The Maharaja Sayajirao Uiversity of Baroda
The Maharaja Sayajirao Uiversity of Baroda


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20th to the 24th of July 2020

162nd European Study Group with Industry


We are pleased to announce that the 162nd European Study Group with Industry will take place online from the 20th to the 24th of July 2020.

European Study Groups with Industry are an internationally recognised method of technology transfer between academic mathematicians and industry. The first one was held in Oxford in 1968 and now they take place regularly throughout the year in Europe, with one annually in the UK.

European Study Groups with Industry are week long workshops that provide a forum for problem presenters from businesses and non-academic institutions to work alongside academic mathematicians and data scientists on real-world problems of direct relevance. On the first day the 6-8 problem presenters will pitch their problems to an audience of 60-80 mathematicians. Work-groups will then be formed with the aim of producing viable solutions that will be presented back to the problem presenters at the end of the week. A report will then be written up in the months following the event.

Due to the ongoing COVID-19 pandemic, the 162nd European Study Group with Industry will take place online. We have the generous support of the Virtual Forum for Knowledge Exchange in the Mathematical Sciences (V-KEMS), which includes the Knowledge Transfer Network, the Newton Gateway to Mathematics, the Isaac Newton Institute (INI), the International Centre for Mathematical Sciences (ICMS), as well as various representatives from the mathematical sciences community. V-KEMS have run several successful trials of virtual study groups using video conferencing software and a range of collaborative online tools, and with this experience, we anticipate that the 162nd European Study Group with Industry will be as lively and as productive as ever.

Academic participants

European Study Groups with Industry are an exciting way of working on a new real-world problem, whilst giving you the opportunity to develop collaborative team working skills, learn some new tricks and try something out of the ordinary.

Places are limited , but if you would like to take part, please complete the registration of interest form.


Overview for potential problem presenters

Do you have data that you’re struggling to make sense of? Do you need to understand why something is happening? Would you like to control or optimise it? If you have a problem like these, the 162nd European Study Group with Industry is an opportunity to get help from a room full of world leading mathematicians and data scientists.

Problem descriptions

Problems being lined up for the study group include:

  • A problem to develop climate crisis stress tests to assess corporate bonds.
  • Dstl – the science inside UK national security is considering the problem of uncertainty quantification of self-organised swarms of drone sensors.
  • Faraday Predictive Ltd want to understand the relative magnitude of distortions to motor current arising from changes in motor load, eccentricity and rotor condition. 
  • Innovation Embassy would like to estimate the total amount that online customers will spend based on limited data, including how the customer arrives at the website and their initial purchase.
  • Transfinite (problem 1) want to quantify risk under deployment uncertainty in radio spectrum management.
  • Transfinite (problem 2) would like to assess the probability of satellite collision and/or the number of avoidance manoeuvres that would be needed in busy orbit shells.
  • Vet AI want to develop a method to extend a medical coding system that minimises the risk of clinicians creating duplicate codes.
  • Zenotech would like to develop low dimensional/highly compressed approximations of point cloud data relating to aerodynamical hazards, such as regions of turbulence around buildings.




For enquiries please contact Dr Jonathan Ward via j.a.ward@leeds.ac.uk


Organising committee

  • Onno Bokhove (University of Leeds)
  • Chris Budd (University of Bath)
  • Matt Butchers (Knowledge Transfer Network)
  • Alan Champneys (University of Bristol)
  • Helen Copeland (University of Leeds)
  • Tiziano De Angelis (University of Leeds)
  • Tamás Gorbe (University of Leeds)
  • Elena Issoglio (University of Leeds)
  • William Lee (University of Huddersfield)
  • Daniel Lesnic (University of Leeds)
  • Alastair Rucklidge (University of Leeds)
  • Jonathan Ward (University of Leeds)
  • Dawn Wasley (International Centre for Mathematical Sciences)