Please see my web page https://www.macs.hw.ac.uk/~dwcorne/ -- it will generally be more up to date than this. And, of course, as a computer scientist, my  google scholar profile  will capture much more of relevance than the 'Scopus' profile.

I research into optimisation, machine learning and data mining. I also work extensively with businesses in exploiting my research (from advising start-ups through to major industry-supported projects). In straightforward terms, I design algorithms that quickly find solutions to difficult problems in design, logistics, telecoms, bioinformatics, and many other areas. I also work with prediction and forecasting methods that learn from and exploit data.(e.g. automated financial trading, predicting diseases from genetic data, and so on.). Technically, my main focus is on understanding how appropriately to design and/or configure algorithms for any given space of problem instances or datasets. I am particularly interested and specialist in multi-objective optimisation, evolutionary computation, methods that hybridise learning and optimization, and ‘super-heuristics’ – automatically discovering fast algorithms for a given space of problems.

My research career started with 6 years as a research associate in the Dept of Artificial Intelligence, University of Edinburgh (1990—1996). Initially I was working on an AI in Design project, and then moved on to evolutionary computation for logistics; this was the project that led directly to the current highly successful and commonly used ‘hyper-heuristics’ techniques. I entered the academic ladder with a lectureship at Reading in 1997, and there developed interests and high-impact contributions in multi-objective optimization, bioinformatics, telecommunications and web science, and at the same time began to work with industry (BT, and several SMEs); I became Reader in 2002, took up a Chair in Computer Science at Exeter in 2003 (where I also developed links with Motorola and BAE Systems), and moved to Heriot-Watt at the end of 2007, where I continue to combine fundamental research with knowledge exchange at various levels.