Start Dates: October, January, April and July
MSc by Research
One year full-time
Two years part-time
Master of Philosophy (MPhil)
One year full-time
Two years part-time
Doctor of Philosophy (PhD)
Three years full-time
Five years part-time
Three years full-time
Distance Learning PhD
Three years full time
Led by Professor Tim Ritchings, this research involves the development and evaluation of novel Intelligent Systems for digital signals, images and videos using Pattern Recognition and AI techniques to help in their interpretation and understanding of the data. Areas of application include biomedical applications, augmented reality and mobile applications.
This research area, led by Dr Apostolos Antonacopoulos focuses on the extraction of text from scanned documents. Innovative approaches are sought to improve all steps of the digitization workflow resulting in systems deployed in the real-world. Major collaborations with content holding institutions such as the British Library and commercial organisations such as Google and ABBYY ensure that problems are topical and solutions have significant impact.
Led by Professor Farid Meziane, research in this area is looking at developing models and methods for information extraction and retrieval, Natural language processing including Arabic, the use of ontologies for document classification and extraction, data intensive computing and business intelligence. Current research involves the development of models for data mining in the cloud and the development of data mining techniques for large data sets.
This research area, led by Professor Sunil Vadera is developing new cost-sensitive data mining methods. It aims to develop new approaches that take account of the cost of misclassifying examples and the cost of acquiring the information. Such cost-sensitive algorithms have potential for application in medical diagnosis, credit scoring, and energy minimization. Examples of research include projects with British Gas to apply data mining to SMART meters data to understand energy consumption behaviour and an FP7 project called SEEDS: Self-Learning Energy Efficient BuilDings and open Spaces.
This research area, led by Dr Chris Bryant, focuses on the development and application of machine learning algorithms. Areas of machine learning of interest include rule induction, relational data mining and inductive logic programming. The main focus of the applications are contemporary, challenging problems in molecular biology.
Led by Dr Saraee Mohamed, research in this area promotes the paradigm shift of Data Mining from data-centered interesting pattern mining to domain-driven actionable knowledge discovery. Mohamed’s research involves enhancing the DM system to enable them to Semantic Web applications. This showcase suggests a methodology for building Semantic Web Mining systems.
This research area is lead by Professor Terrence Fernando. This research focus on developing systems and prototypes for distributed organisations, focusing on sectors such as aerospace, automotive, building construction and urban planning
Led by Dr Adil Al-Yasiri, this research involves the development and evaluation of architectures, approaches and methodologies for developing high performance software systems. Specific areas of applications are agile methods, distributed architectures for the cloud, smart environments and ambient intelligence.
This research area, led by Dr John Haggerty, focuses on the securing of computer systems against attacks and the subsequent digital investigations should attacks be detected. Areas of interest include network security in emerging environments, intrusion detection, mobile security and new techniques for digital investigations. Current research involves the detection and response to Denial of Service attacks in MANETs and large data set visual analytics in digital forensics investigations.
1st class or upper second class undergraduate degree in a computer Science or Related discipline. For PhD degrees, Masters degree is preferred but not essential.
We welcome applications from students who may not have formal/traditional entry criteria but who have relevant experience or the ability to pursue the course successfully
English requirement for non-UK/ EU students
The following qualifications are accepted as evidence of proficiency in English:
We offer four entry points – October, January, April and July. Applications can be submitted at any point within the year.
You should have a first degree that provides a foundation in the principles of computing and scientific practice. This could include a Computer Science degree but also Engineering and other applied science degrees with strong programming elements. Evidence of ability to study and critically appraise literature independently is essential.
As a student embarking on a postgraduate research degree you will be assigned a supervisory team, to help guide and mentor you throughout your time at the University. However, you are ultimately expected to take responsibility for managing your learning and will be expected to initiate discussions, ask for the help that you need and be proactive in your approach to study.
International Students are required by the Home Office and/or the Foreign & Commonwealth Office (FCO) to apply for an Academic Technology Approval Scheme (ATAS) Certificate before they begin studying their course. You may need to obtain an ATAS Certificate before you come to the UK in order for you to comply with Home Office regulations. Please refer to your offer conditions.
