In the summer of 2021, AI3SD teamed up with the Directed Assembly Network to run a virtual summer school on Machine Learning 4 Materials & Chemicals which encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. 

The summer school events were run every tuesday afternoon between the 6th July-24th August. The sessions were run privately for the summer school participants, however where the speakers gave permission for their talks to be made public we have added them to our AI3SD YouTube Channel. Please note the table below contains links to videos all of all of the speakers who gave permission for their talks to be shared, it is not an exhaustive list of the summer school speakers.

The full YouTube playlist for this Seminar Series can be found here: ML4MC Seminar Series Playlist

DateTitleSpeakerVideo LinkDOI
06/07/2021Directed Assembly of Materials – A 50 year retrospective
Professor Chick Wilson (University of Bath)
Video LinkDOI Link
13/07/2021Accelerated discovery for carbon capture solvents at IBM Research
Dr Flaviu Cipcigan (IBM)
Not AvailableNot Available
20/07/2021DNA: coding blocks for biocompatible assembly & disassembly
Dr Niek Buurma (Cardiff University)
Video LinkDOI Link
20/07/2021Applying Machine Learning to Structured Time-course sensor data for Improved Chemical Outcomes and Reproducibility
Dr David Pattison (Deep Matter)
Video LinkDOI Link
20/07/2021Assembling peptide and protein structures
Dr Anna Peacock (University of Birmingham)
Video LinkDOI Link
27/07/2021How to detect unexpected features and physical processes in single-molecule data
Professor Tim Albrecht (University of Birmingham)
Video LinkDOI Link
27/07/2021Machine Learning with Causality in Chemistry
Dr Bao Nguyen (University of Leeds)
Video LinkDOI Link
27/07/2021Light and Directed Assembly
Professor Julia Weinstein (University of Sheffield)
Not AvailableNot Available
10/08/2021Calibrated deep representations and entropy based active learning for materials property prediction
Dr Keith Butler (STFC)
Video LinkDOI Link
10/08/2021The Vast World of Very Small Holes: Metal-Organic Frameworks and Microporous Materials
Dr Timothy Easun (Cardiff University)
Not AvailableNot Available
10/08/2021Quantifying crystal similarity to predict material properties
Dr James Cumby (University of Edinburgh)
Video LinkDOI Link
17/08/2021Simulation of chemical dynamics and spectroscopy with deep learning representations of electronic structure
Dr Reinhard Maurer (University of Warwick)
Video LinkComing Soon
17/08/2021Using machine learning for discovery in supramolecular materials
Dr Kim Jelfs (Imperial College London)
Not AvailableNot Available
17/08/2021Understanding the solid form: Structural Systematics Crystal Sponges
Professor Simon Coles (University of Southampton)
Video LinkComing Soon