8h45-9h15 Welcoming coffee, distribution of badges
9h15-9h30 Data Intelligence Institute of Paris and Graduate School Chemistry presentation
9h30-10h00 ● Data-driven high-throughput experimentation using combinatorial material science methods and machine learning
Lars Banko, Ruhr-Universität Bochum
10h00-10h30 ● Solving the inverse problem in atmospheric remote sensing with machine learning techniques
Lieven Clarisse, Université libre de Bruxelles (ULB)
10h30-11h00 Coffee break
11h00-11h30 ● Optimization of Lithium Ion Battery Manufacturing Processes by Combining Physics-Based and Machine Learning Modeling
Alejandro A. Franco, Université de Picardie Jules Verne
11h30-12h00 ● Emulating the complexity of secondary organic aerosol formation with machine learning approaches
Camille Mouchel-Vallon, Laboratoire d'Aérologie, Université de Toulouse, CNRS.
12h00-12h30 ● Digitalization of Organic Chemistry: Autonomous Flow Reactors Associating In-line/Online Analyses and Feedback Algorithms
François-Xavier Felpin, Nantes Université
12h30-14h00 Lunch
14h00-14h30 ● Advancing transmission electron microscopy with machine learning : towards high-throughput data acquisition and real-time structural analysis down to the atomic scale
Jaysen NELAYAH, Materials and Quantum Phenomena laboratory (UMR 7162) , Université de Paris Cité
14h30-15h00 ● Can a molecular Boltzmann generator train itself without data?
Jérome Henin, Institut de Biologie Physico-Chimique, Paris
15h00-15h30 Coffee break
15h30-16h00 ● Data-driven chemical understanding
Janine George, Federal Institute for Materials Research and Testing (Department Materials Chemistry) and FSU Jena (Institute of Condensed Matter Theory and Optics)
16h00-16h30 ● Machine learning for the prediction of molecular properties
Benoît Gaüzère Maître de conférences en informatique chez INSA Rouen Normandie
