Academics

Professor Toby Breckon

Professor

Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 42396
Professor in the Department of Engineering

(email at toby.breckon@durham.ac.uk)

Biography

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 EngineeringCranfield University, the UK’s only postgraduate-only university, and the School of InformaticsUniversity 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 visionautomated X-ray security screening, vision in built environmentssensor fusionvisual 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.

Research Groups

  • Innovative Computing

Research Interests

  • Autonomous sensing
  • Computer vision
  • Image processing
  • Machine learning
  • Robotic sensing

Publications

Journal Article

Authored book

  • 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.

Conference Paper

Doctoral Thesis

Related Links

Media Contacts

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

Supervises

Dr Boguslaw Obara

Associate Professor

Associate Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 42431
Room number: E290 (christopherson bulding)

Research

http://www.dur.ac.uk/boguslaw.obara/

My key research interests are image processing, pattern recognition, and computer vision applied in a wide range of domains, from biology, medicine, and engineering to arts & humanities.

Appointments

  • Associate Professor / Senior Lecturer / Lecturer, School of Engineering and Computing Sciences, University of Durham, Durham, UK.
  • Postdoctoral Researcher, Oxford e-Research Centre and Oxford Centre for Integrative Systems Biology, University of Oxford, Oxford, UK.
  • Postdoctoral Researcher, Center for BioImage Informatics, University of California, Santa Barbara, CA, USA.
  • Research Assistant, Vision Research Laboratory, University of California, Santa Barbara, CA, USA.
  • Research Assistant, Computer Vision Laboratory, ETH, Zurich, Switzerland.
  • Research Assistant, Polish Academy of Sciences, Krakow, Poland.

Education

  • PhD in Computer Science, AGH University of Science and Technology, Krakow, Poland
  • MSc in Physics, Jagiellonian University, Krakow, Poland

Research Groups

Department of Computer Science

  • Innovative Computing

Department of Biosciences

  • Durham Centre for Bioimaging Technology

Research Projects

Department of History

Research Interests

  • Image Processing
  • Pattern Recognition
  • Computer Vision
  • BioImage Informatics

Selected Publications

Journal Article

Chapter in book

Conference Paper

Show all publications

Media Contacts

Available for media contact about:

  • Computer Science:

Supervises

Dr Donald Sturgeon

Assistant Professor
Assistant Professor in the Department of Computer Science

Contact Dr Donald Sturgeon (email at donald.j.sturgeon@durham.ac.uk)

Publications

Journal Article

Conference Proceeding

Dr Tobias Weinzierl

Associate Professor

Associate Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 42519

Contact Dr Tobias Weinzierl (email at tobias.weinzierl@durham.ac.uk)

Book

T. Weinzierl: A Framework for Parallel PDE Solvers on Multiscale Adaptive Cartesian Grids. Verlag Dr. Hut, München, 2009.

This book is available online though I very much appreciate if you buy it from the publisher.

Book

M. Bader, H.-J. Bungartz and T. Weinzierl (ed.): Advanced Computing, Volume 93 of Lecture Notes in Computational Science and Engineering. Springer-Verlag, Heidelberg, Berlin, 2013.

Indicators of Esteem

Research Groups

  • Innovative Computing

Research Interests

  • High-performance Computing
  • Parallel Algorithms
  • Scientific Computing

Selected Publications

Journal Article

Authored book

Chapter in book

Conference Paper

  • Atanasov, Atanas, Srinivasan, Madhusudhanan & Weinzierl, Tobias (2012), Query-driven Parallel Exploration of Large Datasets, Large Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on. 23 -30.

Newspaper/Magazine Article

Show all publications

Related Links

Supervises

Dr Suncica Hadzidedic

Assistant Professor

Assistant Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 47346
Room number: E231

Contact Dr Sunčica Hadžidedić (email at suncica.hadzidedic@durham.ac.uk)

Biography

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.

Research group

Innovative Computing Group

Research Interests

  • Human-computer interaction
  • Web personalisation / user modelling
  • Affective (context-aware) recommender systems
  • Intelligent tutoring systems
  • Behavioural analytics
  • Applied machine learning in healthcare
  • Online privacy

Publications

Journal Article

Chapter in book

Conference Paper

  • 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-AdvertisementIEEE 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 AdsIEEE 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 HerzegovinaFifth International Conference on Social Medial Technologies, Communication and Informatics (SOTICS). Barcelona, Spain.
  • Shi, LCristea, 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.

Dr Noura Al Moubayed

Assistant Professor

Assistant Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 41749
Room number: E236 (Christopherson Building)

(email at noura.al-moubayed@durham.ac.uk)

Biography

Dr Al Moubayed is an Assistant Professor at the department of computer science in Durham University, and a Visiting Associate Professor at the School of Computing Science in Newcastle University.

