The #BiasinAI Group led by Professor Sue Black, based in the department of Computer Science at Durham University, brings together academia, industry and government experts from diverse backgrounds to carry out cutting edge research with the aim of producing practical advice and new methods to reduce bias in the creation and use of AI products and services.
Who we are
Professor Sue BlackDurham University
Sarah WyerDurham University
Dr Chris WillcocksDurham University
Caroline Criado PerezInvisible Women
Dr Robert E SmithRage Inside the Machine
Sarah WilkinsonNHS Digital
Professor Gina RipponThe Gendered Brain
Renée CummingsUrban AI
Louise HooperGarden Court Chambers
Dr James LukeIBM
Dr Rashmi MisraMicrosoft
John BuyersOsborne Clarke LLP
Swathi YoungIntegrity Management Services, Inc.
Brian Runciman MBCSBCS, the Chartered Institute for IT
Kate BaucherelGalia Digital
Monica ChadhaTechnology, Media and Telecoms
Aireni OmerriInformation Security for Africa
Professor Alison LearyLondon South Bank University
Professor Yvette TaylorUniversity of Strathclyde
Dr Cristina CostaDurham University
Dr Mihretu P. GutaAddis Ababa University
Claire ButterfieldLocal Government
Demetra BradyUniversity of Cambridge
Professor Alexandra CristeaDurham University
Professor Toby BreckonDurham University
Dr Steven BradleyDurham University
Dr Suncica HadzidedicDurham University
Professor Sue Black
Professor in the Department of Computer Science
Professor Sue Black is a Technology Evangelist at Durham University, a digital skills expert, social entrepreneur, consultant and international keynote speaker with over 20 years experience. She has a computer science PhD, management and change management experience and is passionate about getting everyone excited about the opportunities that technology offers. She has also got over 20 years technology and digital skills teaching experience, along with successful social media campaigning and women and leadership expertise.
- Innovative Computing
- Women in tech
- Social media
- Software engineering
- A Al-Subaihin, F Sarro, S Black, L Capra, M Harman (2018). App Store Effects on Software Engineering Practices. IEEE Transactions on Software Engineering 50 (8), 1
- AA Al-Subaihin, F Sarro, S Black, L Capra, M Harman, Y Jia, Y Zhang (2016). Clustering mobile apps based on mined textual features. Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement
Identifying and mitigating against bias in large scale meta-learning language models from an intersectional perspective.
PhD in Computer Science
Sarah is a PhD student in the Department of Computer Science. Her thesis focuses on identifying and mitigating against bias in large scale meta-learning language models from an intersectional perspective.
- Bias in Artificial Intelligence
- Large scale meta-learning language models
- Widening Participation in HE
- AI Ethics
- Women in STEM
- Equality Diversity and Inclusion
Teaching Fellow in Computer Science (Foundation Programme)
Sarah teaches computer science on the Foundation Programme. She is the module convenor for Foundation Computer Science, and also teaches English for Scientists with Project.
Durham University Women in Tech (DUWIT) Mentor Co-ordinator
Global Ambassador Women in Tech Network
Dr Chris Willcocks
(email at firstname.lastname@example.org)
Chris Willcocks is an Assistant Professor in the Innovative Computing Group at the Department of Computer Science at Durham University. He is also a director and CTO of the Durham University research spinout company Intogral Limited. He has worked as a PDRA for Newcastle University, Durham University, and has been a visiting researcher at the Hong Kong University of Science and Technology. His interdisciplinary research focuses on providing elegant solutions to computationally expensive or ill-defined problems within the fields of medical imaging computing (MIC), machine learning, high-performance computing, image processing, bioimage informatics and computer graphics. More information about his publications and software is available on www.cwkx.com and Github profile github.com/cwkx
Machine Learning Teaching
I am teaching an upcomming sub-module on applied machine learning. Slides and other material will appear on my webite as they’re released.
Slides for cybersecurity and other material will appear on my webite as they’re released.
- University Hospital of North Durham (ongoing research with Deep Learning and Medical Image Computing)
- Intogral Limited – Innovate UK successful grant £211,996
- P&G (ongoing project with Deep Learning)
- DSTL – our team successfully competed against multiple companies for phase 2 funding for £850,000 shared with one other team)
- Intogral Limited (£211,996)
- Discretionary Award for exceptional contribution to research and collaborative projects (£1000)
- Research Day (2nd place prize for best presentation)
- Ustinov travel award
- NVIDIA Hardware Grant (£1000)
- EPSRC funded scholarship
- Unsupervised Learning
- Medical Image Computing
- Level Set Methods
- Big Data Analytics
- Image Processing
- GPGPU Computing
- Data Visualization
- Segmentation & Skeletonization
- Deep Learning
- A. V. Nasrulloh, C. G. Willcocks, P. T. G. Jackson, C. Geenen, M. S. Habib, D. H. W. Steel, and B. Obara, “Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes,” IEEE Transactions on Medical Imaging, 580-589, 2018, ISSN: 0278-0062. DOI: 10.1109/TMI.2017.2767908.
- Chris G. Willcocks, P. T. Jackson, C. J. Nelson, and B. Obara, “Extracting 3D Parametric Curves from 2D Images of Helical Objects,” IEEE Transactions on Pattern Analysis and
Machine Intelligence, vol. 39, no. 9, PP. 1757–1769, Sep. 2017, ISSN: 0162-8828. DOI: 10.1109/TPAMI.2016.2613866.
- Chris G. Willcocks, P. T. Jackson, C. J. Nelson, A. Nasrulloh, and B. Obara, “Interactive GPU Active Contours for Segmenting Inhomogeneous Objects,” Journal of Real-time Image Processing, Dec. 2017, video url: https://youtube.com/watch?v=6W4mO7BPeGg, issn: 1861-8219. doi: 10.1007/s11554-017-0740-1.
- S. Akcay, M. E. Kundegorski, Chris G. Willcocks, and T. P. Breckon, “Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 9, pp. 2203–2215, Sep. 2018, issn: 1556-6013. doi: 10.1109/TIFS.2018.2812196.
- M. Roberts, Chris G. Willcocks, and B. Obara, “Deep Learning for the Classification and Clustering of Museum Collections,” Computing Applications & Quantitative Methods in Archaeology, Nov. 2018.
- H. Alhasson, Chris G. Willcocks, P. T. Jackson, and B. Obara, “Understanding the relationship between curvilinear structure enhancement and skeletonisation,” Journal of Computer Vision and Understanding, 2018, issn: 1077-3142. (In Revision)
- S. Alharbi, Chris G. Willcocks, P. T. Jackson, and B. Obara, “Sequential Graph-based Extraction of Prominent Curvilinear Structures,” Journal of Signal, Image and Video Processing, Jan. 2019, issn: 1863-1711 (In Revision)
- Chris G. Willcocks and F. W. B. Li, “Feature-varying skeletonization: Intuitive control ove the target feature size and output skeleton topology,” The Visual Computer – International Journal of Computer Graphics, CGI, vol. 28, no. 6, PP. 775–785, 2012, ISSN: 1432-2315. DOI: 10.1007/s00371-012-0688-x.
