Professor Susan Craw
| Biography | Susan Craw is a Professor Emeritus in Artificial Intelligence since retiring in 2018 after a 35-year career at RGU. She was the founding Director of IDEAS Research Institute (2009-2014), Faculty Head of Research & Graduate Studies (2006-2009), and Head of School of Computing (2001-2005). Her research leadership shaped RGU’s significant AI research activity. She led RGU’s Computing Research Assessment Exercises from 1992, building the profile to internationally excellent with some world-leading research in 2008. She was instrumental in RGU being a founding partner of Scotland’s SICSA research alliance (www.sicsa.ac.uk). Craw has 100+ peer-reviewed papers in top journals, including Artificial Intelligence and Computational Intelligence, and leading conferences IJCAI, AAAI, ICCBR. She was awarded AAAI Senior Membership (2015) in recognition of her contribution to AI. Craw has been a member of EPSRC College since 2003, and SFC Research & Knowledge Exchange Committee (2015-19). She was an international expert for the EXPOSED Aquaculture Operations Centre for Research Innovation, Trondheim, Norway (2014-19), and on the selection panel for Frank Knox scholarships at Harvard (2004-09). She spent sabbaticals at Aberdeen University (1991-2), Ishida’s lab at Kyoto University (1994), Pazzani’s research group at UCI (1999), and short research visit to Khemani’s lab at IIT Madras (2010). |
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| Research Interests | Susan Craw’s research develops Machine Learning and Data Mining technologies to create Case-Based Reasoning, Recommender and Decision Support systems. Her research extracts knowledge from ‘big data’ in music/image/document collections, sensor networks, social media. Her research is highly relevant to industry: Oil & Gas ‘Lessons Learned’; Medical Decision Support; Satellite Incident Management; Pharmaceutical Product Design. Smart Systems research underpins Information Engagement: Music Recommendation; Archive Browsing; Interpretations for Museums and Historic Sites. Ongoing DataLab-funded research with Albyn Housing and NHS Highland enables Behaviour Monitoring from SmartHome Sensor Data to allow people to live independently and well in their homes for longer. |
| Teaching and Learning | Postgraduate Research in Artificial Intelligence Postgraduate Taught Courses in Artificial Intelligence, Machine Learning, Data Mining, Research Methods Honours Courses in Data Mining |
| Scopus Author ID | 6603885506 |