Her main research interest is in unsupervised deep learning, natural language processing, and optimisation. Dr Al Moubayed obtained her PhD from the Robert Gordon University, followed by post-doctoral positions in the University of Glasgow and Durham University. She developed machine learning and deep learning solutions in the areas of social signal processing, cyber-security, and Brain-Computer Interfaces. All of which involve high dimensional, noisy and imbalance data challenges.

Indicators of Esteem

  • 2015: Member of the Editorial Board: Artificial Intelligence Research (AIR) Journal, Toronto, Canada Area, since 2015-present
  • Area Chair: Women in Machine Learning Workshop (part of NIPS), 2017
  • Invited Speaker: Re-Work Deep Learning Summit – London, 2017
  • Invited Speaker: Technologies of Crime, Justice and Security Conference, 2018
  • Invited Speaker: e-Crime and Artificial Intelligence forum, London, 2018
  • Invited Speaker and Panel Member: 3rd ACM-W UK Inspire Conference, 2018
  • Keynote Speaker: NVIDIA’s GPU Programming and Machine Learning Workshop ‘Deep Learning Applications powered by GPGPUs’, 2016
  • Member of the Editorial Board:Journal of Autonomous Intelligence, United States. Since 2018 – present
  • Sponsorship Chair: 29th British Machine Vision Conference, 2018
  • Technical Program Committee Chair: ACM Multi Media Conference, 2018

Research Groups

  • Innovative Computing

Research Interests

  • Natural Language Processing
  • Social Robotics
  • Social Signal Processing
  • Anomaly Detection
  • Machine Learning – Deep Learning
  • Unsupervised Feature Learning
  • Evolutionary Computation
  • Multi-Objective Optimisation
  • Brain Computer Interfaces
  • Swarm Intelligence

Selected Publications

Journal Article

Chapter in book

Conference Paper

Doctoral Thesis

Show all publications

Selected Grants

  • 2016: Phase 2: Open Source Big Data Insight. Automated Knowledge Discovery and Classification (Co-Investigator and Named Research Associate. Funding Value: £452,100.00)
  • 2015: Phase 1: Open Source Big Data Insight. Automated Knowledge Discovery and Classification (Co-Investigator and Named Research Associate. Funding Value: £36,173.08)

Professor Alexandra Cristea

Professor

Professor of Computer Science in the Department of Computer Science

Room number: E291

(email at alexandra.i.cristea@durham.ac.uk)

Bio

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.

Publications

Research Groups

  • Innovative Computing

Research Interests

  • Adaptive, personalised web
  • Applied AI
  • Learner Analytics Data Analytics
  • Semantic Web
  • Social Web
  • User Modelling
  • Web Science

Selected Publications

Journal Article

Chapter in book

Conference Paper

Show all publications

Media Contacts

Available for media contact about:

  • Computer Science: Web Science
  • Computer Science: Learner Analytics
  • Education: Learner Analytics

Supervises

Professor Gordon Love

Professor

Head of Department of Computer Science in the Department of Computer Science

Head of Department (g.d.love@durham.ac.uk), Department of Computer Science
Professor in the Department of Physics

(email at g.d.love@durham.ac.uk)

Publications

Google Scholar (most complete)

or see

ResearchID , ORCID Profile, or Scopus

Biography

Conoscopic Image: Lithium Liobate between crossed polarisers

I am the Head of the Department of Computer Science. I took on this role in August 2017 after leading the Group which oversaw the creation of the separate Departments of Engineering and Computer Science – from the old joint School of Engineering and Computing Sciences.

Recent Roles & Responsibilities

Career Summary

Durham University

  •  Professor 2011 – Present
  •  Reader 2005 – 2011
  •  Senior Lecturer 2004 – 2005
  •  Lecturer 1997 – 2004

University of New Mexico, Albuquerque, & USAF Phillips Laboratory, USA

  • Optical Physicist 1995 – 1997

Raman Research Institute, Bangalore, India:

  •  Royal Society Visiting Fellow 1992 – 1993

Visiting Positions

  •  Epiphany Term 2002: Visiting Position at the Cavendish Astrophysics Group, Cambridge.
  •  Epiphany Term 2007: Visiting Position at UC Berkeley, School of Optometry.
  •  Epiphany Term 2012: Visiting Position at the Medical University of Innsbruck,, Austria

 

 

Research Interests

My research involves optics and the physics of light. Much of my work has involved adaptive optics which is a technology used in astronomy to improve the performance of large ground telescopes. The technology, like my research, has diversified and is now used in the biosciences, vision science, and computer graphics.

More generally, I am an applied physicist but I work with colleagues in vision science, computer science, and psychology on problems related to 3D displays, the optics of the eye, and computer graphics.

In Computer Science I work in the Innovative Computer Group. In Physics I work in  the Centre for Advanced Instrumentation.

I have a long standing collaboration with Martin Bank’s Group at Berkeley, working on 3D displays, acccommodation, and some interesting work on animal eyes.


