Energy Landscapes: from molecules and nanodevices to machine learning
The potential energy landscape provides a conceptual and computational framework for investigating structure, dynamics and thermodynamics in atomic and molecular science. This talk will summarise new approaches for global optimisation, quantum dynamics, the thermodynamic properties of systems exhibiting broken ergodicity, and rare event dynamics. Applications will be presented that range from prediction and analysis of high-resolution spectra, to coarse-grained models and design principles for self-assembly of mesoscopic structures, with recent results for machine learning landscapes.
Selected Publications:
Perspective: Energy Landscapes for Machine Learning, PCCP, 19, 12585-12603, 2017.
 Exploring Biomolecular Energy Landscapes’
 Feature Article: Exploring Biomolecular Energy Landscapes, Chem. Commun., in press, DOI:10.1039/c7cc02413d
 Perspective: Insight Into Reaction Coordinates and Dynamics From the Potential Energy Landscape, JCP, 142, 130901, 2015.
 Energy Landscapes: Some New Horizons, Curr. Op. Struct. Biol., 20, 3-10, 2010.Â
 Energy Landscapes, Cambridge University Press, Cambridge, 2003
Biography
David J. Wales received his BA, PhD, and ScD degrees from Cambridge University in 1985, 1988 and 2004. He spent 1989 as a Lindemann Trust Fellow at the University of Chicago, working with Prof. R. S. Berry. He was a Research Fellow at Downing College Cambridge in 1990, a Lloyd’s of London Tercentenary Fellow in 1991, and a Royal Society University Research Fellow from 1991 to 1998. He was awarded the Meldola Medal and Prize by the Royal Society of Chemistry in 1992, and the Tilden Prize in 2015. In 1998 he was appointed to a Lectureship in Cambridge and is now Professor of Chemical Physics and Chair of the Theory Group in the Chemistry Department. He was elected as a Fellow of the Royal Society in 2016.