You can find out if your programme requires an ATAS by checking the FCO website at https://www.gov.uk/academic-technology-approval-scheme with your JACS code which will be on your offer letter should you choose to make an application. If you cannot find it please contact International Conversion team at email@example.com. If you have any queries relating directly to ATAS please contact the ATAS team on Salford-ATAS@salford.ac.uk.
You can apply for your ATAS Certificate via this link: https://www.atas.fco.gov.uk/
Our current students are carrying out research in a range of topics including:
Darah Aqel (PhD), Supervisor Prof Sunil Vadera
A Framework for Employee Appraisals based on Inductive Logic Programming & WEKA data mining algorithms
Susan Lomax (PhD), Supervisor Prof Sunil Vadera
Cost-sensitive decision tree learning
Khairi Alaswad (PhD), Supervisor Prof Sunil Vadera
framework for human behaviour and its relationship with energy consumption
Eman B.Nashnush (PhD), Supervisor Prof Sunil Vadera
Cost-sensitive Bayesian Network algorithm
Samar Shilbayeh (PhD), Supervisor Prof Sunil Vadera
A Cost Sensitive Meta- Learning framework
Jawad Sadek (PhD), Supervisor Prof Farid Meziane
Question Answering Systems in Arabic Using Rhetorical Structures,
Haya Alshahri (PhD), Supervisor Prof Farid Meziane
Electronic Commerce acceptance in Saudi Arabia, PhD
Edyaf, Waliad M. (PhD), Supervisor Prof Farid Meziane
Managing Change in IS Development, The Libyan case study.
Abdelhafid Boussouar(PhD), Supervisor Prof Farid Meziane
Data Mining Applications in the cloud
Osama Othman (PhD), Supervisor Dr Chris Bryant
Reduction Methods for Rule Induction
Azlan Mohamed(PhD), Supervisor Prof Tim Ritchings
Automated analysis and tracking of tendon excursion studies in dynamic ultra-sound imaging
Mohua Munshi (PhD), Supervisor Dr Mohamad Saraee
Study on the intersection of prognostic information on disease recurrences and the image analysis system for identification of potential threshold
Maher Turifi (PhD), Supervisor Dr Mohamad Saraee
This project aims at developing models and techniques to help with patterns formation from big data repository.
Aiman Mjara (PhD), Supervisor Dr Mohamad Saraee
This project investigate assess E-Learning approach in Higher Education with emphasis on Higher Education System in Libya
Amaryam Kausar (PhD), Supervisor Dr Adil Al-Yasiri
Agile Methodologies for Offshore Software Development.
Shaymaa Al-Shammari (PhD), Supervisor Dr Adil Al-Yasiri
Proactive Middleware for the Cloud.
Albandari Alsumayt (PhD), Supervisor Dr John Haggerty
Detection and response to Denial of Service attacks in MANETs.
All postgraduate research students are expected to attend the College’s research methods seminars during their first year of study, covering subjects such as conducting a literature review, methods of data collection, research governance and ethics, and analysis, presentation, interpretation and rigour in qualitative research.
In addition, the University offers all postgraduate research students an extensive range of free training activities to help develop your research and transferable skills. The Salford Postgraduate Research Training Programme (SPoRT) has been designed to equip researchers both for your university studies, and for your future careers whether in academia, elsewhere in the public sector, or in industry and the private sector.
As a postgraduate research student at the University of Salford, you are required to meet a number of milestones in order to re-register for each year of study. These ‘progression points’ are an important aid for both you and your supervisory team and it is essential that you complete them on time.
Learning Agreement: this is completed by you and your supervisor collaboratively in the first 3 months of your research programme. It encourages both of you to develop a thorough and consistent understanding of your individual and shared roles and responsibilities in your research partnership.
Annual Progress Report: this report is completed by your supervisor at the end of each year of study, and reports on your achievements in the past year, the likelihood that you will submit on time, confirmation of the Learning Agreement and relevant training undertaken.