Selected External Appointments

  • External Examiner, University of York, Dept. of Physics, 2016-2020
  • Council Member, Institute of Physics, 2010-2014
  • Conference Chair, Photon14, Imperial College, London, Sept. 2014
  • Member, STFC IPS (Innovations Partnership Scheme) Panel, 2010-2013
  • External Examiner for Imperial College’s MSc in Optics and Photonics, 2007-2010
  • Chair of the Institute of Physics’ Optical Group, 2007-2010 (previously Treasurer and ordinary member).
  • Member of the Royal Society’s International Fellowship Panel, 2007–2010
  • Member the STFC/Royal Society of Edinburgh Enterprise Fellowships Panel, 2009-2012
  • Board Member of the European Optical Society, 2006-2010
  • Member of the Institute of Physics’ Group Coordination Committee, 2008-2014
  • Steering Committee & Research Board Member of the Faraday Partnership in Smart Optics, 2001– 2005

Teaching

I have taught a whole range of courses involving optics, astronomy, electronics, image processing and classical mechanics. I have also taught several external courses (including many years contributing to the SIRA Course on Optical Engineering and Imperial College’s Short Course on Adaptive Optics).

I have been an external PhD. examiner at Cambridge (x3), Edith Cowan (Australia), Glasgow (x2), Heriot Watt (x2), Imperial (x4), Kent, Nottingham, Oxford (x2), Sheffield, St. Andrews, TU Delft (NL), TU Denmark, UC Dublin, UCL.

My competed PhD. students (as primary supervisor) are

This is the “Durham Radio Telescope” on the roof of physics built up by a series of 4th year students working with me.

Colleges

  • I was originally an undergraduate at Van Mildert College
  • I was a College Tutor at St. Cuthbert’s Society from 1993 – 1995
  • I was a College Mentor at Hatfield College from 2008 – 2013
  • I am a visiting fellow at St. Chad’s College in 2016/17

Stereoscopic MonoVision

The following image of a statue and sundial is an example of some of my recent work on stereoscopic vision – showing how the eye synthesises differentially blurred images to produce a sharp whole. The image is a standard-cross-fused stereo image (view the left image with your right eye and vice versa in order to see a 3D image). You will see that as well as the camera position changing slightly between the two shots (which gives the 3D effect) the camera focus has been changed so that in the left hand image the statue is sharp and the gnomon is blurred, and vice versa. If you are able to cross fuse you will see an image where both appear to be sharp. (See link below to higher resolution image which might be easier to view).

Original Paper Higher Resolution Image 

Research Groups

Department of Computer Science

  • Innovative Computing

Centre for Materials Physics

  • Experimental structure and dynamics of biological soft matter

Department of Biosciences

  • Durham Centre for Bioimaging Technology

Department of Physics

  • Centre for Advanced Instrumentation

Research Interests

  • Vision Science
  • 3D Displays
  • Computer Graphics
  • Adaptive Optics
  • Liquid Crystal Technology
  • Image Processing
  • Optics

Teaching Areas

  • L1 Foundations of Physics: Classical Mechanics I(10 hours/year.)

Publications

Journal Article

Conference Paper

  • Aksit, Kaan, Ng, Ren, Banks, Martin S., Love, Gordon D., Lopes, Ward, Kim, Jonghyun, Spjut, Josef, Patney, Anjul, Shirley, Peter, Luebke, David, Cholewiak, Steven A. & Srinivasan, Pratul (2017), Varifocal virtuality: a novel optical layout for near-eye displayACM SIGGRAPH 2017 Emerging Technologies on – SIGGRAPH ’17. Los Angeles, ACM, New York, 25.

Media Contacts

Available for media contact about:

  • Visualisation / 3D displays:
  • Advanced Instrumentation:
  • Vision / eye movement:

Supervises

Dr George Alex Koulieris

Assistant Professor
Assistant Professor in the Department of Computer Science
Room number: E111

(email at georgios.a.koulieris@durham.ac.uk)

Biography

I am an Assistant Professor in the Innovative Computing Group at the Department of Computer Science at Durham University. My primary research interests lie in the field of computer graphics, in particular applied visual perception to rendering and display hardware, with a strong focus on near-eye displays and virtual reality.

Before joining Durham in 2018, I was a post-doctoral researcher at Inria, France, team GraphDeco, and visiting scholar at UC Berkeley Vision Science, USA, working on near-eye, stereo displays.

Google Scholar Profile

Research Groups

  • Innovative Computing

Research Interests

  • Computer Graphics
  • Displays
  • Virtual Reality
  • Visual Perception

Selected Publications

Journal Article

Conference Paper

Doctoral Thesis

  • Koulieris, George Alex (2015). Context-aware Gaze Prediction applied to Game Level Design, Level-of-Detail and Stereo Manipulation. Technical University of Crete, Department of Electronic and Computer Enginneering. PhD.

