Algorithm, Big data, numerical calculations, data science, machine learning, coding, modeling, accelerating, innovating, Data Challenge

Why this data challenge?

Sébastien Gourvenec (Data Science & Artificial Intelligence R&D manager – Total Energies _ Saclay-France)
This Data Challenge was an opportunity to discuss our machine learning and data science practices.

Athanasios Kontopoulos (Computational & Data Science Scientific Director, Data & Decision Sciences Lab (d2-Lab) founder – Air Liquide R&D, Fellow)
We held the event to strengthen ties between teams from TotalEnergies and Air Liquide, and also to enjoy some time together.

Sébastien Gourvenec
The AI potential is incredible.

Athanasios Kontopoulos
It’s going to be a crucial tool in the years to come.

Who can participate?

Athanasios Kontopoulos
This type of challenge is open to everyone in our companies and to all data enthusiasts.

Lucie Chen (Air Liquide – Canada)
I love data because data is the key to open the door to the unknown.

Athanasios Kontopoulos
Participants came from all over the world,

Sébastien Gourvenec
some were beginners and were able to make their first data journey.

The topic?

Athanasios Kontopoulos
The topic was wind power.

Sébastien Gourvenec
Because renewable energies are intermittent by nature, so it’s a real challenge to predict the quantities that can be produced.

Paul Martin (TotalEnergies Intern – France)
The challenge was really pleasant because it was an open problem that could be approached by lot of different ways in my opinion.

Sébastien Gourvenec
During the phase 1, the problem was quite simple: participants had to predict the wind power production on one farm.

Yen Sun (TotalEnergies – United States)
It allows me to play around with wind power data and also to understand the importance of wind power prediction.

Athanasios Kontopoulos
We had excellent participation rates.

Sébastien Gourvenec
We had 210 participants for over 2,700 contributions, which are very high figures.

Athanasios Kontopoulos
In the second phase, we created 10 duos who generated 376 solutions.

Sébastien Gourvenec
The duos were all very different, with a wide range of profiles and competency levels, and it was incredible to see them all work together.

What about the results?

Athanasios Kontopoulos
When you give data scientists the opportunity to work together, it generates even more creativity in their solutions.

Sergei Parshin (Air Liquide – Russia)
In a team, the best solution is team solution.

Sébastien Gourvenec
The winners of phase 2 put forward some really ingenious and brilliant solutions.

Athanasios Kontopoulos
We were really amazed,

Sébastien Gourvenec
The first words that came to mind were creativity and application.

Athanasios Kontopoulos
It showed us that data science is much more than just a science. There’s also an artistic aspect to it.

Next?

Sébastien Gourvenec
We can really capitalize on these solutions,

Athanasios Kontopoulos
to better model the energy mix, which includes more and more renewable energies. It was an incredible human adventure

Sébastien Gourvenec
between TotalEnergies and Air Liquide, with some wonderful encounters and productive discussions.

Athanasios Kontopoulos
There is still a lot to come.

Sébastien Gourvenec
We are going to create other data challenges on other topics and open it to more companies.