Self Evaluation Report: this is completed by you at the end of each year of study. It asks you to comment on your academic progress, supervisory arrangements, research environment, research training, and relevant training undertaken.
Interim Assessment: this is an assessment of your progress by a panel. It takes place towards the end of your first year, and is designed to ensure you have reached a threshold of academic performance, by assessing your general progress. The assessment comprises a written report, presentation and oral examination by a Panel. You must successfully complete it in order to register for your second year.
Internal Evaluation: this will take place towards the end of the second year and successful completion is required in order to continue onto your third year of study. You will be expected to show strong progress in your PhD study reflected in the submission of a substantial piece of work, generally at least 4 chapters of your thesis.
The Informatics Research Centre is a research and consulting research group with a strong national and international reputation located within the school of computing, science and engineering at the University of Salford. Home to over twenty research staff, the centre is developing novel methods and systems for the analysis and recognition of images and other data, learning behaviours and causal models that have a wide range of potential applications including prediction of credit ratings, restoration of historical documents, medical diagnosis, programme ratings, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval, intelligent scheduling, user modelling, and as embedded self-learning components in intelligent agents. The Centre supports research in Software Engineering, Context aware software and data visualisation.
The underlying scientific and engineering expertise of the group is in areas such as cost-sensitive decision tree learning, association mining, Inductive logic programming, Bayesian Networks, semantic clustering and ontologies, fuzzy logic, text mining, information extraction, neural networks, image recognition and restoration, data visualisation, software engineering and context aware systems, information security and Forensic Computing.
Dr Adil Al-Yasiri
Adil’s research interests are in developing and applying software engineering methods and software architectures in pervasive computing environments. His research focus is on developing new techniques that seamless integration between services and users with such environments. This include (but not limited to) studying user behaviour in such environments using machine learning techniques, developing novel architectures and methods for building pervasive systems and defining new metrics for evaluating quality of experience for users. Application environments include ubiquitous computing, ambient intelligence, cloud computing and context aware systems.
Adil has published extensively in his area of research in a number of refereed journals and conferences and supervised a number of PhD students which resulted in 100% success rate. He also brings extensive international experience by working as a consultant for a number of clients world-wide. Adil’s full research profile is:
Dr Apostolos Antonacopoulos
Dr Antonacopoulos leads the Pattern Recognition and Image Analysis research Lab. He has worked and published extensively on various problems in Document Analysis and Understanding as well as on other applications of Pattern Recognition and Image Analysis. He has co-edited the first Special Issue on Historical Document Analysis as well as the first book on Web Document Analysis. He is a member of the Editorial Boards of the International Journal on Document Analysis and Recognition and of the Electronic Letters on Computer Vision and Image Analysis.
He is currently serving as the Chair of the IAPR Education Committee. In 2008-2010 he served as the 1st Vice President of the IAPR and prior to that he chaired or served as a member of a number of IAPR and other committees. He has given a number of invited talks and tutorials and is holding engagements as a technical advisor to libraries and archives, among which are the British Library and the Welcome Trust archives. He has significant experience in leading and participating in national, European and industry-sponsored projects. Current significant project involvement includes the €12M IMPACT EU-funded project and the €4M European Newspapers EU-Funded project. See http://www.primaresearch.org/people/aa for Apostolos’s complete research profile.
Dr Chris Bryant
Chris is interested in machine learning, especially inductive logic programming. His specific interests include automating some aspects of the scientific method, refining biological pathways and acquiring biological grammars. Chris was the Principal Investigator on the EPSRC project "Efficient Biological Grammar Acquisition" (GR/S68682, £110K). (http://www.cse.salford.ac.uk/profiles/bryant/interests.php).
He enjoys applying machine learning to contemporary, challenging problems in molecular biology. He has worked in the following areas previously. Predicting the coupling preference of GPCR proteins; Recognising human neuropeptide precursors; Predicting which of the upstream Open Reading Frames in S.cerevisiae regulate gene expression; Discovering how genes participate in the aromatic amino acid pathway of S.cerevisiae.
