Recordings
Monday (13.05.2024)
- Lilo Pozzo
Open-Science laboratory automation for AI-accelerated materials research and optimization (link to recording) | (link to slides) - Brenden Pelkie
Open-Science laboratory automation for AI-accelerated materials research and optimization (link to recording) | (link to slides)
Tuesday (14.05.2024)
- Kevin Jablonka
Large language models for materials science (link to recording 1, link to recording 2) | (link to slides) | GitHub - Jörg Neugebauer
Maximizing High-Throughput Discovery and Machine Learning Efficiency Through Computational Workflows (link to recording) | (link to slides) - Sarath Menon
Maximizing High-Throughput Discovery and Machine Learning Efficiency Through Computational Workflows (link to recording) | (link to slides) | GitHub | Jupyter Notebook
Wednesday (15.05.2024)
- Christoph Koch Machine learning in electron microscopy and spectroscopy (link to recording 1, link to recording 2)
- Workshop Opening (link to recording)
- Andy Sode Anker Machine learning for analysis of experimental scattering data in materials chemistry (link to recording) | (link to slides)
- Andreja Benčan Golob Addressing Challenges in 4D STEM Data of Ferroelectrics Using Machine Learning (link to recording) | (link to slides)
- Martin Uhrin Symmetry-aware generative model for amorphous solids (link to recording) | (link to slides)
- Christer Söderholm Materials design of inorganic crystals with 3D transformers (link to recording) | (link to slides)
- DAEMON talk (link to recording) | (link to slides)
Thursday (16.05.2024)
- Ekin Dogus Cubuk
Scaling up computational materials discovery via deep learning - Javier Heras-Domingo
Unlocking the Potential of EXAFS: Machine Learning Approaches for Spectroscopic Data (link to recording) | (link to slides) - Nejc Hodnik
Exploring Big Data for a Deeper Understanding of Electrocatalyst Behavior (link to recording) | (link to slides) - Panel Discussion
(link to recording) - Vinko Sršan
Deep learning-based drift correction in atomically resolved STEM images (link to recording) | (link to slides) - Andrea Ruiz
Quantitative description of metal center organization and interactions in single-atom catalysts (link to recording) | (link to slides) - Helge Stein
What comes after acceleration of research? What got us here? (link to recording) | (link to slides) - Dušan Strmčnik
Machine Learning for Investigation of Nickel Surface Chemistry in Electrocatalytic Production of Hydrogen (link to recording) | (link to slides) - Sašo Šturm
Autonomous laboratory for sustainable research and discovery of new materials (link to recording) | (link to slides) - Austin Zadoks
Spectral Operator Representations (link to recording) | (link to slides) - Franco Pellegrini
LATTE: an atomic environment descriptor based on Cartesian tensor contractions (link to recording) | (link to slides) - Matthias Stosiek
Lignin Carbohydrate Complexes – Learning the Structure-Property Relation with Artificial Intelligence (link to recording) | (link to slides) - Nataliya Lopanitsyna
Revealing Chemical Pathways in Reaction Data through Noctis (link to recording) | (link to slides) - Emma King-Smith
Practical Machine Learning for Organic Small Molecule Modelling (link to recording) | (link to slides)
Friday (17.05.2024)
- Teodoro Laino
Fueling the Digital Chemistry Revolution with Language and Multimodal Foundation Models (link to recording) | (link to slides)
- Lei Zhang
A Comparative Study of Machine Learning Models and Vector Analysis Techniques for Improved Prediction of Quaternary Material Systems Based on Word Embeddings (link to recording) | (link to slides)
- Matej Praprotnik
Developing an Implicit Solvation Machine Learning Model for Molecular Simulations of Ionic Media (link to recording) | (link to slides)
- Panel Discussion
- Matilda Sipilä
Application of the Question Answering method to extract information from materials science literature (link to recording) | (link to slides)
- Morgan Kerhouant
Enterprise deployment, scaling and democratisation of R&D models
- Tian Xie
MatterGen: a generative model for inorganic materials design (link to recording)
- Closing