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causal models that have a wide range of potential applications including prediction of credit ratings, restoration of historical documents, medical diagnosis, programme ratings, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval, intelligent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.