So far, 100% of the past doctoral students supervised by Chris have successfully graduated with a PhD and found employment. Chris has published extensively in refereed, learned journals and international refereed conferences. Chris has a track record of attracting research funding to support his doctoral students including an EST Marie Curie Fellowship (MEST-2-CT-2004-514169); travel grants awarded by the Scottish International Education Trust and The Society for the Study of Artificial Intelligence and Simulation of Behaviour; and an advanced course awarded by the European Coordinating Committee for Artificial Intelligence. SEEK Research Profile: http://www.seek.salford.ac.uk/profiles/CBRYANT.jsp
Dr John Haggerty
John’s main research interests include network security, computer forensics, signature matching and mobile computing. In addition to publishing in international academic journals, book chapters and conference proceedings in these areas, John holds three patents for new computer forensics approaches that have been developed from his research. These have received major investment from a university and commercial collaboration to develop the tools for market. He also acts as a reviewer to major computer security and digital forensics journals and is a member of a number of international conference programme committees in these areas. John is also currently working on an inter-disciplinary, collaborative project with the School of History, University of Nottingham, analysing 18th century British-Atlantic business networks using tools and techniques associated with digital forensics investigations. John’s SEEK research profile is at:
Professor Terrence Fernando
Terrence is the Director of the ThinkLab at the University of Salford. He has a broad background in conducting multi-disciplinary research programmes. During 2001 and 2004 he led a regional research centre on advanced virtual prototyping. This EPSRC/OST funded (£1.7m) project involved key research teams to develop visualisation and simulation technologies for product design. As part of the EU funded Future_Workspaces roadmap project and the MOSAIC project, Prof. Fernando brought together over 100 companies and research centres from areas such as aerospace, automotive and system architecture to define a 10 year European vision for future collaborative engineering workspaces. This work resulted in receiving 12MEuro from EU for a project called CoSpaces IP to implement an innovative collaborative technology platform for aerospace, automotive and construction industries, involving 22 European partners. He was also a member of the INTUITION Network of Excellence project (5MEuro) to develop coordinated research activities on VR. As a part of the EPSRC funded Vivacity project, he led the development of a collaborative urban planning environment in collaboration with Black Country Consortium and Ordnance Survey. This work is now being further developed to support regeneration projects within Salford, involving a range of stakeholders including City Council, Police and Environment Agency. Terrence research profile is: http://www.seek.salford.ac.uk/profiles/FERNANDO449.jsp
Professor Farid Meziane
Professor Farid Meziane is the Head of the Data Mining and Pattern Recognition Research Centre in the School of Computing, Science and Engineering. He holds was awarded a PhD from the University of Salford for his research on obtaining formal specifications from informal specifications, which was one of the first demonstrated uses of natural language processing in Software Engineering and one of the first proposals to extract and utilize deep knowledge from text. Farid’s expertise is in the area of data and knowledge engineering and his research include the development of ontologies for information extraction, business intelligence and data intensive computing. His work on the Arabic Language include the development of an ontology based on verb derivation, a named entity extraction system and the use of rhetorical structure theory for QA systems. Farid was the investigator or co-investigator in the SEED, Funsiec and VOSTER EU funded projects. Farid has successfully supervised 5 PhD students to completion and is in the editorial board of international journal and member of the programme committee of international conferences
Farid is the Chair of the 18th International Conference on application of natural language to information systems. Farid full research profile is: http://www.seek.salford.ac.uk/profiles/MEZIANE727.jsp
Dr Mohamed Saraee
Dr Saraee research interests lie in advanced database systems, data and text mining, bioinformatics and semantic web. His research goal is to develop data and text mining applications across diverse data sources, e.g., medical and biomedical data, scientific documents, software repository data, business process models, banking and finance, retail, telecommunication and manufacturing. He has published over 105 papers in (ISI / International) Journals and (IEEE / International) conferences. In particular his research is related to Mining Advanced Data Types including Temporal, Spatial and multimedia. By publishing the first paper in 1995, he led the research in the field of Temporal Data Mining. He has been involved for the last 10 years is Medical Data Mining (MDM). His interest in this field was initiated from the research collaboration with the Medical School, Manchester University, which resulted in many publications including British Medical Journal (BMJ) and Journal of Artificial Intelligence in Medicine. His other research area with great impact is Bioinformatics. He has published extensively in this area including BMC Medical Genomics and the International Journal of Business Intelligence and Data Mining.