Show all publications

Dr Lawrence Mitchell

Assistant Professor
Assistant Professor in the Department of Computer Science

(email at lawrence.mitchell@durham.ac.uk)

Biography

I am an Assistant Professor in the Department of Computer Science at Durham University. My research is in high performance computing and computational mathematics. Much of my recent focus has been in the development of compilers and software abstractions for the development of numerical models implemented using the finite element method. This research is concretely realised in the open source Firedrake project. I am particularly interested in preconditioning techniques for challenging problems in computational and atmospheric fluid dynamics.

Research interests

The focus of my work is how to address the increasingly sophisticated needs of computational science practitioners by changing the way we think about numerical models. I develop computational mathematical abstractions that enable the automation of efficient implementations of complex, multiscale, numerical methods on modern supercomputers.

Compilers for numerical software

In the Firedrake project, I work on capturing the mathematical abstractions in numerical models, blending symbolic reasoning and numerical computation. This enables an approach to numerical software development that leverages symbolic information to synthesise high performance, parallel implementations of mathematical algorithms. This is possible through careful design of software abstractions, and development of domain-specific optimising compilers.

Fast solvers for geophysical flows

A large part of sophisticated numerical model development is in the design of robust linear and nonlinear solvers for the equations of interest. I have a particular interest in fast solvers for structure-preserving discretisations in atmospheric fluid dynamics. With Eike Müller, I developed a mesh-, and parameter- independent multigrid scheme for the mixed finite element discretisation proposed for the UK “GungHo” Dynamical Core project. We are presently working on multilevel schemes for the hybridised formulation of these equations, which should permit faster solvers. This latter work is in close collaboration with Colin Cotter, and Thomas Gibson.

Research Groups

  • Innovative Computing

Selected Publications

Journal Article

Working Paper

Show all publications

Dr Ioannis Ivrissimtzis

Associate Professor

Assistant Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 44288

(email at ioannis.ivrissimtzis@durham.ac.uk)

I am an Assistant Professor in the Department of Computer Science of Durham University. I have a degree in mathematics from the University of Thessaloniki, Greece and a PhD in mathematics from the University of Southampton. Before joining Durham University I was a lecturer at the Department of Creative Computing in Coventry University. Before that, I was a researcher at the Department of Computer Graphics of the
Max-Planck Institut fuer Informatik, in Saarbruecken, Germany and before that, a Research Associate at the Computer Laboratory of Cambridge University.

My research interests are in the area of computer graphics. In particular, I work on subdivision surfaces, polygonal mesh encoding and the application of statistical learning methods in surface reconstruction from scan data.

Indicators of Esteem

Research Groups

  • Algorithms and Complexity
  • Innovative Computing

Selected Publications

Show all publications

Supervises

Dr Chris Willcocks

Assistant Professor
Assistant Professor in the Department of Computer Science
Room number: E111a

(email at christopher.g.willcocks@durham.ac.uk)

Biography

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.

Cybersecurity Teaching

Slides for cybersecurity and other material will appear on my webite as they’re released.

Personal Webpage

Blog & Articles

Company Webpage

Intogral Limited

GitHub

Link to Profile

Industry Collaboration

  • 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)
  • Dyson
  • Unilever

Grants/Awards

  • 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

Research Interests

  • Unsupervised Learning
  • Medical Image Computing
  • Level Set Methods
  • Big Data Analytics
  • Image Processing
  • Cybersecurity
  • GPGPU Computing
  • Data Visualization
  • Segmentation & Skeletonization
  • Optimization
  • Deep Learning

Journals

  • 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.

Supervises

Dr Yang Long

Assistant Professor
Assistant Professor in the Department of Computer Science
Telephone: +44 (0) 191 33 48133
Room number: E112

Contact Dr Yang Long (email at yang.long@durham.ac.uk)

Biography

Yang Long is an Assistant Professor in the Department of Computer Science, Durham University. He is also an MRC Innovation Fellow aiming to design scalable AI solutions for large-scale healthcare applications. His research background is in the highly interdisciplinary field of Computer Vision and Machine Learning. While he is passionate about unveiling the black-box of AI brain and transferring the knowledge to seek Scalable, Interactable, Interpretable, and sustainable solutions for other disciplinary researches, e.g. physical activity, mental health, design, education, security, and geoengineering. He has authored/co-authored 20+ top-tier papers in refereed journals/conferences such as IEEE TPAMI, TIP, CVPR, AAAI, and ACM MM, and holds a patent and a Chinese National Grant.

