Talked at CECAM
We gave a talk and presented a poster at CECAM workshop held from Feb 19th to Feb 21th. We had a great discussion with the researchers advancing the HPC and atomistic simulation fields.
The slides of the talk is now available to have a look on public, don’t miss it.
Title
Million years of research acceleration with universal neural network potential-based SaaS
Description
- Introduce paper “Towards Universal Neural Network Potential for Material Discovery”
- Impact made by cloud service Matlantis: Universal High-speed Atomistic Simulator
Document
Speaker
Kosuke Nakago
Preferred Networks, Inc.
Kosuke Nakago is an Engineer at Preferred Networks, Inc. He received his master degree in theoretical physics from the University of Tokyo in 2014. He worked on deep learning research & development at Preferred Networks, Inc. and developed chainer-chemistry, A Library for Deep Learning in Biology and Chemistry. He is also supporting users to utilize Matlantis for their innovative material discovery at Preferred Computational Chemistry, Inc. His research interest includes deep learning as well as its application to materials science. He also participates data science competition and he is Kaggle competition master and notebooks grandmaster.
Rudy Coquet
Preferred Computational Chemistry, Inc.
Senior Manager at PFCC, he received his PhD in Chemistry from Cardiff University, UK in 2005 and his MBA from HEC Paris, France in 2013.