Mohamed’s full research profile is: http://www.seek.salford.ac.uk/profiles/SARAEE871.jsp
Professor Tim Ritchings
Tim is interested in the development and evaluation of novel Intelligent Systems that involve the digital signals and images, using Pattern Recognition and AI techniques to help in their interpretation and understanding of the data. His focus has been on effective and reliable systems that address significant real-world issues in both medicine and industry. In addition to traditional signal and image analysis techniques, he has expertise with using Knowledge/Rule based systems, fuzzy reasoning, Artificial Neural Networks, and Genetic Programming in the context of signals and images techniques. He also has expertise in visualisation techniques to support the signal and image analysis, and development of Augmented Reality applications using hand-held devices.
Tim has supervised over 20 PhD students to successful completion, and has over 100 publications in Journals and International refereed Conferences. He received EPSRC funding (£120K) for his project on Automated voice quality monitoring for differentiating cancer therapy, recovery patterns, and KTP funding (£170K, with Dr Antonacopoulos) for Automated analysis and object tracking in video data from car-park security cameras. Tim’s full research profile is: http://www.seek.salford.ac.uk/profiles/RITCHINGS845.jsp
Professor Sunil Vadera
Sunil’s main interests are developing and applying data mining methods such as decision tree learning, Bayesian networks, self-organising maps, and neural networks. His research has included work on machine learning for sensor validation with the Mexican Instituto de Electricas, a British Gas funded project applying data mining on SMART meters data, the development a system known as Dust-Expert that advises on the relief venting of explosions in chemical processes for the Health and Safety Executive in the UK and research on data mining for credit rating of sub-prime loans for East Lancashire Moneyline (IPS) Ltd . He is Principal Investigator of an FP7 project SEEDS that aims to develop “Self learning Energy Efficient builDings and open Spaces”. He was chair of the UK BCS Knowledge Discovery and Data Mining Symposium held in Salford in 2009, General Chair of the IFIP conference on Intelligent Information Processing in 2010 and his research has been published in some of the leading outlets, including the Computer Journal, ACM Transactions on Knowledge Discovery from Data, Expert Systems Journal, Foundations of Science, and IEEE Transactions of Power Systems. Sunil’s research profile is: http://www.seek.salford.ac.uk/profiles/VADERA960.jsp
Professor Yau Jim Yip
Professor Jim Yip research expertise is in the areas of Knowledge Based Systems (KBS) and Artificial Intelligence (AI). Funded projects include applications in chemical and process industry, textile, manufacturing and construction industry, geographical applications and environmental management. Jim is the UK Co-Director of the Web Intelligence Consortium.
He is the principal/joint grant holder of external funded research projects worth £1.3m with 95 publications. Jim has supervised 34 research fellows and students with 12 PhD completions. He is a member of the EPSRC Peer Review College and a Leverhulme Trust grant proposal reviewer and was an EU registered expert and Panel Judge on Esprit/Framework research proposals. Jim is in the editorial board of many international journals and member of the programme committee of international conferences.
Students leaving the School with a postgraduate research degree are taking various positions in academia, research centres and industry. Previous students have taken academic roles in universities around the world including Malaysia, the Middle East, North Africa and South America.
Dr Thierry Mamer (Supervisor: Dr Chris Bryant)
Current Occupation: Researcher, British Telecom, Ipswich.
Dr Jia Wu (Supervisor: Prof. Sunil Vadera)
Current Occupation: Research Assistant, University of Salford
Dr Maryam Rahnemoonfar (Supervisor: Dr A. Antonacopoulos)
Current Occupation: Assistant Professor, Isfahan University, Iran.
