The department’s research aim is to continue developing its research culture, capacity and international reputation. We are committed to engaging in knowledge generation, applicable research and enhanced societal impact activities. Expertise is housed in the research centre and visual computing lab and it is primarily focused around smart data analytics and visualisation, disruptive technologies and smart applications, cyber security, autonomous systems and robotics, telecommunications, computer vision, augmented and virtual reality.
Centre for Data and Complex Systems Research
Director: Professor Nik Bessis
Deputy Director: Professor Yannis Korkontzelos
The research centre has been formed to support the development of an environment of international excellence in the areas of computer and data science with a particular emphasis on smart data analytics, data representation and visualisation; cyber security; interoperable and interconnected distributed applications and technologies and smart infrastructures; AI and autonomous robotics, telecommunications, IoTs and other disruptive services and technologies. The research centre is structured into five high-level research groupings:
Smart data analytics
The Smart Data Analytics Research Group focusses on core and applied aspects of Data Analytics, Data Science and Machine Learning.
The Smart Data Analytics Research Group aims to promote and shape research relevant to the theory and practice of methods and tools for data collection, enrichment, processing and storage. It focuses on developing application-driven methods, algorithms and protocols that enable efficient collection, transfer and curation of images, videos, text, time series, data streams and other types of unstructured or semi-structured data.
The Group has expertise on a multitude of fields in the broad research areas of Machine Learning, Data Mining, Natural Language Processing, Social Media mining, Optimisation algorithms, Metaheuristics and AI Ethics. The Group’s research activity is inherently interdisciplinary. Application domains of current interest include medicine & healthcare, psychology, software analysis, astronomy, physics and unmanned aerial vehicles (UAVs) for geography.
- Real-time machine learning
- Resource-efficient machine learning
- Classification Imbalance
- outlier detection
- novelty detection (novel classes in dynamically-changing data)
- one-class learning
- Big data
- Data mining, pattern recognition & semantic analysis
- Natural Language Processing and Text Mining
- Social Media mining
- Metaheuristic Algorithms (single & multi-objective)
- Soft Computing Methods
- Search and Optimization Algorithms
- Grammar Induction, Inference and Domain Specific Languages
- Feature design and analysis
- AI Ethics
- Prof Yannis Korkontzelos (Group Leader)
- Dr Robert Lyon (Group co-leader)
- Dr Nonso Nnamoko
- Dr Hari Pandey
- Prof Marcello Trovati
- Dr Huaizhong Zhang
- Babatunde Onikoyi (PhD student, Graduate Teaching Assistant)
Our research group has attracted over £1M of external funding from several sources, such as InnovateUK and European Commission Horizon 2020.
- EC Horizon 2020 CrossMiner: Developer-Centric Knowledge Mining from Large Open-Source Software Repositories
- EC Horizon 2020 TYPHON: Polyglot and Hybrid Persistence Architectures for Big Data Analytics
Members of the group are supervising and have supervised many MRes and PhD students on research projects related to the research and application areas mentioned above. Members are always interested in supervising new PhD students.
To discuss potential PhD topics under Smart Data Analytics, please contact Prof Yannis Korkontzelos. For other enquiries related to PhD admissions, please contact Prof Ella Pereira, Director of Research.
Smart systems and applications
Research focus and activities
The focus of our group is on developing novel autonomous and smart systems, capable of collating, communicating, and computing information streams. The new paradigm of hybrid, complex and intelligent systems are expected to provide solutions to many health, industry and automation challenges, thus improving quality of life and wellbeing. However, developing interconnected/distributed systems have become increasingly complex and require expertise in the key enabling technologies such as Internet of Things (IoT), fog, cloud and AI.
Our group members with expertise in the areas of Distributed Systems, Distributed Middleware, Cloud computing, IoT and IoT enabled smart systems, applied AI/ML/Deep Learning, ontologies, semantic web and biometrics share interest in addressing challenges posed by the complexity of delivering highly reliable and dependable technological innovations and smart solutions. We carry out both fundamental and applied research.
