EDF: DataScience@work seminar

Title: Adaptive probabilistic forecasting of temporal data for electricity markets

Speaker: Yannig Goude – Senior Researcher: Machine Learning & Forecasting


  • 2 – 3.30pm Seminar + Q&A in Room 2.41, Fry Building
  • 3.30 – 4pm networking with students and colleagues in Common Room, Fry Building.

Location: Room 2.41, Fry Building


Optimising production and making decisions on the electricity markets requires the modelling of various hazards (electricity consumption, temperature, solar radiation, wind, hydraulic contributions, unavailability of power plants, market prices, and renewable production) based on historical data.  For them to work and be of practical interest, in most cases these models have to meet a number of requirements: they have to be interpretable (understandable by the end users, generally engineers in the business departments), adaptive (in the sense of automatically adapting to changes in the data) and efficient. Against a backdrop of increasing production from renewable sources and major tensions in the markets (rising electricity prices, unavailability of production facilities, gas supplies), the teams at EDF R&D (Osiris department) are developing forecasting models that combine these different characteristics.

Yannig Goude is a senior researcher working at EDF R&D, in the department Optimisation Simulation RIsk and Statistics (Osiris), since 2008 and an associate professor at the Laboratoire de Mathématiques d’Orsay, Université Paris-Saclay. He obtained a Ph.D. in statistics and probability in 2007 at the Université Paris-Sud 11, Orsay. His research interests are forecasting, time series, machine learning, semi-parametric models, and online aggregation of experts. 



The Smith Institute: DataScience@work seminar

When: Friday 7 July, 2-3pm with networking in the Common room thereafter

Location: Room 2.04, Fry Building


The Digital Revolution, Radio Waves and Data Science

Over the past three decades, a whole new sector has grown up around the creation and delivery of mobile data services, which is still growing.  A major challenge has been to provide the capacity in the electromagnetic spectrum to keep pace with demand, and this task has fallen largely on the desks on government regulators.  In addressing it, they have drawn upon the experience of physicists, economists, computer scientists and mathematicians, leading to at least one Nobel Prize along the way and many underpinning scientific advances.  The driver for this progress has been the downstream economic benefits, which are hard to estimate accurately, but amount in financial terms to multiple tens of billions annually.  In this talk, I will survey some of the scientific highlights that have enabled this ‘digital revolution’, concentrating on those that have a strong intersection with data science.

Dr Robert Leese is Chief Technical Officer at the Smith Institute and also Fellow in Mathematics at St Catherine’s College, Oxford.  Beginning in the UK, about 15 years ago, he has worked on many of the auction mechanisms that different governments around the world have used to make spectrum available for new services.

About the Smith Institute

Mathematical approaches coupled with data exploration are key to tackling real-world challenges, to finding the solutions that transform industries and enable societies, businesses and governments to thrive.

From improving the performance of railways to meeting Carbon Zero targetsforecasting crop growth to verifying radio spectrum auctions, the Smith Institute has been tackling their clients’ most critical and complex problems with bespoke solutions for over twenty years.

The possibilities of harnessing mathematical tools are infinite; they enable transformation for their clients across a variety of sectors, applying specialist domain knowledge paired with fresh thinking in transportenergydefencesecurityFMCG and radio spectrum.

For further information about The Smith Institute, see their website.

OVO Energy: DataScience@work seminar


Dave Eagon, Lead Data Scientist

Dr Angharad Stell, OVO Energy


  • 2 – 3.30pm Seminar + Q&A in Room G.13, Fry Building
  • 3.30 – 4pm networking with students and colleagues in Common Room, Fry Building. 
Abstract: OVO is a major UK Energy supplier, headquartered in Bristol, providing gas and power to domestic consumers. The Portfolio Management team is responsible for forecasting, valuing and hedging billions of pounds of commodity each year. In this talk we will discuss the challenges faced by our team in recent years (COVID, Cost of Living, Ukraine), the challenges that are still to come and how we use machine learning, statistics and computer science to manage our risks. We will explore what a typical day in our data science team might look like, the decisions we are responsible for and how we make them.
Dave Eagon has a degree in Mathematics and Statistics from Oxford University and was an investment banker before qualifying as an actuary specialising in finance and investments. He joined OVO in 2021 and now leads the OVO trading data science team. Dr Angharad Stell has a degree in Natural Sciences from Cambridge University and a PhD in Atmospheric Chemistry from Bristol University. She spent two years as a Research Associate in the Atmospheric Chemistry Research Group at Bristol University before joining the trading data science team in 2022.

About OVO Energy

OVO Energy was founded in 2009 and redesigned the energy experience to be fair, effortless, green and simple for all customers. OVO is on a mission through its sustainability strategy Plan Zero to tackle the most important issue of our time; the climate crisis, by bringing our customers with us on the journey towards zero carbon living. OVO Energy has committed to being a net zero carbon business and achieve bold science-based carbon reduction targets by 2030, while helping members reduce their household emissions at the same time.

For further information about OVO Energy, see their website and their LinkedIn page.

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