Conferences and Thesis
- Fady Medhat, Mahnaz Mohammadi, Sardar Jaf, Chris G. Willcocks, Toby Breckon, Peter Matthews, Andrew Stephen McGough, Georgios Theodoropoulos, Boguslaw Obara, “TMIXT : a process flow for Transcribing MIXed handwritten and machine-printed Text.”, IEEE International Conference on Big Data, 2018.
- C. J. Nelson, Chris G. Willcocks, P. T. Jackson, P. Laissue, and B. Obara, “Application of high-speed level set segmentation to light sheet fluorescence microscopy,” in Light Sheet Fluorescence Microscopy International, Sheffield, UK, Aug. 2016.
- N. Mukerji, C. J. Nelson, Chris G. Willcocks, P. T. Jackson, and B. Obara, “Real-time segmentation of brain vasculature and identification of anomalies in magnetic resonance angiography,” in European Congress of Neurosurgery, Athens, Greece, Sep. 2016.
- Chris G. Willcocks, “Sparse Volumetric Deformation – Animating and rendering huge amounts of volumetric data using GPGPU computing,” http://etheses.dur.ac.uk/8471/, PhD thesis, Durham University, Oct. 2013.
Caroline Criado Perez
Job Title: Author
Dr Robert E Smith
Job Title: Technologist, complexity scientist, entrepreneur, writer and and sought-after public speaker
Professor Gina Rippon
Job Title: Professor Emeritus of Cognitive NeuroImaging
Affiliation: Aston Brain Centre, Aston University
Job Title: Criminologist, criminal psychologist, AI ethicist and data activist
Renée Cummings specialises in diverse, equitable and inclusive AI design, development and deployment, principled, responsible and trustworthy AI strategy, ethical AI policy development and governance, AI risk management, AI crisis communication and using AI to save lives.
A Columbia University community scholar, and the founder of Urban AI, LLC, Renée works at the intersection of AI, criminal justice, epidemiological and urban criminology. Passionate about the potential of AI, she speaks internationally on how to use AI to solve many societal challenges, AI for sustainable development, AI leadership and AI for business solutions. Renée also has extensive experience in homicide reduction, gun and gang violence prevention, investigating violent crimes, juvenile justice, evidence based policing, law enforcement leadership, community policing and police and media relations. Her work extends to therapeutic jurisprudence, corrections, rehabilitation, reentry and substance abuse treatment. Renée is committed to using AI to design ethical, real time, human centred solutions to improve public safety, enhance quality of life and future proof society. She’s also a journalist, and motivational speaker.
Job Title: IBM Security Accelerated Value Leader
Check out Lesley’s recent article: Five Technology Design Principles to Combat Domestic Abuse
Dr James Luke
Job Title: Director, Alexa AI – Knowledge International
Dr Rashmi Misra
Job Title: Head of AI & Mixed Reality Platforms
Job Title: Group CISO & Group Director Technology
Job Title: Partner, Head of AI and Machine Learning
Affiliation: Osborne Clarke LLP
Job Title: CTO, Integrity Management Services, Inc.
Affiliation: Integrity Management Services Inc.
Swathi Young is a keynote speaker, blogger, community-builder and Chief Technology Officer of Integrity Management Services Inc., a healthcare services company, where she is leading innovative AI solutions for clients. In her 20+ years of technology experience, she has led over 100+ projects globally – Belgium, India and the United States across a number of Fortune 100 companies like GE and Oracle.
Swathi is passionate about using cutting edge, artificial intelligence technologies to increase the performance of organisations. She believes that the intersection of Artificial Intelligence and humanities is important to focus on as we lay the foundation of AI applications for future generations. She is the Washington DC Ambassador for Women in AI, an international non-profit organisation whose goal is to increase diversity in the field of AI.
Swathi is also the founder of DC Emerging technologies, a 2000+ member community in Washington DC whose goal is to equip innovators with the knowledge and resources they need to turn theory into applications with emerging technologies. She recently co-authored the AI Playbook, a framework to help US government to implement AI solutions. She is a member of the 2020 Forbes Technology Council.
Brian Runciman MBCS
Job Title: Head of Content and Insight
Affiliation: BCS, the Chartered Institute for IT
Job Title: Digital Strategist
Affiliation: Galia Digital
Job Title: Independent Director
Affiliation: Technology, Media and Telecoms
Job Title: Founder ISfA
Professor Alison Leary
Job Title: Professor of Healthcare & Workforce Modelling
Affiliation: London South Bank University
Professor Yvette Taylor
Job title: Professor of Education
Affiliation: University of Strathclyde
Yvette Taylor is a Sociologist and Professor of Education, University of Strathclyde. She is PI on the EU funded project ‘Comparing Intersectional Lifecourse Inequalities among LGBTQI+ Citizens in 4 European Countries’ (CILIA, 2018-2021), with previous projects including ESRC funded ‘Making Space for Queer Identifying Religious Youth’ (2011-2013) and British Academy mid-career fellowship ‘Critical Terrain: Dividing Lines and Lives’ (2013-2014).
Yvette has published four sole-authored books, and co-authored Feminist Repetitions in Higher Education: Interrupting Career Categories (Palgrave, 2020). Edited titles include Educational Diversity: the subject of difference and different subjects (2012); The Entrepreneurial University. Public Engagements, Intersecting Impacts (2014); Feeling Academic in the Neoliberal University: Feminist Flights, Fights and Failures (2018). Yvette edits the Palgrave Gender and Education Series, co-edits the Routledge Advances in Critical Diversities Series, and is a Fellow of the Academy of Social Sciences.
Dr Cristina Costa
Job Title: Assistant Professor
Affiliation: Durham University
Dr Mihretu P. Guta
Title: Assistant Professor of Philosophy (Addis Ababa University)
Adjunct Professor of Philosophy (Biola University and Azusa Pacific University).
Affiliation: Addis Ababa University, Biola University and Azusa Pacific University.
