AI3SD AI for Materials Discovery Workshop Event
- Time:
- 13:00 - 18:00
- Date:
- 19 March 2019
- Venue:
- Hartley Suite University Road Southampton SO17 1TL
For more information regarding this event, please email Dr Sami Kanza at S.Kanza@soton.ac.uk .
Event details
Materials play a key role in modern society and the growing demands for functionality, selectivity, re-usability, efficiency and environmentally sustainable which all place huge demands on the chemistry. The use of Computational Chemistry and more generally Artificial and Augmented Intelligence (AI) to predict structure and function provides new possibilities in using theory to drive innovation and discovery.
FAQ
1. Who should attend?
Anyone with an interest in Materials discovery, Artificial Intelligence, Machine Learning, Deep Learning, and particularly those looking to apply AI technologies to materials discovery. We welcome members from academia, industry and government. We are always looking to grow our Network+ and bring in people with a wealth of experience in the many different subject areas that are needed so that we can form interdisciplinary partnerships and work together to further the field of Scientific Discovery.
2. What will I get out of it?
You will be able to network with likeminded people who have research interests that complement yours. There will be several keynotes around the topics of AI for Materials Discovery to spark discussion and ideas. You will hear a range of thought-provoking talks about different aspects of using AI technologies in the area of materials discovery, and have the opportunity to both discuss this subject area with other members of the workshop and address questions to the speakers. Members of the Network Executive Group will also be in attendance so you will be able to find out more about our Network and the opportunities we have available including funding opportunities and the types of events we will be running (e.g. workshops, conferences and hackathons).
3. What are the aims of the workshop?
This workshop is aiming to help the Network+ to drive progress in this area and facilitate collaboration by introducing people to make new interdisciplinary teams, and to produce new grant applications. To achieve this we may commission literature reviews, papers, or small scale investigations to test out new ideas. We welcome ideas and suggestions about how to go forward in this area and how best to achieve our aims.
4. What are the main themes of the workshop?
Materials, Computational chemistry, Novel Mathematics, AI.
Speaker information
Prof. Graeme Day,Graeme is a Professor of Chemical Modelling at the University of Southampton. His research interests centre on the development and application of computational methods for understanding and predicting the structures and properties of molecular materials. An area of particular interest is crystal structure prediction, and its applications in structure determination, polymorph discovery and the design of materials with targeted properties. These research areas all stem from a fundamental interest in understanding and modelling intermolecular interactions. Graeme is the author or co-author of over 95 publications, including 5 book chapters. He serves on the advisory board for the Royal Society of Chemistry’s journal Molecular Systems Design and Engineering, is on the steering committee of the UK Materials Chemistry High End Computing Consortium and is a member of the EPSRC peer review college.
Dr Ben Mills,Optoelectronics Research Centre ,Ben is a Senior Research Fellow and EPSRC Early Career Fellow at the Optoelectronics Research Centre at the University of Southampton, where he leads a research group focussed at the interface of laser machining and machine learning. Ben completed his PhD in high harmonic generation via ultrafast lasers at the University of Southampton in 2009, and then became the manager of the “FAST lab”, a femtosecond laser facility at the University. His background covers 10 years in ultrafast lasers and their application for high-precision materials processing. Current research interests also include laboratory automation and machine learning, in particular convolutional neural networks.
Prof. Felix Studt,Karlsruhe Institute of Technology (KIT), Germany,Felix is a Professor at the Institute of Chemical Technology and Polymer Chemistry (ITCP) and the Institute of Catalysis Research and Technology (IKFT) at the Karlsruhe Institute of Technology (KIT). His research interests are in theory guided materials discovery, electrochemical processes, synthesis gas conversion, CO2 reduction, and routes from biomass to chemicals. He has published over 70 papers which have had over 2900 citations, and has been invited to speak at many international conferences. He has also published a textbook on the Fundamental Concepts in Heterogeneous Catalysis.
Dr Vitaliy Kurlin,Materials Innovation Factory in Liverpool,Vitaliy is a Computer Scientist at the Materials Innovation Factory in Liverpool, where he facilitates the collaboration between Chemists and Computer Scientists. He was awarded the Marie Curie International Incoming Fellowship (2005-2007) and the EPSRC grant “Persistent Topological Structures in Noisy Images" (2011-2013). In 2014-2016 he has gained industrial experience through Knowledge Transfer Secondments in the Computer Vision group at Microsoft Research, Cambridge, UK. From 2018 he leads the Liverpool team on a £2.8M EPSRC 5-year grant “Application-Driven Topological Data Analysis” (with Oxford and Swansea). His research group includes one postdoc and five PhD students working on applications of topology and geometry to Materials Science, Computer Vision and Climate.
Dr Angeles Pulido,Crystallographic Data Centre (CCDC) the Cambridge CDC,Angeles is a Research and Application Scientist at the Crystallographic Data Centre (CCDC) the Cambridge CDC, she is part of the Pfizer Design Centre within the Materials Science team who apply computational techniques to study organic molecular crystals relevant to pharmaceutical industry, with especial interest in crystal structure prediction, materials stability and polymorphism. Angeles’ main research interest is in silico modelling of solids and the use of computational techniques to provide an atomistic view and a better understanding of thermodynamic, kinetic and spectroscopic features of crystalline organic and inorganic materials.