Workshop media
Introductory talks and Tutorials
Bjørk Hammer: Machine learning acceleration of global structure optimization
Part I | Part II | pdf | tutorial notebook
Armi Tiihonen: Gaussian processes and Bayesian optimization
Lecture | tutorial | pdf | tutorial notebook (solution notebook)
Matthew Evans: Open databases integration for materials design (OPTIMADE)
Lecture | tutorial | pdf | tutorial notebook
Yury Lysogorskiy: Active learning for interatomic potentials development
Lecture | tutorial | pdf | tutorial notebook
Wednesday talks
Philippe Schwaller: Bayesian optimisation for chemical reactions [pdf]
Simona Capponi: Batched Bayesian optimization for molecular structures [pdf]
Rasmus Kronberg: Machine learning and materials science on LUMI [pdf]
Tonio Buonassisi: Inverse Design: Why Aren’t We There Yet? [pdf]
Kristian Berland: Screening of low lattice thermal conductivity materials using active learning [pdf]
Maria Chan: Theory-informed AI for experimental data interpretation [pdf]
Thursday talks
Adam Foster: Machine learning in scanning probe microscopy [pdf]
Xin Yang: Investigating oxygen reduction kinetics at gold-water interface using machine learning potentials [pdf]
Leonard Ng: High-throughput, single-experiment optimisation of roll-to-roll fabricated non-fullerene acceptor photovoltaics using machine learning [pdf]
Amirhossein Naghdi Dorabati: Neural network interatomic potentials for nanoindentation MD simulations [pdf]
Gareth Conduit: The modern-day blacksmith [pdf]
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Kim Jelfs: Remembering the lab in computational molecular material discovery [pdf]
Venkat Kapil: The first-principles phase diagram of monolayer nanoconfined water [pdf]
Claudio Zeni: Exploring the robust extrapolation of high-dimensional machine learning potentials [pdf]
Ming-Chiang Chang: Integrated autonomous and user-guided active learning for targeted material synthesis [pdf]
Joakim Löfgren: Bayesian optimization for experimental materials design [pdf]
Juha Koivisto: Mapping fluid state properties of biofoams to solid state using Bayesian optimization [pdf]
Shijing Sun: Application of machine learning in EV battery R&D [pdf]
Friday talks
Samuel Kaski: Collaborative AI for assisting virtual laboratories [pdf]
Ulpu Remes: Multi-fidelity Bayesian optimization structure search [pdf]
Sašo Džeroski: Semi-supervised and active multi-target regression for material design [pdf]
Martin Pimon: Electrons go nuclear: a unique interaction with Thorium-229 [pdf]
Julija Zavadlav: Deep molecular modeling: the impact of training objective [pdf]