Job Title: Senior Data Analyst
Affiliation: Local Government
Job Title: MPhil Student in Philosophy
Affiliation: University of Cambridge
Professor Alexandra Cristea
Professor of Computer Science in the Department of Computer Science
(email at email@example.com)
Alexandra I. Cristea is Professor, Head of the Innovative Computing research group at the Computer Science Department, Durham University. Her research includes web science, learning analytics, user modelling and personalisation, semantic web, social web, authoring, with over 250 papers on these subjects (over 3700 citations on Google Scholar, h-index 31). Especially, her work on frameworks for adaptive systems has influenced many researchers and is highly cited (with the top paper with over 180 citations and growing). She is within the top 50 researchers in the world in the area of educational computer-based research according to Microsoft Research. Prof. Cristea has been highly active and has an influential role in international research projects. She is experienced in running research projects and has led various projects – Newton funded workshop on Higher Education for All (’14-’18), Santander funded Education for disadvantaged pupils (’14-18′), Warwick-funded project APLIC (’11-;12), EU Minerva projects ALS (06-09) and EU Minerva ADAPT (’02-’05); as well as participated as university PI in several EU FP7 projects – BLOGFOREVER (’11-’13), GRAPPLE (’08- ’11), PROLEARN (’07) and as co-PI in the Warwick-funded Engaging Young People with Assistance Technologies (’13-’15) also featured by the BBC. Recently she has taken giving back to the community to a different level, with the project TechUP (2019-2020) training 100 women in computer science from various (BAME) backgrounds. She has been keynote/invited speaker, organiser, co-organizer, panelist and program committee member of various conferences in her research field (including, for example, ITS, AIED, UMAP, ED-MEDIA, Hypertext, Adaptive Hypermedia, ICCE, ICAI). She is a member of the editorial board of the IEEE Transactions on Learning Technologies, executive peer reviewer of the IEEE LTTF Education Technology and Society Journal and she was co-editor of the Advanced Technologies and Learning Journal. She acted as UNESCO expert for adaptive web-based education at a high-level (Ministry of Education and Educational institutes) meeting of East European countries, educational invited expert for the Romanian prime minister, as well as EU expert for H2020, FP7, FP6, eContentPlus. She has interacted with various international and local media (she has given a recent live radio interview to Power 106FM in Jamaica; work from her lab has been publicised by Free Radio Coventry & Warwickshire, Birmingham Post, Birmingham Mail, phys.org, The Daily Dot, Mirror, Vice Motherboard, BBC News, Pinterest, Globenewswire, Romanian TV). She is a BCS fellow, a HEA fellow, IEEE Senior Member and IEEE CS member, EATEL (European Association of Technology Enhanced Learning) founding member, ACM member.
IoC TechUP Project
100 (BAME) women will have the chance to be retrained in IT. The main page of the TechUP project is here.
- Innovative Computing
- Adaptive, personalised web
- Applied AI
- Learner Analytics Data Analytics
- Semantic Web
- Social Web
- User Modelling
- Web Science
- Tsakalidis, Adam, Papadopoulos, Symeon, Voskaki, Rania, Ioannidou, Kyriaki, Boididou, Christina, Cristea, A.I., Liakata, Maria & Kompatsiaris, Yiannis (2018). Building and evaluating resources for sentiment analysis in the Greek language. Language Resources and Evaluation
- Gkiokas, Alexandros & Cristea, A. I. (2018). Cognitive agents and machine learning by example representation with conceptual graphs. Computational Intelligence 34(2): 603-634.
- Qaffas, Alaa A. Cristea, A.I. & Mead, Mohamed A. (2018). Lightweight adaptive E-Advertising Model. Journal of Universal Computer Science 24(7): 935-974.
- Suncica Hadzidedic Bazdarevic & Cristea, A. I. (2017). Do personalisation and emotions affect the use of cancer-related websites?. Online Information Review 41(1): 102-118.
- Shi, Lei & Cristea, A. I. (2016). Learners thrive when using multifaceted open social learner models. IEEE MultiMedia 23(1): 36-47.
- Tsakalidis,Adam Papadopoulos, S. Cristea, A. I. & Kompatsiaris, Yiannis (2015). Predicting elections for multiple countries using Twitter and polls. IEEE Intelligent Systems 30(2): 10-17.
- Gkotsis, George Stepanyan, Karen Cristea, A. I. & Joy, Mike (2014). Entropy-based automated wrapper generation for weblog data extraction. World Wide Web 17(4): 827-846
- Cristea, A. I., Katsaros, Dimitrios & Manolopoulos, Yannis (2014). Introduction to the special issue of the journal World Wide Web: Social media preservation and applications. World Wide Web 17(4): 691-693.
- Ashman, Helen Brailsford, Tim Cristea, A. I., Sheng, Quan Z. Stewart, Craig Toms, Elaine G. & Wade, Vincent (2014). The ethical and social implications of personalization technologies for e-learning. Information & Management 51(6): 819-832.
Chapter in book
- Zhou, Yiwei, Demidova, Elena & Cristea, A. I. (2017). What’s new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval. In Transactions on Computational Collective Intelligence XXVI. Nguyen, N., Kowalczyk, R., Pinto, A. & Cardoso, J. Cham: Springer. 10190: 2010-231.
- Shi, Lei Cristea, A. I. & Hadzidedic, Suncica (2014). Multifaceted open social learner modelling. In Advances in Web-Based Learning – ICWL 2014, 13th International Conference, Tallinn, Estonia, August 14-17, 2014, Proceedings. Popescu. Elvira Lau, Rynson W. H. Pata, Kai Leung, Howard & Mart, Laanpere Cham: Springer. 8613: 32-42.
- Yiwei Zhou & Cristea, A. I. (2017), Connecting targets to tweets semantic attention-based model for target-specific stance detection, in Bouguettaya, Athman Gao, Yunjun Klimenko, Andrey Chen, Lu Zhang, Xiangliang Dzerzhinskiy, Fedor Jia, Weijia Klimenko, Stanislav V. & Li, Qing eds, Lecture Notes in Computer Science 10569: Web Information Systems Engineering – WISE 2017, 18th International Conference. Moscow, Springer, Cham, 18-32.
- Tsakalidis, Adam Liakata, Maria Damoulas, Theodoros Jellinek, Brigitte Guo, Weisi & Cristea, A. I. (2016), Combining heterogeneous user generated data to sense well-being, in Matsumoto, Yuji & Prasad, Rashmi eds,COLING 2016. Osaka, The COLING 2016 Organizing Committee, 3007-3018.
- Shi, Lei & Cristea, A. I. (2016), Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning, in Micarelli, Alessandro, Stamper, John & Panourgia, Kitty eds, Lecture Notes in Computer Science 9684: Intelligent Tutoring Systems, 13th International Conference, ITS 2016. Zagreb, Springer, 294-300.
- Zhou, Yiwei Kanhabua, N. & Cristea, A. I. (2016), Real-time timeline summarisation for high-impact events in Twitter, in Kaminka, Gal A. Fox, Maria Bouquet, Paolo Hüllermeier, Eyke Dignum, Virginia Dignum, Frank & Harmelen, Frank van eds, Frontiers in Artificial Intelligence and Applications 285: ECAI 2016. The Hague, IOS Press, 1158-1166.
