Professor Morris read Chemistry as an undergraduate and graduate at Oxford, completing his Part II and DPhil with Prof. W. Graham Richards in molecular modelling and graphical protein sequence analysis. In 1991 he moved to The Scripps Research Institute, California, developing the widely-cited protein-ligand docking software, AutoDock. He helped launch the first biomedical screensaver computing project, FightAIDS@Home, spawning other biomedical projects on IBM’s World Community Grid. He moved back to the UK in 2008 to join the Oxford spinout InhibOx (now Oxford Drug Design), doing ‘real-world’ drug discovery and developing novel virtual screening methods, as well as spearheading the use of cloud computing in drug discovery. He moved on to become Head of Computational Chemistry at another Oxford spinout, Crysalin, developing novel protein engineering techniques for reliable protein crystallization.

Prof. Morris has co-organized the Royal Society of Chemistry’s "AI in Chemistry” Conference since 2022, and the MGMS-CSAT Joint Sheffield Cheminformatics Conference since 2019. He also founded Comp Chem Kitchen, hosting events highlighting best-practices in computational chemistry, cheminformatics and related fields.

Prof. Morris works closely with Prof. Deane in the Department of Statistics in the Oxford Protein Informatics Group (OPIG). He is also Programme Co-Director of the SABS R³ (Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research) Centre for Doctoral Training. In September 2019, he became Deputy Director of Graduate Studies. He is a Research Fellow of Green Templeton College, Oxford.

Former students have gone on to work in academia (Universities of Auckland; Malta; Oxford; and Stanford); pharma (AstraZeneca, Astex, Bayer, Chemify, and Isomorphic Labs); patent law (Carpmaels & Ransford); research software engineering (University of Oxford and Swiss National Supercomputing Centre); research funding (UKRO/UKRI); and venture capital (Redalpine).

My research is focused on the development of novel methods in computer-aided drug discovery, docking, virtual screening, cheminfomatics and bioinformatics. I am particularly interested in the intersection of physics, chemistry, and machine learning, including active learning, deep learning, Bayesian optimization, explainable AI, and generative AI.