|Professor in the Department of Computer Science||MCS 2027||+44 (0) 191 33 41754|
After studying maths and then Computer Science, Steven joined Durham University in 1997 as a lecturer in Computer Science. From 2004-2013 he was a part-time teaching fellow, spending the rest of his time on web consultancy, mainly on research projects across the university. From 2013 he was a full-time teaching fellow in the department of Computer Science and has been an Associate Professor (teaching) since 2017.
- Computer Science education
- Knowledge representation and student learning
- Citizen science
- Web-based data collection
- Real-time systems
- Software engineering
- Innovative Computing
- Children’s hospice service data mapping project 2011/12
- Mapping Unit
- 2019: Best Paper Award Koli Calling 2019: For "Addressing Bias to Improve Reliability in Peer Review of Programming Coursework"
- 2018: Chair, UK and Ireland ACM Special Interest Group in Computer Science Education (SIGCSE): The UK and Ireland ACM SIGCSE ;aims to provide a national forum for the examination and exchange of research and practice related to the learning and teaching of computing. ;
- 2017: Excellence in Learning & Teaching Award: Awarded by Durham University in June 2017
Chapter in book
- Gajbhiye, Amit, Winterbottom, Thomas, Al Moubayed, Noura & Bradley, Steven (2020). Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. In Artificial Neural Networks and Machine Learning – ICANN 2020. Farkaš, Igor, Masulli, Paolo & Wermter, Stefan Springer. 12396: 633-646.
- Bradley, Steven (2020), Creative Assessment in Programming, Durham, England, ACM, 1.
- Bradley, Steven (2019), Addressing Bias to Improve Reliability in Peer Review of Programming Coursework, Koli Calling 2019. Finland, ACM, New York, 19.
- Bradley, Steven & Church, Stephen (2018), Collaborative Creative Computing, London Computing Education Research Symposium. London.
- Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, Bradley, Steven & McGough, A. Stephen (2018), CAM: A Combined Attention Model for Natural Language Inference, in Abe, Naoki Liu, Huan Pu, Calton Hu, Xiaohua Ahmed, Nesreen Qiao, Mu Song, Yang Kossmann, Donald Liu, Bing Lee, Kisung Tang, Jiliang He, Jingrui & Saltz, Jeffrey eds, IEEE International Conference on BIG DATA. Seattle, United States of America, IEEE, Piscataway, N.J., 1009-1014.
- Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, McGough, A. Stephen & Bradley, Steven (2018), An Exploration of Dropout with RNNs for Natural Language Inference, in Kurková, V., Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros S. & Maglogiannis, Ilias G. eds, Lecture Notes in Computer Science, 11141 ICANN 2018: 27th International Conference on Artificial Neural Networks. Rhodes, Springer, Cham, 157-167.
- Bradley, Steven (2016), Managing Plagiarism in Programming Assignments with Blended Assessment and Randomisation, in Sheard, Judy & Suero Montero, Calkin eds, 16th Koli Calling Conference on Computing Education Research. Koli, Finland, Association for Computing Machinery (ACM), New York, NY, 21-30.
- Hsing, P.-Y., Bradley, S., Kent V., Hill R., Whittingham M. & Stephens P. (2015), Monitoring Wild Mammals in County Durham with a Citizen Science Web Platform, ICCB 27th International Congress for Conservation Biology. Montpellier, France, Montpellier.
- Bennett, K.H., Bradley, S., Glover, G. & Barnes, D. (2003), Software evolution in an interdisciplinary environment, in O'Brien, L. & Gold, Nicolas eds, STEP Software Technology and Engineering Practice, 11th. International Conference. Amsterdam, IEEE Computer Press, 199-203.
- Fox, Maria, Long, Derek, Bradley, Steven & McKinna, James (2001), Using Model Checking for Pre-Planning Analysis, AAAI Symposium on Model-based Validation of Intelligence. AAAI.
- Steven Bradley & Alexandra Cristea (2019). Proceedings of the 3rd Conference on Computing Education Practice. Computing Education Practice, Durham, UK, ACM.
- Hsing, P.-Y., Coghill, L., Ryder, J., Austin, M., Dooley, S., Ellison, A., Fenwick, C., Garland, M., Humphrey, P., Proudlock, H., Robson, A., Steer, C., Turnbull, L., Kent, V.T., Bradley, S., Hill, R.A., Ascroft, R. & Stephens, P.A. (2020). Citizen scientists: school students conducting, contributing to and communicating ecological research – experiences of a school–university partnership. School Science Review 101(376): 67-74.
- Hsing, P.-Y., Bradley, S.P., Kent, V.T., Hill, R.A., Smith, G.C., Whittingham, M.J., Cokill, J., Crawley, D., MammalWeb Volunteers, & Stephens, P.A. (2018). Economical crowdsourcing for camera trap image classification. Remote Sensing in Ecology and Conservation 4(4): 361-374.
- Rees, S.W., Bruce, M. & Bradley, S. (2014). Utilising Data-driven Learning in Chemistry Teaching: a Shortcut to Improving Chemical Language Comprehension. New Directions 10(1): 12-19.
- Onyett, Steve Linde, Karen Glover, Gyles Floyd, Siobhan Bradley, Steven & Middleton, Hugh (2008). Implementation of crisis resolution/home treatment teams in England: national survey 2005–2006. Psychiatric Bulletin 32(10): 374.
- Johnstone, David & Bradley, Steven (2005). Opportunistic scheduling in a constraint-rich world. ACM SIGBED Review 2(2): 19.