With the strong focus on applications for digital health and industry 4.0 and its system based approach, the group compliments and synergise with the work carried out by colleagues from other research groupings within the department, e.g. smart analytics, computer vision and those from engineering disciplines. We believe that complexity involved in developing and delivering smart applications very often requires interdisciplinary approach to research and problem solving. To support of our interdisciplinary activities, internally, we are working with the Health Research Institute. Externally, we have established collaborations with industry, NHS, academic partners, stakeholders and research users.
- Fog/Edge/Cloud computing
- Distributed systems
- Applied AI/Machine Learning
- Internet of Things (IoT)
- Body/Sensor Networks
- Ontology and semantics technologies
- Digital health
- Healthcare applications
- Distributed Application/Systems development
- Multimedia Networks
- Mobile Applications – Mobile Healthcare
- Future Internet – IoT
- Industry 4.0
- Cyber Physical Systems
- Smart Cities
- Autonomous transportation systems
- Digital Twins
- Environmental/climate-change/Disaster management systems
- Prof Ella Pereira (Group Leader)
- Dr Muhammad Awais
- Prof Nik Bessis
- Prof Marcello Trovati
- Dr Nonso Nnamoko
- Dr Sarah McHale
- Dr Peter Matthew
- Dr Huazhong Zhang
- Dr Mohzin Raza
- Dr Xutao Deng
- Wilson Costa (PhD student, Graduate Teaching Assistant)
- Hezekiah Samwini (PhD student, Graduate Teaching Assistant)
Our research group has attracted close to £1M of external funding from several sources, such as InnovateUK, EPSRC and the Department for Education.
- KTPs with Country Range Group LTD and BEC Integration LTD
The group members have extended experience of supervising MRes and PhD studies and welcomes proposals on the topics related to the groups research activities and interests, above.
For any PhD or other enquiries please contact Prof Ella Pereira, Director of Research.
The Cyber Security Research group is committed to carry out internationally recognized, high-quality research on security and privacy in computer systems and networks. We collaborate with academic and industrial partners in the UK and worldwide in different research and knowledge transfer projects. The research activities of the group focus on designing and evaluating secure and privacy friendly systems, networks, and applications, by proposing novel approaches in these areas. Several of our publications appeared in reputed journals and conferences. Along with the research activities, we teach several modules in undergraduate and postgraduate security programmes at Edge Hill University.
Blockchain based security and privacy enhancing technologies and applications
The concept of enterprise and permissioned blockchains opens many opportunities to design and develop decentralised applications to provide higher degree of data control and transparency for the users. Another advantage is that smart contracts can be used to automate security verification and notification in enterprise environments. We investigate the application of this decentralised concept, and design new applications such as distributed collaborative intrusion detection systems (IDSs), and decentralised data protection mandate enforcement engines.
Security and privacy by design
System design goes through several stages before it is finally followed by implementation and production. It is crucial that any flaw in the design is recognised and fixed at the early stage to avoid production and implementation delay and additional cost. Our research covers different areas of system design, including threat and risk assessment, user-centred design and fully automated or computer aided security and privacy verification methods.
Security and privacy problems of Internet of Things and smart services and applications.
Internet of Things (IoT) applications help making our life more convenient and safer, and enable smart city, smart homes, or smart health-care initiatives worldwide.
Potential design flaws in these applications and services pose high security and privacy risks to the system users. To prevent this, we design and evaluate secure and privacy friendly approaches for IoT applications and developing testbeds for performance evaluations.
Security and privacy problems of biometrics systems and applications.
Biometrics systems are broadly used for authentication purposes; however, applying them correctly as part of a complex security system is not trivial. Incorrect application or installation can pose security and privacy risks and violate data protection mandates. We focus on designing and developing approaches and algorithms to improve the effectiveness of biometrics authentication, and model different types of biometric systems to evaluate their security and privacy properties based on mathematical methods.