Selected Publications

  • 1: Long, Yang, Liu, Li, Shen, Fumin, Shao, Ling & Li, Xuelong (2018). Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion RegularisationEEE Transactions on Pattern Analysis and Machine Intelligence 40(10): 2498-2512.
  • 2: Gao, Yan, Long, Yang, Guan, Yu, Basu, Anna, Baggaley, Jessica & Ploetz, Thomas (2019). Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable AccelerometersProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3(1): 12.
  • 3: Zhou, Lingli, Zhang, Haofeng, Long, Yang, Shao, Ling & Yang, Jingyu (2019). Depth Embedded Recurrent Predictive Parsing Network for Video ScenesIEEE Transactions on Intelligent Transportation Systems 1.
  • 4: Huang, Yan, Long, Yang & Wang, Liang (2019), Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding, AAAI.
  • 5: Zhang, Haofeng, Long, Yang, Guan, Yu & Shao, Ling (2019). Triple Verification Network for Generalized Zero-Shot LearningIEEE Transactions on Image Processing 28(1): 506-517.
  • 6: Cai, Ziyun, Long, Yang & Shao, Ling (2018). Adaptive RGB Image Recognition by Visual-Depth EmbeddingIEEE Transactions on Image Processing 27(5): 2471-2483.
  • 7: Long, Yang, Liu, Li, Shen, Yuming & Shao, Ling (2018), Towards affordable semantic searching: Zero-shot retrieval via dominant attributes, Thirty-Second AAAI Conference on Artificial Intelligence.
  • Zhang, Haofeng, Long, Yang, Liu, Li & Shao, Ling (2019). Adversarial unseen visual feature synthesis for Zero-shot Learning. NEUROCOMPUTING 329: 12-20.
  • Guan, Congying, Qin, Shengfeng & Long, Yang (2019). Apparel-based deep learning system design for apparel style recommendation. INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY 31(3): 376-389.
  • Zhang, Haofeng, Long, Yang, Yang, Wankou & Shao, Ling (2019). Dual-verification network for zero-shot learning. INFORMATION SCIENCES 470: 43-57.
  • Long, Yang, Guan, Yu & Shao, Ling (2019). Generic compact representation through visual-semantic ambiguity removal. PATTERN RECOGNITION LETTERS 117: 186-192.
  • Zhang, Haofeng, Long, Yang & Shao, Ling (2019). Zero-shot Hashing with orthogonal projection for image retrieval. PATTERN RECOGNITION LETTERS 117: 201-209.
  • Zhang, Haofeng, Long, Yang & Zhao, Chunxia (2018). Attribute relaxation from class level to instance level for zero-shot learning. ELECTRONICS LETTERS 54(20): 1170-1171.
  • Long, Yang, Zhu, Fan, Shao, Ling & Han, Junwei (2018). Face recognition with a small occluded training set using spatial and statistical pooling. INFORMATION SCIENCES 430: 634-644.
  • Long, Yang, Guan, Yu & Shao, Ling (2018). Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters 186: 192.
  • Zhang, Haofeng, Liu, Li, Long, Yang & Shao, Ling (2018). Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval. IEEE TRANSACTIONS ON IMAGE PROCESSING 27(4): 1626-1638.
  • Zhang, Haofeng, Long, Yang & Shao, Ling (2018). Zero-shot leaning and hashing with binary visual similes. Multimedia Tools and Applications 1-19.
  • Long, Yang, Zhu, Fan & Shao, Ling (2016). Recognising occluded multi-view actions using local nearest neighbour embedding. Computer Vision and Image Understanding 144: 36-45.
  • Mao, Huaqi, Zhang, Haofeng, Long, Yang, Wang, Shidong & Yang, Longzhi (2019), A General Transductive Regularizer for Zero-Shot Learning, BMVC.
  • Wang, Junyan, Hu, Bingzhang, Long, Yang & Guan, Yu (2019), Order Matters: Shuffling Sequence Generation for Video Prediction, BMVC.
  • Cai, Ziyuni, Long, Yang & Shao, Ling (2018), Adaptive Visual-Depth Fusion Transfer, ACCV.
  • Guan, Congying, Qin, Shengfeng, Ling, Wessie & Long, Yang (2018), Enhancing apparel data based on fashion theory for developing a novel apparel style recommendation system, World Conference on Information Systems and Technologies Springer, Cham. 31-40.
  • Long, Yang, Tan, Yao, Organisciak, Daniel, Yang, Longzhi & Shao, Ling (2018), Towards light-weight annotations: Fuzzy interpolative reasoning for zero-shot image classification, BMVC.
  • Zhu, Yi, Long, Yang, Guan, Yu, Newsam, Shawn & Shao, Ling (2018), Towards Universal Representation for Unseen Action Recognition, IEEE Conference on Computer Vision and Pattern Recognition 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) IEEE; CVF; IEEE Comp Soc. 345 E 47TH ST, NEW YORK, NY 10017 USA, IEEE, 9436-9445.
  • Long, Yang & Shao, Ling (2017), Describing unseen classes by exemplars: Zero-shot learning using grouped simile ensemble, 2017 IEEE winter conference on applications of computer vision (WACV) IEEE. 907-915.
  • Long, Yang, Liu, Li, Shao, Ling, Shen, Fumin, Ding, Guiguang & Han, Jungong (2017), From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis, Computer Vision and Pattern Recognition IEEE.
  • Long, Yang & Shao, Ling (2017), Learning to recognise unseen classes by a few similes, Proceedings of the 25th ACM international conference on Multimedia ACM. 636-644.
  • Long, Yang, Liu, Li & Shao, Ling (2017), Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) IEEE. 944-952.
  • Long, Yang, Liu, Li & Shao, Ling (2016), Attribute embedding with visual-semantic ambiguity removal for zero-shot learning, BMVC.
  • Long, Yang (2017). Zero-shot Image Classification. University of Sheffield. PhD.

