Professor David Hand is Emeritus Professor of Mathematics and Senior Research Investigator at Imperial College, London, where he formerly held the Chair in Statistics. He is a Fellow of the British Academy, and an Honorary Fellow of the Institute of Actuaries, and has served (twice) as President of the Royal Statistical Society. He served as a non-executive director of the UK Statistics Authority for 8 years and on the EU's the European Statistical Advisory Committee. He chairs the National Statistician's Expert User Advisory Committee and the ONS's Centre for Applied Data Ethics Advisory Committee. He previously Chaired the Research Board of Imperial College’s Data Science Institute and was Chair of the UK’s Administrative Data Research Network. He spent eight years as Chief Scientific Advisor to Winton Capital Management. He has published 300 scientific papers and 32 books, including Principles of Data Mining, The Wellbeing of Nations, Measurement Theory and Practice, and The Improbability Principle. His most recent books are Amy's Luck, Dark Data, From GDP to Sustainable Wellbeing, and Measurement: A Very Short Introduction. In 2002 he was awarded the Guy Medal of the Royal Statistical Society, and in 2012 he and his research group won the Credit Collections and Risk Award for Contributions to the Credit Industry. He was awarded the George Box Medal in 2016, and the Research Medal of the International Federation of Classification Societies in 2019. In 2013 he was made OBE for services to research and innovation.
The Improbability Principle website is http://improbability-principle.com/
The Dark Data website is https://darkdata.website/
Hand DJ, 2009, Measuring classifier performance: a coherent alternative to the area under the ROC curve, Machine Learning, Vol:77, ISSN:0885-6125, Pages:103-123
Hand DJ, 2006, Classifier technology and the illusion of progress, Statistical Science, Vol:21, ISSN:0883-4237, Pages:1-14
et al., 2002, Statistical fraud detection: A review - Comments and rejoinders, Statistical Science, Vol:17, ISSN:0883-4237, Pages:249-255
et al., 2000, Data mining for fun and profit, Statistical Science, Vol:15, ISSN:0883-4237, Pages:111-131