- Zhou, Yiwei & Cristea, A. I. (2016), Towards detection of influential sentences affecting reputation in Wikipedia, in Nejdl, Wolfgang eds, ACM Web Science Conference 2016. Hannover, ACM, New York, 244-248.
- Zhou, Yiwei Demidova, Elena & Cristea, A. I. (2016), Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia, 1: SAC 2016, 31st ACM Symposium on Applied Computing. Pisa, ACM, New York, 750-757.
- Lei Shi, Cristea, A. I., Awan, M. S. K. (Malik Shahzad K.), Hendrix, Maurice & Stewart, Craig (2013), Towards understanding learning behavior patterns in social adaptive personalized e-learning systems, 5: 19th Americas Conference on Information Systems. Chicago, AMCIS, 3678.
- Gkotsis, George Stepanyan, Karen Cristea, A. I. & Joy, Mike (2013), Zero-cost labelling with web feeds for weblog data extraction, 23rd International World Wide Web Conference (WWW 2013). International World Wide Web Conferences Steering Committee, 73-74.
Available for media contact about:
- Computer Science: Web Science
- Computer Science: Learner Analytics
- Education: Learner Analytics
Professor Toby Breckon
Professor in the Department of Computer Science
(email at firstname.lastname@example.org)
Toby Breckon is a Professor in the Innovative Computing Group at the Department of Engineering and Department of Computer Science at Durham University and a tutor at St. Chads College. He leads research in computer vision, image processing and robotic sensing with a strong emphasis on generalised machine learning and pattern recognition approaches.
Before joining Durham in 2013, he held faculty positions at the School of Engineering, Cranfield University, the UK’s only postgraduate-only university, and the School of Informatics, University of Edinburgh. Prior to this he was a mobile robotics research engineer with the UK MoD (DERA) and QinetiQ as well as holding prior positions with the schools inspectorate OFSTED, the Scottish Language Dictionaries organisation and dot-com software house Orbital Software.
He has held a visiting faculty positions at ESTIA (Ecole Supérieure des Technologies Industrielles Avancées, South-West France), Northwestern Polytechnical University (Xi’an, China), Waseda University (Kitakyushu, Japan) and Shanghai Jiao Tong University (Shanghai, China) specializing in aspects of computer vision and machine learning.
His key research interests, in the domain of applied computer vision & robotics, are as follows: automotive computer vision, automated X-ray security screening, vision in built environments, sensor fusion, visual surveillance and sensing for autonomous vehicles He has a range of publications and leads several funded research projects in these areas.
In 2008 he led the development of image-based automatic threat detection for the the Stellar Team’s SATURN multi-platform robot system in the MoD Grand Challenge. The team went on to win the challenge and were awarded the R.J. Mitchell Trophy for innovation by the UK MoD (2008) and later the Finmeccanica Group Innovation Award (2009). The ongoing achievements of this innovative work were also recognised by an IET Award for Innovation (Team Category, 2009)
His research work is recognised by the Royal Photographic Society Selwyn Award (2011) for a significant early career contribution to imaging science.
- Innovative Computing
- Autonomous sensing
- Computer vision
- Image processing
- Machine learning
- Robotic sensing
- Atapour-Abarghouei, A. & Breckon, T.P. (2018). A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion. Computers and Graphics 72: 39-58.
- Qian, C., Breckon, T.P. & Xu, Z. (2018). Clustering in pursuit of temporal correlation for human motion segmentation. Multimedia Tools and Applications 77(15): 19615-19631.
- Akcay, S., Kundegorski, M.E., Willcocks, C.G. & Breckon, T.P. (2018). Using Deep Convolutional Neural Network Architectures for Object Classification and Detection within X-ray Baggage Security Imagery. IEEE Transactions on Information Forensics & Security 13(9): 2203-2215.
- Zhang, W., Zhao, Y., Breckon, T.P. & L. Chen (2017). Noise Robust Image Edge Detection based upon the Automatic Anisotropic Gaussian Kernels. Pattern Recognition 63(8): 193-205.
- Mouton, A. & Breckon, T.P. (2015). A Review of Automated Image Understanding within 3D Baggage Computed Tomography Security Screening. Journal of X-Ray Science and Technology 23(5): 531-555.
- Chermak, L., Breckon, T.P., Flitton, G.T. & Megherbi, N. (2015). Geometrical approach for automatic detection of liquid surfaces in 3D computed tomography baggage imagery. Imaging Science Journal
- Mouton, A. & Breckon, T.P. (2015). Materials-Based 3D Segmentation of Unknown Objects from Dual-Energy Computed Tomography Imagery in Baggage Security Screening. Pattern Recognition 48(6): 1961-1978.
- Flitton, G.T., Mouton, A. & Breckon, T.P. (2015). Object Classification in 3D Baggage Security Computed Tomography Imagery using Visual Codebooks. Pattern Recognition 48(8): 2489-2499.
- Kriechbaumer, T., Blackburn, K., Breckon, T.P., Hamilton, O. & Riva-Casado, M. (2015). Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications. Sensors15(12): 31869-31887.
- Breszcz, M. & Breckon, T.P. (2015). Real-time Construction and Visualization of Drift-Free Video Mosaics from Unconstrained Camera Motion. The Journal of Engineering 2015(16): 1-12.
- Qian, Cheng, Breckon, Toby P. & Li, Hui (2015). Robust visual tracking via speedup multiple kernel ridge regression. Journal of Electronic Imaging 24(5): 053016
- Flitton, G., Breckon, T.P. & Megherbi, N. (2013). A comparison of 3D interest point descriptors with application to airport baggage object detection in complex CT imagery. Pattern Recognition 46(9): 2420-2436
- Mouton, A., Megherbi, N., Van Slambrouck, K., Nuyts, J. & Breckon, T.P. (2013). An Experimental Survey of Metal Artefact Reduction in Computed Tomography. Journal of X-Ray Science and Technology 21(2): 193-226.
- Magnabosco, M. & Breckon, T.P. (2013). Cross-Spectral Visual Simultaneous Localization And Mapping (SLAM) with Sensor Handover. Robotics and Autonomous Systems 63(2): 195-208.
- Breckon, T.P. & Fisher, R.B. (2012). A hierarchical extension to 3D non-parametric surface relief completion. Pattern Recognition 45(1): 172-185.
- Mroz, F. & Breckon, T.P. (2012). An Empirical Comparison of Real-time Dense Stereo Approaches for use in the Automotive Environment. EURASIP Journal on Image and Video Processing 2012: 13.
- Kheyrollahi, A. & Breckon, T.P. (2012). Automatic Real-time Road Marking Recognition Using a Feature Driven Approach. Machine Vision and Applications 23(1): 123-133.