Professor Sue Black

Professor

Professor in the Department of Computer Science

Biography

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.

Research Groups

  • Innovative Computing

Research Interests

  • Women in tech
  • Twitter
  • Social media
  • Software engineering

Selected Publications

Journal Article

  • 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

Conference Paper

  • 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

Dr Craig Stewart

Assistant Professor
Assistant Professor (Teaching) in the Department of Computer Science
Telephone: +44 (0) 191 33 40418
Room number: E107

(email at craig.d.stewart@durham.ac.uk)

Biography

Dr Stewart has worked in the areas of HCI, Serious Games, Personalised Systems, Multimedia and Cultural Studies in research and education for over 25 years. Dr Stewart’s doctoral research (entitled A Cultural Education Model: Design and Implementation of Adaptive Multimedia Interfaces in eLearning) consists of examining the effect that technology enahnced learning is having on cultural education and how HCI influences this.

Research Interests

  • Adaptive Systems
  • HCI
  • User modelling
  • Personalised Systems
  • Elearning
  • Cultural Studies

Teaching Groups

  • EDIC

Teaching Areas

  • Software Engineering (COMP2252)

Selected Publications

Journal Article

  • Lameras, Petros, Arnab, Sylvester, Dunwell, Ian, Stewart, Craig, Clarke, Samantha & Petridis, Panagiotis (2017). Essential features of serious games design in higher education: Linking learning attributes to game mechanics. British journal of educational technology 48(4): 972-994.
  • 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-learningInformation & Management 51(6): 819-832.
  • Stewart, Craig (2008). Authoring \& Culture in Online Education. J. UCS 14(17): 2877-2896.
  • Meccawy, Maram, Stewart, Craig D & Ashman, Helen (2007). Adaptive educational hypermedia interoperability and content creation with a web service-based architecture. International Journal of Learning Technology 3(3): 269-285.
  • Stewart, Craig, Cristea, Alexandra I, Brailsford, Tim & Ashman, Helen (2005). ‘Authoring once, delivering many’: creating reusable adaptive courseware.
  • Brown, Elizabeth, Cristea, Alexandra, Stewart, Craig & Brailsford, Tim (2005). Patterns in authoring of adaptive educational hypermedia: A taxonomy of learning styles. Journal of Educational Technology \& Society 8(3): 77-90.

