Nicolas Bousquet Email and Phone Number

Quantmetry provides data science, big data and AI services from the upstream phases of a digital transformation strategy to solutions implementation: Data Strategy (roadmap definition, data governance, reg. compliance..) ; Data Science (natural Language Processing & chatbots, Computer Vision, time series analytics, predictive maintenance...) ; Big Data architectures(Architecture design and implementation (Cloud and on-premise), code optimization, models testing, deployment and monitoring)Quantmetry also drives numerous R&D projects in artificial intelligence, on the basis of our values and with many academic and non-academic partners, for skills and consulting improvement as well as for the common good (health, environment, etc.). As the scientific director, I developed the scientific strategy of Quantmetry, taking part in the company management, built AI projects with our motivated team and extern partners (universities, research centers, companies, in France and abroad), managed the expert team and led the whole research. A particular emphasis was (and still is) placed on IA for modeling and simulation for industry and healthcare. Check out the R&D webpage!

Researcher, scientific project manager

Managing a > 20 p team focused on simulation-based robustness studies of power plants to climate and socio-economic changes (up to 22th century)

I was holding a position of research management in applied statistics and mathematics. I am specialized in data processing, modelling (especially Bayesian modelling), statistical inference and decision-helping. I manage several people (junior engineers, Ph.D. students, post-doctoral researchers, internships..) on research and development thematics mostly related to industrial risk and reliability of EDF assets (management of the lifetime of production plants) and their resulting socio-economic risks. The technical stakes of these R&D studies mainly deal with the management of uncertainties in behavioral projections (simulations), from numerical models calibrated from in-situ data (grounds experiments), treatment of massive databases and possibly human expertise. Numerous other works deal with the management of natural resources and assets (e.g., hydraulical engineering, ecosystemic compartment submodels), and allow me to connect the industrial and environmental worlds from a technical viewpoint. Finally, one of my major theme of interest is the development of innovation by crossing scientific and economical competences.Current interests---------------------Massive data treatment & deep machine learning & in-situ analysis & virtual reality => decision-helpingSome realizations-------------------------Elaborating algorithms for detecting extreme natural hazards Modelling predictive reliability for the management of industrial maintenance, and sustainability of environmental resourcesManaging the development of R&D software tools implementing algorithms of data and expert information processingModelling and prediction of uncertainties in asset managementLeading academic and industrial collaborations Supervising Ph.D. and post-doctoral researchersMany articles published in journal or conference proceedingsLecturer in several universities in France and abroad

Decisional Bayesian statistics for business, industry and environmental management

Industrial Risk Management DptMathematical Treatment of Uncertainties in Critical Processes

Mathematics and Scientific Computing