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 including cloud computing and distributed systems, next-generation internet, sensor 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.
- Health Informatics focusing on biomedical models, hypotheses, and systems for future biomedical research projects using data from both studies and simulations.
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.
Ceesay, S, Barker, AD & Lin, Y
2020, Benchmarking and performance modelling of MapReduce communication pattern
. in J Chen & LT Yang (eds), Proceedings 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2019).
, 8968864, IEEE International Conference on Cloud Computing Technology and Science, IEEE Computer Society, pp. 127-134, 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Sydney, Australia, 11/12/19
Cooper, J & Arandjelovic, O
2020, Understanding ancient coin images
. in L Oneto, N Navarin, A Sperduti & D Anguita (eds), Recent Advances in Big Data and Deep Learning.
Proceedings of the International Neural Networks Society, vol. 1, Springer, Cham, pp. 330-340, INNS Big Data and Deep Learning , Genova, Italy, 16/04/19
Li, W, Fayed, M
, Oteafy, SMA & Hassanein, HS 2019, 'A cache-level quality of experience metric to characterize ICNs for adaptive streaming
', IEEE Communications Letters
, vol. 23, no. 2, 8594670, pp. 262-265. https://doi.org/10.1109/LCOMM.2018.2890223
Petford, J, Carson, I, Nacenta, M
& Gutwin, C 2019, A comparison of guiding techniques for out-of-view objects in full-coverage displays
. in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI'19).
, 58, ACM, New York, ACM Conference on Human Factors in Computing Systems 2019, Glasgow, United Kingdom, 4/05/19