- Han, J., Breckon, T.P., Randell, D.A. & Landini, G. (2012). The Application of Support Vector Machine Classification to Detect Cell Nuclei for Automated Microscopy. Machine Vision and Applications 23(1): 15-24.
- Tang, I. & Breckon, T.P. (2011). Automatic Road Environment Classification. IEEE Transactions on Intelligent Transportation Systems 12(2): 476-484.
- Breckon, T.P., Jenkins, K.W. & Sonkoly, P. (2011). Realizing Perceptive Virtual Reality Imaging Applications on Conventional PC Hardware. Imaging Science Journal 59(1): 1-7.
- Landini, G., Randell, D.A., Breckon, T.P. & Han, J. (2010). Morphologic Characterization of Cell Neighborhoods in Neoplastic and Preneoplastic Epithelium. Analytical and Quantitative Cytology and Histology 32(1): 30-38.
- Breckon, T.P. & Fisher, R.B. (2008). Three-Dimensional Surface Relief Completion Via Nonparametric Techniques. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(12): 2249-2255.
- Breckon, T.P. & Fisher, R.B. (2005). Amodal Volume Completion: 3D Visual Completion. Computer Vision and Image Understanding 99(3): 499-526.
- Fisher, R.B., Breckon, T.P., Dawson-Howe, K., Fitzgibbon, A., Robertson, C., Trucco, E. & Williams, C.K.I. (2014). Dictionary of Computer Vision and Image Processing. Wiley.
- Solomon, C.J. & Breckon, T.P. (2013). Fundamentos de Processamento Digital de Imagens – Uma Abordagem Pratica com Exemplos em Matlab. LTC (Brazil).
- Solomon, C.J. & Breckon, T.P. (2010). Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab. Wiley-Blackwell.
- Holder, C.J. & Breckon, T.P. (2018), Encoding Stereoscopic Depth Features for Scene Understanding in Off-Road Environments, 15th International Conference on Image Analysis and Recognition (ICIAR 2018). Póvoa de Varzim, Portugal, Springer.
- Dunnings, A. & Breckon, T.P. (2018), Experimentally Defined Convolutional Neural Network Architecture Variants for Non-temporal Real-time Fire Detection, 25th IEEE International Conference on Image Processing (ICIP). Athens, Greece, IEEE.
- Atapour-Abarghouei, A. & Breckon, T.P. (2018), Extended Patch Prioritization For Depth Hole Filling Within Constrained Exemplar-Based RGB-D Image Completion, 15th International Conference on Image Analysis and Recognition (ICIAR 2018). Póvoa de Varzim, Portugal, Springer.
- Maciel-Pearson, B.G., Carbonneau, P. & Breckon, T.P. (2018), Extending Deep Neural Network Trail Navigation for Unmanned Aerial Vehicle Operation within the Forest Canopy, Lecture Notes in Computer Science 19th Towards Autonomous Robotic Systems (TAROS) Conference. Bristol, Springer, 1-11.
- Dong, Z., Kamata, S. & Breckon, T.P. (2018), Infrared Image Colorization Using S-Shape Network, 25th IEEE International Conference on Image Processing (ICIP). Athens, Greece, IEEE.
- Holder, C. & Breckon, T.P. (2018), Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction, The 29th Intelligent Vehicles Symposium (IEEE IV 2018). Changshu, China, IEEE.
- Alshammari, N., Akcay, S. & Breckon, T.P. (2018), On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding, The 29th IEEE Intelligent Vehicles Symposium (IEEE IV 2018). Changshu, China, IEEE.
- Loveday, M. & Breckon, T.P. (2018), On the Impact of Parallax Free Colour and Infrared Image Co-Registration to Fused Illumination Invariant Adaptive Background Modelling, Computer Vision and Pattern Recognition Workshops (CVPR) 2018. Salt Lake City, Utah, IEEE.
- Guo, T., Akcay, S., Adey, P. & Breckon, T.P. (2018), On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks, 25th IEEE International Conference on Image Processing (ICIP). Athens, Greece, IEEE.
- Lin, K. & Breckon, T.P. (2018), Real-time Low-Cost Omni-directional Stereo Vision via Bi-Polar Spherical Cameras,15th International Conference on Image Analysis and Recognition (ICIAR 2018). Póvoa de Varzim, Springer.
- Atapour-Abarghouei, A. & Breckon, T.P. (2018), Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation, 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Salt Lake City, Utah, IEEE, 1-8.
- Maciel-Pearson, B.G. & Breckon, T.P. (2017), An Optimised Deep Neural Network Approach for Forest Trail Navigation for UAV Operation within the Forest Canopy, The UK-RAS Network Conference on Robotics and Autonomous Systems: robots working for and among us. Bristol, UK Robotics and Autonomous Systems Network, 1-3.
- Atapour-Abarghouei, A. & Breckon, T.P. (2017), DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation, 28th British Machine Vision Conference (BMVC) 2017. London, British Machine Vision Association (BMVA).
- Wu, R., Kamata, S. & Breckon, T.P. (2017), Face Recognition via Deep Sparse Graph Neural Networks, British Machine Vision Conference Workshops. London, British Machine Vision Association (BMVA).
- Sugimoto, K., Breckon, T.P. & Kamata, S. (2016), Constant-time Bilateral Filter using Spectral Decomposition, 2016 IEEE International Conference on Image Processing (ICIP). Phoenix, AZ, USA, IEEE, Piscataway, NJ, 3319-3323.
- Katramados, I. & Breckon, T.P. (2016), Dense Gradient-based Features (DeGraF) for Computationally Efficient and Invariant Feature Extraction in Real-time Applications, 2016 IEEE International Conference on Image Processing. Phoenix, AZ, USA, IEEE, Piscataway, NJ, 300-304.
- Holder, C.J., Breckon, T.P. & Wei, X. (2016), From On-Road to Off: Transfer Learning within a Deep Convolutional Neural Network for Segmentation and Classification of Off-Road Scenes, in Hua, Gang & Jégou, Hervé eds, Lecture Notes in Computer Science 9913: European Conference on Computer Vision Workshops. Amsterdam, Springer, Cham, Switzerland, 149-162.
- Hamilton, O.K. & Breckon, T.P. (2016), Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow, 2016 IEEE International Conference on Image Processing. Phoenix, AZ, USA, IEEE, Piscataway, NJ, 3439-3443.
- Kundegorski, M.E., Akcay, S., Devereux, M., Mouton, A. & Breckon, T.P. (2016), On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening, International Conference on Imaging for Crime Detection and Prevention. Madrid, Spain, IET, 12 (6).
