DataSciEn'2018 - Learning from Scientific Data in Energy

IFPEN / Rueil-Malmaison (France) - 16-17 January 2018


DataSciEn'2018 aims at bringing together multi-disciplinary researchers and industrials from the energy sector working on problems with large and complex datasets. The emphasis is on the practical application of state of the art algorithms to extract information from experimental and simulated data.


Topic 1: Advances in Algorithms
The objective of this session is to present in detail efficient algorithms recently developed for machine learning. Topics of interest include:
Double-puce-bleu-ciel-et-orange Topological Data Analysis
Double-puce-bleu-ciel-et-orange Deep Learning
Double-puce-bleu-ciel-et-orange Optimization in Machine Learning
Double-puce-bleu-ciel-et-orange Functional Data Analysis
Double-puce-bleu-ciel-et-orange Visualization
Double-puce-bleu-ciel-et-orange Image analysis and feature detection


Topic 2: Frameworks and Platforms
In this session, we bring together platform and software developers to discuss modern architectures for data gathering and analysis. Special focus will be given to:

Double-puce-bleu-ciel-et-orange Software for Data Analytics
Double-puce-bleu-ciel-et-orange Big data frameworks


Topic 3: Solving Engineering Problems with Data
The objective of this session is to offer the opportunity for successful industrials and scientists to showcase practical applications of data science algorithms and frameworks to experimental or simulated data in their field. Priority will be given to applications related to the energy sector, such as:

Double-puce-bleu-ciel-et-orange Oil and Gas (exploration and production)
Double-puce-bleu-ciel-et-orange Chemical Experiment (refining process, catalysis and pharmaceutical process design)
Double-puce-bleu-ciel-et-orange Sustainable Transport (hybrid and electric engines / software for efficient transportation)
Double-puce-bleu-ciel-et-orange New Energies (biofuels / wind, solar and marine energies / storage)


Download the program here