Computer Science @ University of St Andrews

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Research

  • Academics in robes with Vint Cerf
  • Lecture on web technologies
  • First year lecture
  • MSc students in the lab
  • MSc students in the lab
  • Undergraduate tutorial
  • Lecture
  • MSc students enjoying a sunny day
  • MSc students at the summer BBQ
  • First year students in a lab-based exercise class
  • MSc students in the snow after November graduation
  • MSc students after graduation
  • Undergraduate students after summer graduation
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  • The Jack Cole building
  • Staff discussion

We are a top-class group of researchers with interests in a wide range of areas of theoretical and practical computer science. All our academic staff are research active, working with a team of post-graduate and post-doctoral researchers and a lively population of research students. See our directory of staff and research students.

Our research focuses on core themes of theoretical and practical computer science:

  • Artificial intelligence and symbolic computation including constraint programming, computational algebra and computational logic and natural language processing, image processing and robotics.
  • Computer systems engineering including software architecture cloud computing and next-generation internet, programming models for distributed systems, pervasive systems and data linkage analysis.
  • Human Computer Interaction including pervasive and ubiquitous computing, input and output technologies, intelligent interactive systems and visualisation.
  • Programming languages with an emphasis on type systems and parallelism in functional programming languages.

The School is a member of SICSA - The Scottish Informatics and Computer Science Alliance.

We have research support from a range of funding bodies including the Engineering and Physical Sciences Research Council (EPSRC), the European Commission and Industry.

All School publications are published via the University of St Andrews Research Portal.

Search Publications from the School of Computer Science


See also: completed Computer Science PhD theses.

Recent Publications

Reading small scalar data fields: color scales vs. Detail on Demand vs. FatFonts

Manteau, C, Nacenta, M & Mauderer, M 2017, Reading small scalar data fields: color scales vs. Detail on Demand vs. FatFonts. in Proceedings of the 2017 Graphics Interface conference. Canadian Human-Computer Communications Society, Graphics Interface 2017, Edmonton, Alberta, Canada, 16-19 May.

Improving resource efficiency of container-instance clusters on clouds

Awada, U & Barker, AD 2017, Improving resource efficiency of container-instance clusters on clouds. in 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2017). IEEE, The 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Madrid, Spain, 14-17 May.

Information and knowing when to forget it

Sharma, R & Arandelovic, O 2017, Information and knowing when to forget it. in 2017 IEEE International Joint Conference on Neural Networks (IJCNN). IEEE, 2017 International Joint Conference on Neural Networks, Anchorage, United States, 14-19 May.

Evaluating record linkage: creating longitudinal synthetic data to provide gold-standard linked data sets

Dalton, TS, Dearle, A, Kirby, GNC & Akgun, O 2017, 'Evaluating record linkage: creating longitudinal synthetic data to provide gold-standard linked data sets' Workshop for the Systematic Linking of Historical Records, Guelph, Canada, 11/05/17 - 13/05/17, .

Probabilistic linkage of vital event records in Scotland using familial groups

Akgun, O, Dalton, TS, Dearle, A, Garrett, E & Kirby, GNC 2017, 'Probabilistic linkage of vital event records in Scotland using familial groups' Workshop for the Systematic Linking of Historical Records, Guelph, Canada, 11/05/17 - 13/05/17, .

Beyond the EULA: Improving consent for data mining

Hutton, L & Henderson, T 2017, Beyond the EULA: Improving consent for data mining. in T Cerquitelli, D Quercia & F Pasquale (eds), Transparent Data Mining for Big and Small Data. Studies in Big Data, vol. 11, Springer, pp. 147-167. DOI: 10.1007/978-3-319-54024-5_7

Automatically deriving cost models for structured parallel processes using hylomorphisms

TiTAN: exploring midair text entry using freehand input

Yeo, HS, Phang, X-S, Ha, T, Woo, W & Quigley, AJ 2017, TiTAN: exploring midair text entry using freehand input. in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, New York, pp. 3041-3049, ACM CHI 2017 Conference on Human Factors in Computing Systems, Denver, United States, 6-11 May. DOI: 10.1145/3027063.3053228

Bottom-up vs. top-down: trade-offs in efficiency, understanding, freedom and creativity with InfoVis tools

Mendez, GG, Hinrichs, U & Nacenta, M 2017, Bottom-up vs. top-down: trade-offs in efficiency, understanding, freedom and creativity with InfoVis tools. in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, New York, pp. 841-852, ACM CHI 2017 Conference on Human Factors in Computing Systems, Denver, United States, 6-11 May. DOI: 10.1145/3025453.3025942

Investigating tilt-based gesture keyboard entry for single-handed text entry on large devices

Yeo, HS, Phang, X-S, Castellucci, SJ, Kristensson, PO & Quigley, AJ 2017, Investigating tilt-based gesture keyboard entry for single-handed text entry on large devices. in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems . ACM, New York, pp. 4194-4202, ACM CHI 2017 Conference on Human Factors in Computing Systems, Denver, United States, 6-11 May. DOI: 10.1145/3025453.3025520