- Kundegorski, M.E., Akcay, S., Payen de La Garanderie, G. & Breckon, T.P. (2016), Real-time Classification of Vehicle Types within Infra-red Imagery, in Burgess, D., Owen, G., Bouma, H., Carlysle-Davies, F., Stokes, R.J. & Yitzhaky, Y. eds, Proceedings of SPIE 9995: Optics and Photonics for Counterterrorism, Crime Fighting and Defence XII. Edinburgh, United Kingdom, SPIE (Society of Photo-optical Instrumentation Engineers), Washington, USA, 99950T.
- Al Moubayed, N., Breckon, T.P., Matthews, P.C. & McGough, A.S. (2016), SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder, in Villa, Alessandro E.P., Masulli, Paolo & Pons Rivero, Antonio J. eds, Lecture Notes in Computer Science 9887: Springer International Publishing, Cham, 423-430.
- Thomas, P.A., Marshall, G.F., Faulkner, D., Kent, P., Page, S., Islip, S., Oldfield, J., Breckon, T.P., Kundegorski, M.E., Clarke, D. & Styles, T. (2016), Toward Sensor Modular Autonomy for Persistent Land Intelligence Surveillance and Reconnaissance (ISR), in Kolodny, Michael A. & Pham, Tien eds, Proceedings of SPIE 9831: SPIE Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent Intelligence Surveillance and Reconnaissance VII. Baltimore, Maryland, SPIE, Bellingham, WA, 983108.
- Akcay, S., Kundegorski, M.E., Devereux, M. & Breckon, T.P. (2016), Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery, 2016 IEEE International Conference on Image Processing. Phoenix, AZ, USA, IEEE, Piscataway, NJ, 1057-1061.
- Cavestany, P., Rodríguez, A.L., Martínez-Barberá, H. & Breckon, T.P. (2015), Improved 3D sparse maps for high-performance SFM with low-cost omnidirectional robots, IEEE International Conference on Image Processing. Québec City, Canada, IEEE, Québec City, 4927-4931.
- Webster, D.D. & Breckon, T.P. (2015), Improved raindrop detection using combined shape and saliency descriptors with scene context isolation, Proceedings of IEEE International Conference on Image Processing. Québec City, Canada, IEEE, Québec City, 4376-4380.
- Kundegorski, M.E. & Breckon, T.P. (2015), Posture Estimation for Improved Photogrammetric Localization of Pedestrians in Monocular Infrared Imagery, Optics and Photonics for Counterterrorism, Crime Fighting and Defence. Toulouse, France, SPIE, Toulouse.
- Mouton, A., Breckon, T.P., Flitton, G.T. & Megherbi, N. (2014), 3D object classification in baggage computed tomography imagery using randomised clustering forests, Proc. International Conference on Image Processing. IEEE, 5202-5206.
- Walger, D.J., Breckon, T.P., Gaszczak, A. & Popham, T. (2014), A Comparison of Features for Regression-based Driver Head Pose Estimation under Varying Illumination Conditions, Proc. International Workshop on Computational Intelligence for Multimedia Understanding. IEEE, 1-5.
- Kundegorski, M.E. & Breckon, T.P. (2014), A photogrammetric approach for real-time 3D localization and tracking of pedestrians in monocular infrared imagery, 9253: Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence. SPIE, 1-16.
- Payen de La Garanderie, G. & Breckon, T.P. (2014), Improved Depth Recovery In Consumer Depth Cameras via Disparity Space Fusion within Cross-spectral Stereo, in Valstar, Michel, French, Andrew & Pridmore, Tony eds,Proceedings of the British Machine Vision Conference. BMVA Press, 417.1-417.12.
- Kurcius, J.J. & Breckon, T.P. (2014), Using Compressed Audio-visual Words for Multi-modal Scene Classification,Proc. International Workshop on Computational Intelligence for Multimedia Understanding. IEEE.
- Mouton, A., Megherbi, N., Breckon, T.P., Van Slambrouck, K. & Nuyts, J. (2013), A Distance Weighted Method for Metal Artefact Reduction in CT, Proc. International Conference on Image Processing. IEEE, pp. 2334-2338.
- Hamilton, O.K., Breckon, T.P., Bai, X. & Kamata, S. (2013), A Foreground Object based Quantitative Assessment of Dense Stereo Approaches for use in Automotive Environments, Proc. International Conference on Image Processing. IEEE, pp. 418-422.
- Faria, J., Bagley, S., Rueger, S. & Breckon, T.P. (2013), Challenges of Finding Aesthetically Pleasing Images, Proc. International Workshop on Image and Audio Analysis for Multimedia Interactive Services. IEEE, 1-4.
- Mioulet, L., Breckon, T.P., Mouton, A., Liang, H. & Morie, T. (2013), Gabor Features for Real-Time Road Environment Classification, Proc. International Conference on Industrial Technology. IEEE, 1117-1121.
- Han, J., Gaszczak, A., Maciol, R., Barnes, S.E. & Breckon, T.P. (2013), Human Pose Classification within the Context of Near-IR Imagery Tracking, 8901: Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence. SPIE, 1-10.
- Mise, O. & Breckon, T.P. (2013), Image Super-Resolution applied to moving targets in high dynamics scenes, 8899: Proc. SPIE Emerging Technologies in Security and Defence: Unmanned Sensor Systems. SPIE, 1-12.
- Turcsany, D., Mouton, A. & Breckon, T.P. (2013), Improving Feature-based Object Recognition for X-ray Baggage Security Screening using Primed Visual Words, Proc. International Conference on Industrial Technology. IEEE, 1140-1145.
- Megherbi, N., Breckon, T.P. & Flitton, G.T. (2013), Investigating Existing Medical CT Segmentation Techniques within Automated Baggage and Package Inspection, 8901: Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence. SPIE, 1-8.
- Breckon, T.P., Gaszczak, A., Han, J., Eichner, M.L. & Barnes, S.E. (2013), Multi-Modal Target Detection for Autonomous Wide Area Search and Surveillance, 8899: Proc. SPIE Emerging Technologies in Security and Defence: Unmanned Sensor Systems. SPIE, 1-19.
- Megherbi, N., Breckon, T.P., Flitton, G.T. & Mouton, A. (2013), Radon Transform based Metal Artefacts Generation in 3D Threat Image Projection, 8901: Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence. SPIE, 1-7.
- Chereau, R. & Breckon, T.P. (2013), Robust Motion Filtering as an Enabler to Video Stabilization for a Tele-operated Mobile Robot, 8897: Proc. SPIE Electro-Optical Remote Sensing, Photonic Technologies, and Applications VII. SPIE, 1-17.
- Flitton, G., Breckon, T.P. & Megherbi, N. (2012), A 3D extension to cortex like mechanisms for 3D object class recognition, n/a: 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, RI, USA, IEEE, Providence RI, 3634-3641
- Megherbi, N., Han, J., Flitton, G.T. & Breckon, T.P. (2012), A Comparison of Classification Approaches for Threat Detection in CT based Baggage Screening, Proc. International Conference on Image Processing. IEEE, 3109-3112.
