AI3SD Series: Winter Seminar Series 2020/21

Kanza, Samantha (2021) AI3SD Series: Winter Seminar Series 2020/21. Frey, Jeremy G. and Niranjan, Mahesan (eds.) AI3SD Winter Seminar Series, , Online. 18 Nov 2020 - 21 Apr 2021 . (doi:10.5258/SOTON/AI3SD0207).

Abstract

This is a record of all of the talks from the AI3SD Winter Seminar Series 2020/21. All of our speakers were invited to be interviewed and where that interview has taken place, the records of the talks listed below also contain links to the related interviews. The following talks took place in this series:

1. Topology: From shapes to numbers - Professor Jacek Brodzki (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P0089

2. New theoretical and data-driven approaches to the study of molecular conformational spaces and energy landscapes – Dr Ingrid Membrillo Solis (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P0088

3. The Shape of Data in Chemistry – Insights Gleaned from Complex Solutions and Their Interfaces – Professor Aurora Clark (Washington State University) - http://dx.doi.org/10.5258/SOTON/P0087

4. Natural Language Processing in AI-driven Drug Discovery: What it is, why it matters and how (not) to do it – Dr Sia Togia (Benevolent AI) - Video not available

5. New Trends in Drug Discovery – Robotics & AI – Dr Martin-Immanuel Bittner (Arctoris) - http://dx.doi.org/10.5258/SOTON/P0086

6. An Open Competition of People and Machines to Develop Predictive Models for Antimalarial Drug Discovery – Professor Matthew Todd (University College London) - http://dx.doi.org/10.5258/SOTON/P0085

7. Interpretable machine learning for materials design and characterization – Dr Keith Butler (STFC) - http://dx.doi.org/10.5258/SOTON/P0084

8. When charge transport data are a worm – a transfer learning approach for unsupervised data classification – Professor Tim Albrecht (University of Birmingham) - http://dx.doi.org/10.5258/SOTON/P0083

9. Prediction in organometallic catalysis – a challenge for computational chemistry – Dr Natalie Fey (University of Bristol) - http://dx.doi.org/10.5258/SOTON/P0093

10. Data-driven materials discovery for functional applications – Professor Jacqui Cole (University of Cambridge) - http://dx.doi.org/10.5258/SOTON/P0082 

11. Outlier Detection in Scientific Discovery – Dr Jo Grundy (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P0081

12. Machine learning for electronically excited states of molecules – Dr Julia Westermayr (University of Warwick) - http://dx.doi.org/10.5258/SOTON/P0080

13. Machines Learning Chemistry – Professor Jonathan Hirst (University of Nottingham) - http://dx.doi.org/10.5258/SOTON/P0092

14. Preserving Structural Motifs in Machine-Learning Approaches to Modeling Water Clusters – Dr Jenna A. Bilbrey (Pacific Northwest National Laboratories) - http://dx.doi.org/10.5258/SOTON/P0079

15. Semantic Web in Scientific Research – Possibilities & Practices – Dr Samantha Kanza (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P0078

16. Ontologies, Natural Language, Annotation and Chemistry – Dr Colin Batchelor (Royal Society of Chemistry) - http://dx.doi.org/10.5258/SOTON/P0077

17. H2020 Project Onto Trans – Dr Alexandra Simperler (Goldbeck Consulting) - http://dx.doi.org/10.5258/SOTON/P0076

18. Unifying Machine Learning and Quantum Chemistry: From Deep Learning of Wave Functions to ML/QM-hybrid methods – Dr Reinhard Maurer (University of Warwick) - http://dx.doi.org/10.5258/SOTON/P0075

19. Accelerating structure prediction methods for materials discovery: Professor Graeme Day (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P0074

20. High-Throughput Approaches for the Discovery of Supramolecular Organic Materials: Fusing Computational Screening with Automated Synthesis – Dr Becky Greenaway (Imperial College London) - Video not available 

21. Generating a Machine-Learned Equation of State for Fluid Properties – Professor Erich Müller (Imperial College London) - http://dx.doi.org/10.5258/SOTON/P0073

22. Machine Learning with Causality: Solubility Prediction in Organic Solvents and Water – Dr Bao Nguyen (University of Leeds) - http://dx.doi.org/10.5258/SOTON/P0072

23. Machine learning for biological sequence design – Dr Lucy Colwell (University of Cambridge) - http://dx.doi.org/10.5258/SOTON/P0090

24. Machine learning applications for macro-molecular X-ray crystallography at Diamond – Dr Melanie Vollmar (Diamond) - http://dx.doi.org/10.5258/SOTON/P0091

25. Using convolutional neural networks to enable neoantigen load as a biomarker of cancer immunotherapy – Dr Felicia Ng (AstraZeneca) - Video not available

26. Can Lattice Theory Help Find a Cure for Paralysis? – Dr Nicola Richmond (GlaxoSmithKline) - Video not available

This record has no associated files available for download.

Contributors

Author: Samantha Kanza

Editor: Jeremy G. Frey

Editor: Mahesan Niranjan

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