welcomed an array of internationally recognised speakers from Harvard, Tokyo and the London School of Economics, to name a few.

As we look to the year ahead, we speak to our colleagues from the Heilbronn Institute to find out more about this unique series of events and what is in store for the coming months.

What are the main objectives of the Heilbronn Institute for Mathematical Research?

Data Science graphic“The Heilbronn Institute for Mathematical Research is a national centre supporting research across a range of areas of mathematics in the UK. The Institute is engaged in both classified research, which is directed by GCHQ, as well as an extensive external research programme.

The University of Bristol is the Institute’s principal academic partner and together we run a highly successful programme of events, which includes conferences, focused research groups, visitor programmes and workshops. These activities are designed to enrich the research environment in the mathematical sciences, both in Bristol and across the whole country. More generally, the Institute is also increasingly involved in advocacy for mathematics in the UK.” – Tim Burness, Reader in Pure Mathematics

Next we spoke to Dan Lawson, Senior Lecturer in Data Science,  one of the main event organisers.

Dan Lawson, Senior Lecturer in Data Science
Dan Lawson, Senior Lecturer in Data Science, and Seminar Series event organiser

Can you tell us a bit about the Bristol Data Science Seminars?

“The Data Science Seminars are an avenue for data-intensive researchers to meet and exchange ideas. By teaming up JGI with the Heilbronn Institute, we have been able to bring expert data scientists from institutions around the world to Bristol, from both academia and industry. These seminars cover a range of areas of data science, spanning statistics, machine learning, algorithms and applications including energy, bioinformatics and more.”

Who have you got lined up to talk in this year and what are the main themes to look forward to?

“Confirmed speakers in the next 12 months include Pierre Jacob from Harvard, who is an expert in Bayesian Statistics and Taylan Cemgil from Google DeepMind. One key theme is the link between academia and industry which is only set to grow in importance as Machine Learning becomes an essential part of more businesses.”

Is there anything else you would like to tell us?

Simulated Graph
Simulated Graph

“The Data Science Seminars are always looking for suggestions of speakers with connections to Bristol, from methodology, science application or industrial application backgrounds.” If you’d like to make a suggestion, please get in touch with Dan Lawson.

Thanks to Dan and Tim for speaking with us.

Join us for the next event in the series, a talk by Pierre Jacob from Harvard University on ‘Unbiased Markov chain Monte Carlo with couplings’, Wednesday 11th March, 15.30 – 16.30. Register on Eventbrite today.

Click here for the full list of upcoming Data Science Seminars.

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Heilbronn and JGI logos

New GW4 Data Science Network Launched

The Jean Golding Institute in collaboration with the GW4 Alliance has launched a new GW4 Data Science Network which will act as a hub for news, events and funding opportunities in data science research that are available to staff and students throughout the GW4 Alliance. In particular, the Network will highlight opportunities and events coming from The Alan Turing Institute that are open to all GW4 universities.

The Alan Turing Institute is the national institute for data science and AI in the UK.  The Turing was established with the remit to innovate and develop world-class research in data science and AI that supports next generation theoretical developments and is applied to real-world problems, generating the creation of new businesses, services and jobs.

The GW4 Data Science Network aims to capitalise on the upcoming opportunities that GW4 partners can access via the membership of two University partners (Bristol and Exeter) of The Alan Turing Institute.

The Network has administrative support in all university partners, with a hub at the Jean Golding Institute at the University of Bristol. For more details please contact Elaine Young at gw4-turingnetwork@bristol.ac.uk.

Members of the GW4 Alliance are able to see the latest opportunities and events using the GW4 Data Science Network Portal.  Please email Elaine Young for access.

Brunel’s Network project

Photo courtesy of SS Great Britain Trust

A blog written by James Boyd, Brunel Institute

Isambard Kingdom Brunel

As many Bristolians know, during the 19th century, Isambard Kingdom Brunel was a major force in the development of the city, and the wider region. Working on railways, docks, bridges and revolutionary ships that forged connections across Britain and the world, many of his works are with us today. One of the most significant is the SS Great Britain, which today lies in the heart of Bristol’s old city docks, on the very spot it was built. The first ocean-going vessel in the world to be built of iron, and the first to be moved by a propeller, it is the prototype of the modern ship. Restored as a museum vessel, and visited by hundreds of thousands every year, it is one of the city’s major visitor attractions, and an icon of maritime history.

Brunel Institute

In 2010, the SS Great Britain Trust and the University of Bristol entered into a collaboration to promote and support educational, academic and professional studies in maritime, scientific, industrial and technological history, archaeology and ethnography, through the creation of the Brunel Institute. Situated in the Great Western Dockyard alongside the ship, the Institute is a dedicated facility encompassing archives, reading and teaching space and state of the art conservation suite, which houses the collections and resources of the SS Great Britain Trust, and the University of Bristol’s Brunel Collection, donated by the family in 1950.