- Mouton, A., Megherbi, N., Flitton, G.T., Bizot, S. & Breckon, T.P. (2012), A Novel Intensity Limiting Approach to Metal Artefact Reduction in 3D CT Baggage Imagery, Proc. International Conference on Image Processing. IEEE, 2057-2060.
- Breckon, T.P., Han, J. & Richardson, J. (2012), Consistency in Muti-modal Automated Target Detection using Temporally Filtered Reporting, 8542: Proc. SPIE Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI. 23:1-23:12.
- Carey, D., Shepherd, N., Kendall, C., Stone, N., Breckon, T.P. & Lloyd, G.R. (2012), Correlating Histology and Spectroscopy to Differentiate Pathologies of the Colon, Proc. Conference on Medical Image Understanding and Analysis. 243-248.
- Megherbi, N., Breckon, T.P., Flitton, G.T. & Mouton, A. (2012), Fully Automatic 3D Threat Image Projection: Application to Densely Cluttered 3D Computed Tomography Baggage Images, Proc. International Conference on Image Processing Theory, Tools and Applications. IEEE, 153-159.
- Pinggera, P., Breckon, T.P. & Bischof, H. (2012), On Cross-Spectral Stereo Matching using Dense Gradient Features, Proc. British Machine Vision Conference. 526.1-526.12.
- Chenebert, A., Breckon, T.P. & Gaszczak, A. (2011), A Non-temporal Texture Driven Approach to Real-time Fire Detection, Proc. International Conference on Image Processing. IEEE, 1781-1784.
- Bordes, L., Breckon, T.P., Katramados, I. & Kheyrollahi, A. (2011), Adaptive Object Placement for Augmented Reality Use in Driver Assistance Systems, Proc. 8th European Conference on Visual Media Production. sp-1.
- Breszcz, M., Breckon, T.P. & Cowling, I. (2011), Real-time Mosaicing from Unconstrained Video Imagery for UAV Applications, Proc. 26th International Conference on Unmanned Air Vehicle Systems. 32.1-32.8.
- Gaszczak, A., Breckon, T.P. & Han, J. (2011), Real-time People and Vehicle Detection from UAV Imagery, 7878: Proc. SPIE Conference Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques.
- Katramados, I. & Breckon, T.P. (2011), Real-time Visual Saliency by Division of Gaussians, Proc. International Conference on Image Processing. IEEE, 1741-1744.
- Heras, A.M., Breckon, T.P. & Tirovic, M. (2011), Video Re-sampling and Content Re-targeting for Realistic Driving Incident Simulation, Proc. 8th European Conference on Visual Media Production. sp-2.
- Megherbi, N., Flitton, G.T. & Breckon, T.P. (2010), A Classifier based Approach for the Detection of Potential Threats in CT based Baggage Screening, Proc. International Conference on Image Processing. IEEE, 1833-1836.
- Kowaliszyn, M. & Breckon, T.P. (2010), Automatic Road Feature Detection and Correlation for the Correction of Consumer Satellite Navigation System Mapping, Proc. IET/ITS Conference on Road Transport Information and Control. IET, 2-9.
- Sokalski, J., Breckon, T.P. & Cowling, I. (2010), Automatic Salient Object Detection in UAV Imagery, Proc. 25th International Conference on Unmanned Air Vehicle Systems. 11.1-11.12.
- Flitton, G.T., Breckon, T.P. & Megherbi, N. (2010), Object Recognition using 3D SIFT in Complex CT Volumes,Proc. British Machine Vision Conference. 11.1-12.
- Breckon, T.P., Barnes, S.E., Eichner, M.L. & Wahren, K. (2009), Autonomous Real-time Vehicle Detection from a Medium-Level UAV, Proc. 24th International Conference on Unmanned Air Vehicle Systems. 29.1-29.9.
- Wahren, K., Cowling, I., Patel, Y., Smith, P. & Breckon, T.P. (2009), Development of a Two-Tier Unmanned Air System for the MoD Grand Challenge, Proc. 24th International Conference on Unmanned Air Vehicle Systems. 13.1 – 13.9.
- Katramados, I., Crumpler, S. & Breckon, T.P. (2009), Real-Time Traversable Surface Detection by Colour Space Fusion and Temporal Analysis, Lecture Notes in Computer Science 5815: Proc. International Conference on Computer Vision Systems. Springer, 265-274.
- Golebiowski, R., Breckon, T.P. & Flitton, G.T. (2009), Volumetric Representation for Interactive Video Editing, Proc. 6th European Conference on Visual Media Production. IET, 13.
- Desile, Q. & Breckon, T.P. (2008), 3D Colour Mesh Detail Enhancement Driven from 2D Texture Edge Information,Proc. 5th European Conference on Visual Media Production. IET, SP-4.
- Eichner, M. L. & Breckon, T.P. (2008), Augmenting GPS Speed Limit Monitoring with Road Side Visual Information,Proc. IET/ITS Conference on Road Transport Information and Control. IET, 1-5.
- Rzeznik, J., Barnes, S.E. & Breckon, T.P. (2008), Gesture Recognition using a Laser Pointer, Proc. 5th European Conference on Visual Media Production. IET, SP-1.
- Eichner, M. L. & Breckon, T.P. (2008), Integrated Speed Limit Detection and Recognition from Real-Time Video,Proc. IEEE Intelligent Vehicles Symposium. IEEE, 626-631.
- Han, J., Breckon, T.P., Randell, D.A. & Landini, G. (2008), Radicular cysts and odontogenic keratocysts epithelia classification using cascaded Haar classifiers, Proc. 12th Annual Conference on Medical Image Understanding and Analysis. 54-58.
- Breckon, T.P. (2007), 3D Measurement for Asset and Environment Authentication and Analysis, Proc. 4th International Conference on Condition Monitoring. British Institute of Non-Destructive Testing, 1-10.
- Zirnhelt, S. & Breckon, T.P. (2007), Artwork Image Retrieval using Weighted Colour and Texture Similarity, Proc. 4th European Conference on Visual Media Production. IET, II-8.
- Li, X. & Breckon, T.P. (2007), Combining Motion Segmentation and Feature Based Tracking for Object Classification and Anomaly Detection, Proc. 4th European Conference on Visual Media Production. IET, I-6.
- Flitton, G.T. & Breckon, T.P. (2007), Considering Video as a Volume, Proc. 4th European Conference on Visual Media Production. IET, II-7.
- Eichner, M. L. & Breckon, T.P. (2007), Real-Time Video Analysis for Vehicle Lights Detection using Temporal Information, Proc. 4th European Conference on Visual Media Production. IET, I-9.