Chapter in book

Conference Paper

  • Alamri, Ahmed, Rusby, Harry, Cristea, Alexandra I, Kayama, Mizue, Khan, Javed, Shi, Lei & Stewart, Craig (2018), An Intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System, Proceedings of the 2018 The 3rd International Conference on Information and Education Innovations ACM. 57-61.
  • Cristea, Alexandra I., Alamri, AhmedAlshehri, Mohammad, Kayama, Mizue, Foss, Jonathan, Shi, Lei & Stewart, Craig D. (2018), Can Learner Characteristics Predict Their Behaviour on MOOCs?10th International Conference on Education Technology and Computers – ICETC ’18. Tokyo, ACM, New York, 119-125.
  • Cristea, Alexandra I., Alamri, Ahmed, Kayama, Mizue, Stewart, Craig, Alshehri, Mohammad & Shi, Lei (2018), Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses, in Andersson, B., Johansson, B., Carlsson, S., Barry, C., Lang, M., Linger, H. & Schneider, C. eds, 27th International Conference on Information Systems Development (ISD2018). Lund, Sweden, Association for Information Systems.
  • Cristea, Alexandra I., Alamri, Ahmed, Kayama, Mizue, Stewart, Craig, Alshehri, Mohammad & Shi, Lei (2018), How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers, in Andersson, B., Johansson, B., Carlsson, S., Barry, C., Lang, M., Linger, H. & Schneider, C. eds, 27th International Conference on Information Systems Development (ISD2018). Lund, Sweden, Association for Information Systems.
  • Alshehri,Mohammad, Foss,Jonathan, Cristea,Alexandra I., Kayama,Mizue, Shi,LeiAlamri,Ahmed & Tsakalidis,Adam (2018), On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs, ACM International Conference Proceedings Series (ICPS) 3rd International Conference on Information and Education Innovations (ICIEI’18). London, Association for Computing Machinery, New York, NY, USA, 73-77.
  • John, Santhosh, Shah, Nazaraf & Stewart, Craig (2018), Towards a Software Centric Approach for Ontology Development: Novel Methodology and its Application, 2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) IEEE. 139-146.
  • Thong, Li Ping, Stewart, Craig, Arnab, Sylvester & Lameras, Petros (2016), Virtual Designer: Digital Role-Playing Game for Knowledge Transferal in Design Education, European Conference on Games Based Learning Academic Conferences International Limited. 862.
  • Dunwell, Ian, de Freitas, Sara, Petridis, Panagiotis, Hendrix, Maurice, Arnab, Sylvester, Lameras, Petros & Stewart, Craig (2014), A game-based learning approach to road safety: the code of everand, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems ACM. 3389-3398.
  • Gallear, Wayne, Lameras, Petros & Stewart, Craig (2014), Serendipitous learning \& serious games: A Pilot Study, 2014 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL2014) IEEE. 247-251.
  • Lameras, Petros, Petridis, Panagiotis, Dunwell, Ian, Hendrix, Maurice, Arnab, Sylvester, de Freitas, Sara & Stewart, Craig (2013), A game-based approach for raising awareness on sustainability issues in public spaces, The Spring Servitization Conference: Servitization in the multi-organisation enterprise. 20-21.
  • Scotton, Joshua, Stewart, Craig & Cristea, Alexandra I (2011), ADE: The Adaptive Display Environment for Adaptive Hypermedia, Proceedings of the ACM Hypertext 2011 International Conference.
  • Stewart, Craig, Brailsford, Tim, Chandramouli, Krishna & Cristea, Alexandra I (2010), The CAE-L cultural framework: Definition, instances and web service, 2010 10th IEEE International Conference on Advanced Learning Technologies IEEE. 604-606.
  • Chandramouli, Krishna, Stewart, Craig, Brailsford, Tim & Izquierdo, Ebroul (2008), CAE-L: An ontology modelling cultural behaviour in adaptive education, 2008 Third International Workshop on Semantic Media Adaptation and Personalization IEEE. 183-188.
  • Stewart, Craig, Chandramouli, Krishna, Cristea, Alexandra, Brailsford, Tim & Izquierdo, Ebroul (2008), Cultural artefacts in education: Analysis, ontologies and implementation, 52008 International Conference on Computer Science and Software Engineering IEEE. 706-709.
  • Stewart, Craig (2007), The Role of Culture in Online Education: as an input for the authoring process, User Modelling (UM) conference, A3H workshop.
  • Brown, Elizabeth, Stewart, Craig & Brailsford, Tim (2006), Adapting for visual and verbal learning styles in AEH, Sixth IEEE International Conference on Advanced Learning Technologies (ICALT’06) IEEE. 1145-1146.
  • Stewart, Craig, Cristea, Alexandra, Celik, Ilknur & Ashman, Helen (2006), Interoperability between AEH user models, Proceedings of the joint international workshop on Adaptivity, personalization \& the semantic web ACM. 21-30.
  • Moore, Adam, Brailsford, Timothy J & Stewart, Craig D (2001), Personally tailored teaching in WHURLE using conditional transclusion, Proceedings of the 12th ACM conference on Hypertext and Hypermedia ACM. 163-164.

Doctoral Thesis

  • Stewart, Craig (2012). A cultural education model: design and implementation of adaptive multimedia interfaces in eLearning. University of Nottingham. PhD.

Show all publications

Media Contacts

Available for media contact about:

  • Business: Education and awareness: Personalised, digital systems
  • Computer Science: Personalised, digital systems
  • Computer Science: Information systems and Cultural studies
  • Identity, ethnicity and culture: Information systems and Cultural studies
  • Science: Education, industry & the community: Information systems and Cultural studies

Dr Steven Bradley

Associate Professor (Teaching)

Associate Professor (Teaching) in the Department of Computer Science

Telephone: +44 (0) 191 33 41754

(email at s.p.bradley@durham.ac.uk)

Biography

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

Research Groups

  • Innovative Computing

Research Projects

Department of Sociology

  • Children’s hospice service data mapping project 2011/12
  • Mapping Unit

Research Interests

  • Computer Science education
  • Citizen science
  • Knowledge representation and student learning
  • Web-based data collection
  • Real-time systems
  • Software engineering

Selected Publications

Journal Article

Conference Paper

  • 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.

Show all publications

Related Links

Selected Grants

  • 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 Lei Shi

Assistant Professor
Assistant Professor in the Department of Computer Science
Telephone: +44 (0) 191 33 48131
Room number: E231

Contact Dr Lei Shi

Biography

I am an Assistant Professor in the Innovative Computing Group. I hold a PhD in Computer Science from the University of Warwick and an MSc in Digital Art and Design from Zhejiang University. Before joining Durham Computer Science, I was a Research Fellow at the University of Warwick, and then a Lecturer at the University of Liverpool.