Since 2018, James Boyd, resident research fellow at the Institute, has been using its collections, in combination with other major national collections, to piece together the wider network of engineers, investors and patrons involved in the creation of I K Brunel’s three path-breaking steamships. These ships, the Great Western, (1838) Great Britain (1843) and Great Eastern (1859) were each critical to global history. The first of them was the very first ocean-going vessel purpose built to steam non-stop between Britain and North America; the second, as mentioned, transferred ocean ships to modern materials and propulsion; the last was a costly failure for its investors, a hugely oversized vessel for voyaging to Asia Pacific, but it ended up laying the first continual, working telegraph cable connecting Europe and America.

Brunel’s Network

‘DM162/10/1 – Isambard Kingdom Brunel Letter Books, by Courtesy of the Brunel Institute – a collaboration of the SS Great Britain Trust & University of Bristol

Brunel’s Network is a project that aims to find, record, assess and weight the influence of all the individuals with whom Brunel collaborated in order to deliver these projects. It is an analytical enquiry into communities of innovation, and how they functioned in the past, with Brunel at the epicentre. The analysis initially utilised some basic static network visualizations, built in Gephi, in order to construct a picture from the source material of who provided significant contributions and connections within each project. However, the visualisations and data needed greater dexterity, and also aimed to have a significant public engagement angle, by making interactive, temporal network diagrams available for public exploration.

In a great example of the active collaboration fostered by the Institute, this dynamic element has been generated and continues to be developed by Christopher Woods, Head of Research Software Engineering at Bristol. Christopher has taken the opportunity to create software capable of temporal network analysis that not only comprehends Victorian social, political and professional interactions, but has significant ongoing potential in general temporal analysis of human networks and their development.

With funding support from the Jean Golding Institute, Christopher has also been able to add a third team member, Gareth Jones, so that a public exhibition of Brunel’s Network will be available in the Brunel Institute from the 19th of July 2020 – the 50th anniversary of the day the historic SS Great Britain was towed back to Bristol for restoration. The project team are aiming to have all data, visualisations and analysis prepared for the launch of an interactive app by the close of 2020, before the findings, methods, outcomes (and lessons learned!) are collated and presented to both the digital humanities and data science communities. Hopefully, the project will demonstrate ways in which historical source material and digital methodologies can work in harmony to help both the academic world and wider public comprehend the past, whilst generating present-day software innovations that expand the analytical tools available in Bristol and beyond.

Further progress of this project will be reported in future blog posts.

To keep up to date with this and other projects, news, events, funding and other opportunities please Join the JGI Mailing list.

A Challenge Owner’s perspective of the inaugural Turing Network Data Study Group – Part 2

The challenge team with Challenge Owner Simon de Lusignan and Data Science Principle Investigator Mark Joy

Understanding and improving the reliability of disease monitoring in GP surgeries is the extensive, yet critical task taken on by the team of researchers at Royal Society of General Practitioners (RCGP) and the University of Surrey headed by Professor Simon de Lusignan and Dr Mark Joy. With this goal in mind, the team challenged participants of the first Turing Network Data Study Group to attempt to develop a predictive algorithm using machine learning that corrects sub-optimal data allowing for better disease monitoring. In part two of our blog series focusing on a Challenge Owner’s perspective of the Turing Network Data Study Group, Professor de Lusignan and his team tell us about their experience of the DSG and the challenge they presented: Improving our ability to use routine data to inform the management of key disease areas. You can read part one of this series, where we spoke to another Challenge Owner, University of Bristol’s Danielle Paul about her experience of the event on the JGI blog. Challenge Owner team – who was involved?

  • Prof Simon de Lusignan, University of Oxford/University of Surrey/Royal College of General Practitioners
  • Dr Mark Joy, University of Surrey
  • Rachel Byford, University of Oxford/University of Surrey
  • Dr John Williams, University of Oxford/University of Surrey
  • Dr Nadia Smith, University of Surrey/National Physical Laboratory

Can you give us a brief overview of the challenge you presented to the Data Study Group participants? It is essential to monitor blood pressure in various chronic diseases (e.g. heart disease, diabetes, etc). However, GPs tend to indicate certain biases in recording measurements, for example a preference for round numbers. We have 47 million blood pressure readings and 7 million glycated haemoglobin (HbA1c) readings (a measure of diabetes control) and we were interested in finding the true blood pressure and HbA1c trends from the inaccurate data, comparing trends for different groups of patients (e.g. on various medications). Participants were challenged to attempt to develop a predictive algorithm using machine learning that corrects suboptimal data allowing for better disease monitoring. The challenge ended up being split into three sub-challenges:

  1. Identifying whether a case is a new (incident) or a follow-up (prevalent) when this information is not recorded in the computerised medical record
  2. What is the true underlying blood pressure (BP) in a population where there is marked end-digit preference for zero, when data are recorded?
  3. What is the trend in diabetes control when there is additional testing at the time of ill health?