- Dr Vinh-Thong Ta (Group Leader)
- Dr Mark Liptrott
- Dr Peter Matthew
- Dr Sarah McHale
- Dr Nonso Nnamoko
- Prof Marcello Trovati
Our research group has attracted approximately £250K of external funding from several sources, such as Higher Education Academy and the Department of Business, Energy and Industrial Strategy.
Cyber Security Student Club
The Cyber Security Student Club gathers talented students who expressed strong interest in the field of cyber security. Core members meet to expand their knowledge by discussing and solving practical exercises and problems in system and network security, to socialize, and in general, to have fun with others of similar interest. Members also prepare for Capture the Flag (CTF) competitions and creating practical ethical hacking exercises.
If you are interested in joining the club, please contact Dr Vinh-Thong Ta. Note: The club is only open for students of the Computer Science Department at Edge Hill university.
Members of the group are supervising and have supervised many MRes and PhD students on research projects related to the research and application areas, above. Members are always interested in supervising new PhD students.
Robotics and autonomous systems
The main goal of the Robotics and Autonomous Systems (RAS) research group is to provide innovative solutions and develop novel AI-driven robotics systems to address real-world challenges in a broad range of contexts. We are a newly established interdisciplinary group, looking for synergies and collaborations with national and international industrial and academic partners to transfer knowledge and technology and co-produce impactful research. Our research activities are supported by a suite of state-of-the-art technologies and facilities for robot design and construction.
- Robot mechatronic design
- Bio-inspired robots
- Unmanned aerial vehicles
- Underwater robotics
- Machine vision in robotics
- Soft robotics
- Swarm Robots
- Robots for inspection tasks and hazardous environments
- Industrial robotic automation
- Dr Ammar Al Mhdawi (Group Leader)
- Dr Swagat Kumar(Group co-leader)
- Dr Ardhendu Behera
- Prof Nik Bessis
- Dr Nonso Nnamoko
Members of our research group have attracted approximately £250K of external funding from several sources, such as UKIERI and RCUK.
Automation, robotics, and mechatronics are important technologies that underlie a wide range of applications in manufacturing and automation, as well as autonomous vehicles and robots for surgery. Currently, we are seeking research PhD students to work on novel robotics projects. To discuss potential MRes and PhD topics under Robotics and Autonomous Systems, please contact Dr Ammar Al Mhdawi. For other enquiries related to PhD admissions, please contact Prof Ella Pereira, Director of Research.
Communication Systems Research Group focuses on interdisciplinary fundamental and practical research in communication systems and networks. We aim to research and engineer the underlying technology required to enable the effective functionality of next generation of communication systems (6G). The group supports our partners in the design, development and testing of vertical applications and services in multiple user community-driven contexts, including smart healthcare, intelligent transport, industry 4.0 and smart cities.
- Wireless Systems and Services
- Internet of Things
- AI in Communication Network
- Security in Communication Networks
- Satellite Communication and Applications
- Satellite and Mobile Networks
- Future Disruptive Technologies and Networks
- Dr Hassan Malik (Group Leader)
- Prof Ray Sheriff (Group Co-leader)
- Dr Mohsin Raza
- Dr Muhammad Awais
- Dr Umar Khan
- Brian Akwirry (PhD student)
The group members have extended experience of supervising MRes and PhD studies and welcome proposals on the topics related to the groups research activities and interests. The topics include, but are not limited to:
- AI in wireless Network
- 5G application in Healthcare, Intelligent Transport, Industry 4.0
- 6G Networks
- Satellite Communication
Visual Computing Lab
Director: Prof. Yonghuai Liu
The lab focuses on the topics in the general areas of 3D computer vision, image processing, pattern recognition, visual data analytics, computer graphics, virtual/augmented reality, human sensing and human-robot social interactions. The research is supported by the latest technologies such as the Computer Augmented Virtual Environment (CAVE) and a range of state-of-the-art devices for data acquisition, output, visualisation, and full immersive experiences including: Tobii Eye X, Vive, Z-Space, Kinects, Hype Box, Emotive, Enobio BCI, Nao Robots, 3D Scanner and printer. It has the following goals:
- connecting with stakeholders to impact society
- supporting students to test the latest visual computing techniques and acquire research-lead employability skills
- empowering researchers to solve theoretical and real-world problems in visual computing and utilising virtual and augmented reality technology.
