The convergence of intensive computing and data science at the service of companies
Mines Initiative for Numeric and Data Science (MINDS), a Carnot M.I.N.E.S project, brings together teams from 15 of its research centers around a key challenge : to equip themselves with modern computing tools for the digital transition of companies and for the convergence of “supercomputing” and “data science”
Launched in 2018, MINDS aims to develop a digital platform coupling digital simulation and artificial intelligence dedicated to the digital transformation of businesses.
In less than two years, MINDS has become the pioneer in several areas coupling digital simulation and data science, such as digital twins, Physically-Informed or the use of reinforcement learning coupled with fluid mechanics for flow control.
By creating a digital research and development platform for this convergence, MINDS has created a remarkable leverage effect for developing and maintaining high-level expertise in the digital sciences, while maintaining a balance between open innovation and research structures and specific economic challenges.
Various research initiatives have been launched, supported by initial funding of 1.2 million euros from the Carnot institute M.I.N.E.S., combining the know-how and skills of a unique scientific community comprising applied mathematicians, physicists, computer scientists and mechanics.
Beyond MINDS
At a time of digital transformation and the advent of the industry of the future, the use of predictive science (data science, AI, machine learning, etc.) in industrial processes is a central concern for manufacturers. MINDS is already responding to a number of new needs arising from the convergence of the worlds of digital simulation and artificial intelligence in various sectors: energy, health and materials.
Four new projects have been launched, all of which are based on MINDS developments: (1) real-time control of a photovoltaic power plant using enhanced learning to ensure its safety in the face of extreme winds, (2) setting up a digital twin of furnace installations to control operation and reduce CO2 emissions, (3) shape optimization using artificial intelligence of new heat exchangers in civil aircraft cabins, or (4) deep learning and digital fluid mechanics methods for the analysis and treatment of unruptured aneurysms.