My research lies at the intersection of Human-Centred Computing and Artificial Intelligence. I investigate both theoretical aspects of Human-AI interaction and its practical applications in authentic real-world settings. I am particularly interested in how humans perceive, interact, collaborate and co-create with AI, especially in the fields of education, healthcare and well-being, and social innovation.

I have worked in the domain of Intelligent Tutoring Systems, where I implemented social interactions, open user modelling and gamification based on the theoretical underpinning of Social Constructivism, Self-Determination Theory, and Flow Theory, in order to improve learning engagement, efficiency and effectiveness. I have worked on Digital Crowdsourcing to improve Situated Engagement in the co-design of built healthcare and well-being environments. I have been working on Learning Analytics, where I use statistical modelling and machine learning to analyse massive and heterogeneous data to cluster learners, model behavioural patterns and predict learning outcomes, aiming at understanding and supporting learners in open-scale courses such as MOOCs (Massive Open Online Courses). I have been working on Intelligent Systems to predict surgical outcomes, which combines demographic, medical and psychological predictors with psycho-physiological markers of pain chronicity, to improve the success rate of spinal surgery.

Research Interests

  • Intelligent Tutoring Systems
  • Behavioural Analytics
  • Open User Modelling
  • Gamification
  • Social Innovation
  • Applied AI
  • Experiential AI
  • Transparent AI
  • Human-AI Co-creation

Personal web page

Professor David Budgen

Professor

Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 41724
Telephone: +44 (0) 191 33 41724

(email at david.budgen@durham.ac.uk)

Indicators of Esteem

  • 2010: Invited Keynote Presentation: ECOOP 2010: Presented an invited keynote talk on the theme “From Advocacy to Evidence: A Discipline in Transition” at ECOOP 2010 (European Conference on Object Oriented Programming), Maribor, Slovenia, June 2010.
  • 2010: Invited Participant: SPSD Workshop: I was an invited participant at the workshop on “Studying Professional Software Design” (SPSD), sponsored by the National Science Foundation (NSF) and held at the University of California, Irvine, in February 2010
  • 2006: Conference Keynote: I was a keynote speaker at the IEEE-sponsored 19th Conference on Software Engineering Education and Training, Oahu, Hawaii, 2006.
  • 2004: IEEE-CS/ACM Working Group: I represented the British Computer Society as a member of the IEEE-CS/ACM working group that developed the SE2004 curriculum guidelines for teaching undergraduate software engineering programmes. Published by IEEE Computer Society Press as “Software Engineering 2004: Curriculum Guidelines for Undergraduate Degree Programs in Software Engineering”
  • 1997: EPSRC College: I have been a member of the EPSRC College since its inception in 1997, have reviewed extensively and have taken part in a number of award panels.

Research Groups

  • Innovative Computing

Selected Publications

Show all publications

Supervises

Dr Frederick Li

Assistant Professor

Assistant Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 44299

(email at frederick.li@durham.ac.uk)

Biography

Personal webpage

Frederick Li received both a Bachelor of Arts (Honors) in Computing Studies and a Master of Philosophy from The Hong Kong Polytechnic University in 1994 and 1998, respectively, and a Ph.D. degree in Computer Graphics from the City University of Hong Kong in 2001. He is currently a Lecturer at the University of Durham. Prior to the current appointment, he was an Assistant Professor at The Hong Kong Polytechnic University from 2003 to 2006. From 2001 to 2003, he was the project manger of a Hong Kong Government Innovation and Technology Fund (ITF) funded project.

Frederick Li serves as an Associate Editor of International Journal of Distance Education Technologies on Communications Technologies (Distributed and Collaborative Learning). He has served as the Guest Editor of two journal special issues of International Journal of Distance Education Technologies. In addition, he has also served in the committee of a number of conferences, including ACM VRST 2004 – 2008CASA 2005ICWL 2005 – 2008. He serves as a Program Co-chair of ICWL 2007ICWL 2008IDET 2008 and IDET 2009. He also serves as a Workshop Co-chair of ICWL 2009 and U-Media 2009.

Research Groups

  • Innovative Computing

Indicators of Esteem

  • Conference Organization:
    • Publicity Co-Chair, ACM MM MTDL ‘2010
    • Publicity Co-Chair, IEEE U-Media ‘2010
    • Workshop Co-Chair, ICWL ‘2009
    • Workshop Co-Chair, IEEE JCPC ‘2009
    • Program Co-Chair, IDET ‘2008, ‘2009
    • Program Co-Chair, IDET ‘2007, ‘2008
  • Journal Editorialships:
    • Associate Editor (Communications Technologies), International Journal of Distance Education Technologies (JDET), (since 2007)
    • Editorial Review Board Member, International Journal of Cyber Ethics in Education (IJCEE), (since 2009)

Research Groups

  • Innovative Computing

Research Interests

  • Computer Graphics
  • Distributed Virtual Environment
  • Multimedia Systems
  • Surface Modeling
  • Virtual Reality

Publications

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