It aims to:
- Visualise the signal, image, shape and video data and their operations with the modern CAVE and other devices.
- enhance the visual data for high contrast and removal of unwanted factors,
- analyse and convert the visual data into semantically meaningful components, models, measurements, relevant knowledge and/or interesting responses and behaviours
- explore data visualisation and AR/VR simulation and applications in the real world such as medical imaging, training, computer aided instruction, CAD, systems automation, additive manufacturing, plant science, robotics, autonomous vehicles, intelligent surveillance, remote sensing, industrial quality assurance, and others.
It currently focuses on, but is not limited to, the following areas:
3D computer vision
- 3D shape modelling, analysis and measurements
- camera calibration
- 3D model search and query
- Image noise removal, enhancement and super-resolution.
- Image analysis, decomposition, segmentation, classification and recognition.
- Object detection, classification, recognition and tracking
- Segmentation, clustering, consistency modelling
Computer graphics, virtual/augmented reality, visualisation
- Big-data visualisation
- Reflectance modelling, rendering
- Crowd modelling and simulation
Human sensing and human-robot social interaction
- Facial expression and emotion recognition
- Human visual perception
- Human behaviour representation, responses and prediction
- Human activity/pose representation, estimation, classification, and recognition
- CCTV surveillance and management
- Dr. Ardhendu Behera
- Prof. Yonghuai Liu
- Dr. Peter Matthew
- Dr. Peter Vangorp,
- Dr. Huaizhong Zhang
Data Science STEM Research Centre
Our strategic target for growth in Data Analytics has enabled the department of Computer Science to found and lead an interdisciplinary STEMM research centre, which draws expertise from multiple subjects across the University.
Outcomes and activities
Our research work is captured in:
We also have impact case studies:
Developing simulation software in order to improve technology enhanced learning of modern computer architecture
Teaching and learning of computer architecture has been enhanced using highly interactive simulations with carefully constructed visualisations and animations. Computer scientists need to understand and observe how different parts of a modern computer system’s architecture and organization fit together, interact and support each other. Unique educational simulation software has been designed, developed and evaluated with these requirements in mind. Since the software and teaching materials have been made public, numerous universities worldwide adopted it in their courses with claimed positive impact on student engagement, course popularity, grades, speed of delivery of curriculum, attendance and peer recognition of best practice.
Improving quality assurance of a large software model through relative debugging
As a result of collaborative commissioned research, the lead developers of a major atmospheric research and operational weather forecasting model have changed their approach to quality assuring model source code. Drawing directly on the research findings, the lead developer has taken the decision to adopt a new approach to the correction of inconsistencies and inefficiencies in source code and to alter the software build procedure to be followed by a large model development community. An additional impact, in the form of improved business competitiveness, is felt by a British software and consultancy company, which has been able to enhance a key tool used in their quality assurance and platform migration work with a global client base.
Academics, post-doctoral and PhD researchers have access to cutting-edge facilities including state-of-the-art software (SAS, Matlab, Unity, etc) and hardware (high-end servers, robots, transparent touchscreens, Hololens, VIVEs and the first 4K CAVE installed in a UK academic institution).
The department has also an established community of Postgraduate Researchers undertaking research in different areas of computer science. We operate under a University research governance and ethics framework.