European Study Groups with Industry – what’s the point?
In January I attended my first industrial maths study group: focused on agri-food and co-hosted by the Knowledge Transfer Network and the Bath Institute for Mathematical Innovation. Study groups are, usually, an intensive week of brainstorming and problem-solving by mathematicians and industry representatives.
The agri-food study group was a condensed format over three days and with three companies attending: Phytoponics, Innovent Technologies, and Mondeleze. The event began with presentations to all participants from each of company representatives, describing a problem they currently faced, and what they were hoping to achieve over the study group.
Phytopnics presented their innovative inflatable hydroponics system for growing plants in water. They wanted our help with optimising the dimensions of their product for maximum plant support and growing surface under a number of constraints.
Innovent Technologies hoped to explore the value of slaughtering pigs at different times depending on inputs of the farmer and a series of complex contracts offered by the abattoir.
Mondeleze wanted to us to consider the effect of climate in driving variability of farm cocoa yield. They were unable to provide any data, but had some previous results suggesting that climate was a driver of crop variability.
After these problems had been presented, we were divided into separate rooms allocated to each company. I chose to focus on the cocoa variability problem, along with around 20 other participants. Given that there was no data provided by Mondelez we started by searching the web for freely available sources. We also made great use of Mondelez representative, Eamon O’Hearn’s expertise, getting far more detail on how the cocoa growth and harvest cycle is affected by weather. This discussion continued into the second day, and gave us enough information to start work on a theoretical model using ordinary differential equations to represent growth and harvesting of cocoa according to seasonal rainfall.
I was really impressed by the fluidity with which participants worked: sometimes moving from one room to another, working together in small groups, taking a half hour to really concentrate on processing some data alone before presenting their findings to the group as a whole. Everyone was self-directed and free to work as they pleased, and this led to a highly collaborative effort. This intensive way of working together, with no distractions, generated results (and enthusiasm) very quickly.
In the afternoon on the third and final day, the entire study group reconvened to present the results of our work. In all three cases, there were some useful results, and plenty of ideas for further work to be done.
After the study group I successfully applied to the EPSRC funded network “Research on Changes of Variability and Environmental Risk” for funding to carry out a 6 week Early Career Research Project. I’m going to be working closely with Mondelez on this, benefiting from the knowledge of their cocoa experts, as I develop and test a more complete plant-based model for the resilience of cocoa farming to climate variation.
All in all through attending this study group I not only identified a project which allowed me to develop a grant proposal to work with an industrial partner but I also had the opportunity to work on real life problems with industrial applications plus I had the chance to meet fellow colleagues from different institutions.
I’m now really looking forward to attending my next study group.
If you are interested in attending a ESGI (european study group with industry), Mathematics in Industry Information Service collates all information about past and future study groups. They also compile the reports which are generated at the end of each study group and then presented to the companies. The Mathematics for Industry Network (MI-NET), COST Action TD1409, offers financial support to run and/or attend these events. Next deadline is 30th August 2017.
Dr Lorna Wilson is a Commercial Research Associate with the Bath Institute for Mathematical Innovation at the University of Bath. Lorna holds a PhD in the behaviour of zero-crossings in continuous stochastic processes from the University of Nottingham and an MMath in Mathematics from University of Oxford.