Machine Learning for Spectroscopy - Sciencesconf.org

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	Mon. 26	Tue. 27	Wed. 28
08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00	Registration 8:30 - 8:45 (15min) Registration At the conference venue, TBA Welcome address 8:45 - 9:00 (15min) Welcome address Spectroscopy and AI in semiconductor technology research 9:00 - 9:45 (45min) Spectroscopy and AI in semiconductor technology research Michiel J. van Setten Conditioning on Spectra for Generative Crystal Design 9:45 - 10:30 (45min) Conditioning on Spectra for Generative Crystal Design Pierre-Paul De Breuck Coffee break 10:30 - 11:00 (30min) Coffee break High-throughput calculations of vibrational properties and their analysis 11:00 - 12:00 (1h) High-throughput calculations of vibrational properties and their analysis Xavier Gonze Lunch 12:00 - 13:45 (1h45) Lunch Machine Learning for Phonon Engineering: Toward Predictive Thermal and Spectroscopic Modeling 13:45 - 14:30 (45min) Machine Learning for Phonon Engineering: Toward Predictive Thermal and Spectroscopic Modeling Girogia Fugallo Explicit Electrons in Machine Learning Potentials 14:30 - 15:15 (45min) Explicit Electrons in Machine Learning Potentials Toon Verstraelen Coffee break 15:15 - 15:45 (30min) Coffee break Contributed talks 15:45 - 17:00 (1h15) Contributed talks Malte Grunert, Nathalie Brun, Dario Baum, Arno Annys, Sabana Shabnam Flash talks (5min/person) 17:00 - 17:35 (35min) Flash talks (5min/person) Sourour Ayari, Scheffler Johannes, Gorfer Alexander, Adhyatma Abdurrahman, Karimi Nejad Sara, Hakeem Luqman, Marco Stecca Poster session 17:35 - 18:30 (55min) Poster session	WE-Heraeus Foundation Introduction 8:45 - 9:00 (15min) WE-Heraeus Foundation Introduction - Spectra Prediction and Peak Assignment using Graph Neural Networks 9:00 - 9:45 (45min) Spectra Prediction and Peak Assignment using Graph Neural Networks Annika Bande Accurate XPS predictions of amorphous materials: A machine-learning model combining DFT and GW 9:45 - 10:30 (45min) Accurate XPS predictions of amorphous materials: A machine-learning model combining DFT and GW Dorothea Golze Coffee break 10:30 - 11:00 (30min) Coffee break Vibrational spectroscopy of molecules, condensed phases & interfaces using machine learning and quantum statistical mechanics 11:00 - 12:00 (1h) Vibrational spectroscopy of molecules, condensed phases & interfaces using machine learning and quantum statistical mechanics Venkat Kapil Lunch 12:00 - 13:45 (1h45) Lunch Phonons and anharmonicity in the time of machine-learning interatomic potentials 13:45 - 14:30 (45min) Phonons and anharmonicity in the time of machine-learning interatomic potentials Aloïs Castellano Enhancing Vibrational Spectroscopy Predictions Using Machine Learning 14:30 - 15:15 (45min) Enhancing Vibrational Spectroscopy Predictions Using Machine Learning Ke Chen Coffee break 15:15 - 15:45 (30min) Coffee break Contributed talks 15:45 - 17:00 (1h15) Contributed talks Della Valle Andrea, Laurens de Boer, Max Großmann, Daria M. Tomecka, Joël Eymery Poster session 17:00 - 18:30 (1h30) Poster session Social dinner at Strofilia (Rue du Marché aux Porcs 11/13, 1000 Bruxelles) 19:00 - 22:30 (3h30) Social dinner at Strofilia (Rue du Marché aux Porcs 11/13, 1000 Bruxelles)	Deep Generative Models for Tractable Probabilistic Inference over Molecular Graphs 9:00 - 9:45 (45min) Deep Generative Models for Tractable Probabilistic Inference over Molecular Graphs Vaclav Smidl Decentralized materials research data management, curation and dissemination for accelerated materials discovery 9:45 - 10:30 (45min) Decentralized materials research data management, curation and dissemination for accelerated materials discovery Matthew L. Evans Coffee break 10:30 - 11:00 (30min) Coffee break Data- and theory-informed approaches for accelerating the capture and interpretation of core-level spectra 11:00 - 12:00 (1h) Data- and theory-informed approaches for accelerating the capture and interpretation of core-level spectra Maria K. Y. Chan Lunch 12:00 - 13:00 (1h) Lunch Automatic Quantification of Transition Metal X-ray Photoelectron Spectra using Convolutional Neural Networks 13:00 - 13:45 (45min) Automatic Quantification of Transition Metal X-ray Photoelectron Spectra using Convolutional Neural Networks Lukas Pielsticker Contributed talks 13:45 - 15:00 (1h15) Contributed talks Mandira Das, Thomas P. van Waas, Trung-Phuc Vo, Strocov Vladimir, Frederico Zecchi Closing remarks, Best poster award 15:00 - 15:15 (15min) Closing remarks, Best poster award Departure 15:15 - 18:30 (3h15) Departure .

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