What kind of solutions did the challenge team come up with? The solutions suggested to the three sub-challenges were as follows:

  1. Tree classifiers for classification as this is essentially a binary classification problem (is a GP visit a follow-up or a new, incident visit?); decision trees and random forests for classification of episodes into new and ongoing; data driven approaches to finding threshold and min-max range of number of days between two episodes per diseases.
  2. Latent variables, time series ideas
  3. Bayesian-type approach with an iterative procedure for uncovering the posterior (incorporating Neural Network classifiers for patient characteristics)

What are your hopes for the potential applications of the team’s findings from this week?

The team had to work together to find solutions to the three sub-challenges

We have two members of the group interested in carrying on this work. We hope to explore further the team’s approach to Sub-challenge 1 as we feel this is a promising area for further exploration. The team’s contribution to Sub-challenge 2 is already planned to be incorporated in to the RCGP report to Public Health England. It increases the scope and applicability of this report on the nation’s health in certain key disease areas. Sub-challenge 3 was arguably the more difficult challenge, and the team’s feedback has led us to reconsider how we engineer our data to better address this prediction problem. As a Challenge Owner, what was your favourite part of the Data Study Group week? New perspectives, the opportunity to make more use of our data. We enjoyed engaging with the enthusiasm and energy of the team. Our favourite part was listening to the presentations at the end of the week. Were there any surprises for you at the event? How narrow population health and epidemiological technique are compared with the wealth of ideas and approaches available. Is there anything else you would like to tell us? Two members of the group have been in contact about continuing this work. One to work on “episode types” the other on end-digit preference in blood pressure recording. The event was immensely enjoyable, truly challenging for the team members, and a joy to participate in.

The Alan Turing Institute and Data Study Groups

The inaugural Turing Network Data Study Group was hosted by the Jean Golding Institute at the University of Bristol – one of The Alan Turing Institute’s 13 partner universities in August 2019. The event united six Challenge Owners with 50 students, postdocs and senior academics to tackle real-world data science challenges spanning a variety of fields, from spectroscopy and analytical chemistry to text mining and digital humanities. Building on the popular Data Study Groups (DSGs), held three times a year at Turing HQ in London, this ‘Turing Network’ event was the first of its kind to be hosted by a partner university. It followed the tried-and-tested format of a five-day collaborative hackathon. The Challenge Owners – organisations from industry, government and the third sector – provided real-world data challenges that were tackled by small groups of highly talented researchers. The results were presented on the final day. Find out more about Data Study Groups, including how you can get involved as a researcher or Challenge Owner on The Alan Turing Institute website

JGI Seed corn funding call winners 2020 announced!

The Jean Golding Institute are delighted to announce the winners of the Seed corn funding call 2020.

This funding call has been successfully running for last three years and aims to support activities to foster interdisciplinary research in data science (including AI) and data-intensive research.

The Jean Golding Institute has funded a total of 32 seed corn projects since 2016. This year, we have been able to fund 10 projects and are grateful to have received funds from the Faculty of Arts and Strategic Funding in order to offer additional awards. Our winners this year are:

  • Oliver Davis, Claire Haworth and Nina Di Cara with ‘Mood music: using Spotify to infer wellbeing’
  • Brendan Smith and Mike Jones with ‘Digital humanities meets Medieval financial records: the receipt rolls of the Irish exchequer
  • Zoi Toumpakari, Ivan Palomares Carrascosa, Daniele Quercia and Luca Maria Aiello with ‘Automating food aggregation for nutrition and health research’
  • Avon Huxor, Emma Turner, Eleanor Walsh and Raul Santos-Rodriguez with ‘Elements of free text used in decision making: an exemplar from death reviews in prostate cancer and learning disabilities’
  • Jim Dunham, Gethin Williams, Nathan Lepora, Tony Pickering and Manuel Martinez Perez with ‘Decoding pain: development of a clinical tool to enable real-time data visualisation and analysis of human pain nerve activity’
  • Ranjeet Bhamber, Andrew Dowsey, Febe Van Maldegem and Julian Downward with ‘Super-charging single cell imaging pathology’
  • Elaine McGirr and Julian Warren with ‘Mapping Oliver Messel’
  • Liz Washbrook with ‘Mental health and educational achievement in two national contexts: a machine learning approach
  • Ella Gale, Natalie Fey, Craig Butts, Varinder Aggarwal with ‘Chemspeed data capture and curation’
  • Pierangelo Gobbo and Lars Bratholm with ‘Machine learning assisted polymer design’.

We will  be interested to hear how all these projects progress this year and will report back on their progress in the summer of 2020. Our next Seed corn funding call will be in the Autumn of 2020.

To ensure you keep up to date with any other funding calls, news, events and other opportunities, please join the JGI mailing list.