The Power and Pitfalls of Machine Learning in the Design of New Molecules
• Charlotte Deane, Stephen Roberts, Louise Slater, Neil D. Lawrence
Stephen Roberts
Louise Slater
Neil D. Lawrence
Abstract
AI is currently revolutionising science. It is helping us to discover more promising candidates for therapeutic drugs; it is being used to generate more accurate weather forecasts; and it is at the forefront of efforts to tackle the biodiversity and climate crises. At this inaugural event, we explore the effects that AI is already having on science and those areas of science soon to be influenced.
Professor Charlotte Deane MBE delivers our plenary talk, “The power and pitfalls of Machine Learning in the design of new molecules”. Professor Deane is Executive Chair of the Engineering and Physical Sciences Research Council, and Professor of Structural Bioinformatics in the Department of Statistics at the University of Oxford, where she leads the Oxford Protein Informatics Group.
Following her talk, Professor Deane discusses “AI as the main driver for future science” in a panel session including:
Professor Louise Slater is Professor of Hydroclimatology and Tutorial Fellow at Hertford College, University of Oxford. Louise leads the Hydro-Climate Extremes Research Group, which develops computational approaches to detect, attribute and predict how changes in climate and land cover may affect water-related extremes and society.
Professor Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge. He has been working on machine learning models for over 20 years and recently returned to academia after three years as Director of Machine Learning at Amazon. His main interest is the interaction of machine learning with the physical world.
The panel is chaired by Professor Stephen Roberts, Professor of Machine Learning and Professorial Fellow at Somerville College, University of Oxford. Stephen is co-lead of Oxford’s Schmidt AI in Science Postdoctoral Fellowship Programme.