Presentations - ai3-science-network

Conference 2019‎ > ‎

Presentations

The presentations given at AI3SD2019 can be found below:

Ethics Workshop

Ethical Frameworks, Ethical Judgements - Dr Will McNeill
Ethics for AI for Scientific Discovery - Dr Samantha Kanza

Session 1: AI3SD

AI3SD Network Retrospective - Professor Jeremy Frey

Session 2: Data, AI, Molecules & Materials

Learning with Complex Priors and Interactions - Professor John Shawe-Taylor
Data driven models that predict protein function from sequence - Dr Lucy Colwell
Materials Development in the Energy and Electronics Sectors through Combinatorial Synthesis, High-Throughput Screening and Machine Learning - Professor Brian Hayden

Session 3: Network Funded Projects Interim Reports

Predicting the Activity of Drug Candidates where there is No Target - Professor Matthew Todd
'Next-next' Generation Quantum DNA Sequencing with Chemical Surface Design and Capsule Nets - Professor Tim Albrecht
Deep Learning Enhanced Quantum Chemistry: Pushing the limits of Materials Discovery - Dr Reinhard J. Maurer

Session 4: Machine Learning & Deep Learning for Scientific Discovery

Non-equilibrium Physics and Machine Learning - Professor Juan P. Garrahan
Deep Machine Learning of Quantum Chemical Hamiltonians - Professor David Yaron
AlphaFold: Improved protein structure prediction using potentials from Deep Learning - Dr Andrew Senior

Session 5: AI & Scientific Discovery

The UKRI Review of Support for AI - Dr Renée Van de Locht
Explainable AI and Scientific Discovery - Dr Richard Tomsett

Session 6: Flash Talks for Online Posters

See Poster Page

Session 7: Talks from EPSRC AI Feasibility Studies

Machine Learning for Modelling Microstructure Evolution - Professor Nigel Clarke
The Automation of Science: Robot Scientists for Chemistry and Biology - Professor Ross King
Multi-fidelity Statistical Learning Approach for Organic Molecular Crystal Structure Prediction - Dr Roohoolah Hafizi & Dr Olga Egorova

Session 8: Contributed Talks

Isometric classifications of periodic crystals - Dr Vitaliy Kurlin
Practical applications of deep learning to imputation of drug discovery data - Dr Benedict Irwin
Dense periodic packings in the light of crystal structure prediction - Miloslav Torda
Data Science and the Physical Sciences Data-Science Service - Dr Nicola Knight
Ellipsoids as a new descriptor for materials - Dr James Cumby