Dr Ahmed Khadragi (Supervisor: Prof Tim Ritchings)
Current Occupation: Assistant Professor, Head of Computer Engineering Department, Arab Academy for Science &Technology, Syria Branch
Dr Khaled Eskaf, Dr Marwa El-Shenawy, Dr Rania Kadry, Supervisor Prof Tim Ritchings
Current Occupations: Assistant Professor, Computer Engineering Department, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt
Dr Giap Weng Ng (Supervisor: Prof Tim Ritchings)
Current Occupation: Director of the Centre of Excellence for Semantic Technology and Augmented Reality, UNIMAS
Dr John Sage (Supervisor:Prof Tim Ritchings)
Current Occupation: Head of Radiotherapy Physics, University Hospitals of Leicester NHS .
Dr Ihab El-Aff (Supervisor: Prof Tim Ritchings)
Current Occupation: Assistant Professor, Computer Engineering Department, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt
Dr Edwin Mit (Supervisor: Prof Farid Meziane)
Current Occupation:Deputy Dean Postgraduate and Research, Faculty of Computer Science and Information Technology, University Malaysia Sarawak, Malaysia. (http://www.fcsit.unimas.my/index.php/edwin-mit)
Dr. Mohd Khairudin Kasiran (Supervisor: Prof Farid Meziane)
Current Occupation: Head of Information Systems Department, University Utara Malaysia. (http://soc.uum.edu.my/index.php/en/school/executives)
Wan Nurhayati Wan Ab. Rahman (Supervisor: Prof Farid Meziane)
Current Occupation: Senior Lecturer, Faculty of Computer Science and Information Technology, University Putra Malaysia, Malaysia (http://profile.upm.edu.my/wnurhayati/en/profail.html)
Dr Angham Sabagh (Supervisor: Dr Adil Al-Yasiri)
Current Occupation: Academic Support Tutor, School of Engineering, Manchester Metropolitan University, Manchester, UK.
Dr Samer Ayyat (Supervisor: Dr Adil Al-Yasiri)Current Occupation: Software Quality and Integration Analyst, Autocab International, GPC Computer Software Ltd, Cheshire, UK.
The Informatics Research Centre has strong links with industry and public sector organizations and a strong funding record. Research examples include collaboration with Google on training a character recognition system used in Google Books and an ongoing collaboration with IBM Research.
Examples of current projects utilising the developed novel scientific methods include the EU funded projects. The IMPACT projects that focuses on digital restoration of historical documents and the SEED project that develops intelligent models of the optimisation of energy consumption in intelligent buildings. Other projects include a British Gas funded project for the reduction of energy consumption and CO2 emission using data collected from their SMART Meters, application of machine learning for market segmentation, development of a model capable of learning the behaviour of a Gas Turbine Power plant, semantic text mining in Arabic, evaluation of trust worthiness of web sites, application of inductive logic programming for discovering the mechanisms that regulate gene expressions and use of machine learning for credit scoring for the sub-prime market. The Centre generated over £ 1.5 million over the last 4 years.
In the public sector we work closely with libraries (British Library and most major national and notable libraries in Europe) and a number of hospitals.
For its research on energy use optimisation, the Informatics Research Centre uses the energy house, the world’s first house reconstructed in a controlled environment.
The Energy House is a typical Salford 1919 terraced house that has been reconstructed in a fully environmentally controllable chamber, in which climatic conditions can be maintained, varied, repeated and patterns monitored.
Unlike test houses built outdoors, conditions in the Energy House can be replicated time and time again whatever the weather is like outdoors.
The building currently installed represents 21% of UK housing stock and was rebuilt using the traditional methods of the time, including lime mortar, and lathe and plaster ceilings. The house is classed as a hard to treat property in terms of energy efficiency due to the lack of cavity walls.
Salford Energy House provides a unique testing and development facility in which leading researchers can work collaboratively with industry to develop and test new technology and solutions to improve the energy efficiency of existing projects and processes.
For more information please see the Salford Energy House website.