- Breckon, T.P. & Fisher, R.B. (2006), Direct Geometric Texture Synthesis and Transfer on 3D Meshes, Proc. 3rd European Conference on Visual Media Production. IET, 186.
- Breckon, T.P. & Fisher, R.B. (2005), A Non-parametric Approach to Realistic Surface Completion in 3D Environments, Proc. Postgraduate Research Conference in Electronics, Photonics, Communications and Networks, and Computing Science. EPSRC, 122.
- Breckon, T.P. & Fisher, R.B. (2005), Non-parametric 3D Surface Completion, Proc. Fifth International Conference on 3D Digital Imaging and Modeling. IEEE, 573-580.
- Breckon, T.P. & Fisher, R.B. (2005), Plausible 3D Colour Surface Completion using Non-parametric Techniques, Lecture Notes in Computer Science 3604: Proc. Mathematics of Surfaces XI Institute of Mathematics and its Applications. Springer-Verlag, 102-120.
- Breckon, T.P. & Fisher, R.B. (2004), Environment Authentication through 3D Structural Analysis, Lecture Notes in Computer Science 3211: Proc. International Conference on Image Analysis and Recognition. Springer-Verlag, 680-687.
- T.P. Breckon (2006). Completing Unknown Portions of 3D Scenes via 3D Visual Propogation. School of Informatics, University of Edinburgh. PhD.
Available for media contact about:
- Computer Science: image processing
- Computer Science: object recognition
- Computer Science: computer vision
- Computer Science: robotic sensing
- Computer Science: machine learning
Dr Steven Bradley
Associate Professor (Teaching) in the Department of Computer Science
(email at email@example.com)
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. Since 2013 he has been a full-time teaching fellow in the school of Engineering and Computing Sciences.
Indicators of Esteem
- 2017: Excellence in Learning & Teaching Award: Awarded by Durham University in June 2017
- Innovative Computing
Department of Sociology
- Children’s hospice service data mapping project 2011/12
- Mapping Unit
- Computer Science education
- Citizen science
- Knowledge representation and student learning
- Web-based data collection
- Real-time systems
- Software engineering
- 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.
- 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.
- 2014: google CS4HS (Computer Science for High Schools) award $12k for work on Computer Science Into Schools
- 2013: Durham University Enhancing the Student Learning Experience (ESLE) award: FOCUS Diagnostics – the development of an online diagnostic and instructional toolkit to enhance student understanding of subject specific language
Dr Suncica Hadzidedic
Assistant Professor in the Department of Computer Science
Dr Hadzidedic is an Assistant Professor in the Department of Computer Science at Durham University. She obtained a BSc (First Class Hons) in Information Systems from the University Sarajevo School of Science and Technology (SSST), B&H, and University of Buckingham, UK. She holds an MSc in IT Management from Binary University, Malaysia. In 2018, she was awarded a PhD in Computer Science from the University of Warwick, UK. She worked as a lecturer and a researcher at the University SSST from 2017 to 2019, during which time she joined two EU projects: Erasmus+ e-VIVA (Enhancing and Validating servIce related competences in Versatile learning environments in Western BAlkan Universities) and EU COST Action VascAgeNet (Network for Research in Vascular Aging).
Broadly, her research interests are in human-computer interaction, affective computing and online privacy. She has published research on web personalisation, specifically affect-adaptive user interfaces and affective recommender systems applied to online cancer services. In collaboration with a B&H cancer association, she developed PORT.org.ba, a real-life cancer website providing emotion-based content recommendations and UI adaptation. Her current research is on socially responsible AI, with a particular focus on affect-aware Intelligent Tutoring Systems for students with mood disorders.
- Human-computer interaction
- Web personalisation / user modelling
- Affective (context-aware) recommender systems
- Intelligent tutoring systems
- Behavioural analytics
- Applied machine learning in healthcare
- Online privacy
- Begic, Edin, Hadzidedic, Suncica, Kulaglic, Ajla, Ramic-Brkic, Belma, Begic, Zijo & Causevic, Mirsada (2019). SOMAscan-based proteomic measurements of plasma brain natriuretic peptide are decreased in mild cognitive impairment and in Alzheimer’s dementia patients. PLOS ONE 14(2): e0212261.
- Hadzidedic Bazdarevic, S. & Cristea, A. I. (2017). Do personalisation and emotions affect the use of cancer-related websites?. Online Information Review 41(1): 102-118.
- Hadzidedic Bazdarevic, S. & Cristea, A.I. (2015). How emotions stimulate people affected by cancer to use personalised health websites. Knowledge Management & E-learning: An International Journal 7(4): 658-676.
Chapter in book
- Shi, L., Cristea, A.I., Hadzidedic, S. & Dervishalidovic, N. (2014). Contextual Gamification of Social Interaction – Towards Increasing Motivation in Social E-learning. In Advances in Web-Based Learning – ICWL 2014. 8613: 116.
- Shi, L. Cristea, A. I. & Hadzidedic, S. (2014). Multifaceted open social learner modelling. In Advances in Web-Based Learning – ICWL 2014, 13th International Conference, Tallinn, Estonia, August 14-17, 2014, Proceedings. Popescu. Elvira Lau, Rynson W. H. Pata, Kai Leung, Howard & Mart, Laanpere Cham: Springer. 8613: 32-42.
- Ramic-Brkic, B, Balik, A, Pistoljevic, N & Hadzidedic, S. (2019), Web Tool for Creating Educational/Therapeutic Programmes, 11th International Conference on Virtual Worlds and Games for Serious Applications. Vienna, Austria.
- Al Qudah, Dana A., Cristea, A.I., Hadzidedic Bazdarevic, S., Al-Saqqa, Samar & Al-Sayyad, Rizik M. H. (2015), A Taxonomy-Based Evaluation of Personalized E-Advertisement, IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. 395.
- Al Qudah, Dana A., Cristea, A.I., Hadzidedic Bazdarevic, S., Al-Saqqa, Samar, Rodan, Ali & Yang, Wei (2015), Personalized E-Advertisement and Experience: Recommending User Targeted Ads, IEEE 12th International Conference on e-Business Engineering. 56.
- Hadzidedic Bazdarevic, S. & Cristea, A.I. (2015), What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina, Fifth International Conference on Social Medial Technologies, Communication and Informatics (SOTICS). Barcelona, Spain.
- Shi, L, Cristea, AI & Hadzidedic, S (2014), The Critical Role of Profiles in Social E-Learning Design, 15th Annual Conference on Information Technology Education (SIGITE). Atlanta, Georgia, US.
- Hadzidedic, S, Dervishalidovic, N, Pandzo, A & Ramic-Brkic, B (2013), Use of Student Response Systems in Higher Education in Bosnia and Herzegovina, Recent Advances in Information Systems, Proceedings of the 7th European Computing Conference, WSEAS. Dubrovnik, Croatia.