✦ Artificial Intelligence ✦ Cyber Security and Forensics
✦ Robotics & Automation ✦ Innovative Application & Commercialisation
My research mainly focuses on the theoretical development and practical applications of Computational Intelligence techniques under dynamic, uncertain, customised environments. Some selected research projects are listed below.
Development of a new capability in digital business to grow and diversify income through design and implementation of the SportsAid Athlete Monitoring System (SAMS) to manage athlete performance, health and well-being to win new business in sport and education organisations and with individuals. Please click here to read more about this proejct.
This project aims to develop a new fuzzy modelling approach using the curvature values. This PhD project is co-funded by Yobo Technology Ltd., China and the university. UK Principle Investigator: Dr. Longzhi Yang, and Thailand Principle Investigator: Dr. Tossapon Boongoen
PI: Prof. Lynne Coventry, I'm one of the Co-I
The Academic Centres of Excellence in Cyber Security Research (ACEs-CSR) scheme is sponsored through the Department for Digital, Culture, Media and Sport. It is one of a number of initiatives outlined in the UK Government's £1.9 billion National Cyber Security Strategy 2016-2021, 'Protecting and Promoting the UK in a Digital World', which outlines how Government is working with academia and industry to make the UK more resilient to cyber attacks.
After successfully meeting the scheme’s tough requirements, Northumbria has now been recognised as an ACE-CSR. The Northumbria Cyber Security Research Group leads the University’s research across this area. This multi-disciplinary group combines technical research on biometric encryption, wireless sensor networks, web security protocols, and image recognition, with human-centred work on usable security, privacy, trust and behaviour change. The group’s work identifies both the virtual and physical risks associated with connected smart cities and complements other work ongoing at the University relating to the digital living space, which explores the intersection of people, place and technology in the digital and urban environment.
Collaborated with a local company in developing a digital solution for for effluent treatment recommendation
Collaborated with a local company in developing a digital solution for running product recommendation
This project aims to develop an open cyber security research and practice platform. Prinicple supervisor: Dr. Longzhi Yang
Smart meters have been partially deployed to UK homes to support consumers in managing their energy and expenditure intelligently, to help implement the CO2 emission reduction goal. However, the information from smart meters is still not enough for efficient intelligent home appliance control, as the residents’ living behaviour patterns, as well as the surrounding environments also have great influences on the control decisions for home appliances. Despite of the advance in machine learning and expert system technologies, the extraction of decision patterns based on residents’ behaviours and the surrounding environments is still of great challenge as every resident has their own living style and each dwelling has its own unique characteristics.
Take intelligent home heating systems as an example. In order to accurately and economically control the home heating systems such that a property can always be properly pre-heated when the residents getting home whilst no energy is unnecessarily wasted on heating empty dwellings, the control system should be developed based on a well understating of the information from smart meters (such as electricity supply/demand pattern) and the residents’ living styles, and be timely updated when the supply/demand pattern or the living styles change. However, it is unrealistic for system manufacturer to collect highly personalised data and to consequently produce customised heating controllers for each household, such that the heating controller can make accurate decisions based on the residents’ unique living style in addition to the current electricity supply/demand pattern and surrounding environment.
This research proposes an algorithm which would enable intelligent home heating system to efficiently learn the residents’ behaviour patterns associated with the information from smart maters in a dynamic and adaptive manner. Consequently, mass-production of intelligent heating controllers is allowed. In particular, these devices are initialised by the most general and common rules which are suitable for the majority of people. Then the intelligent controller will learn more customised details in real time after it is deployed. Also, once the electricity supply/demand pattern and the living style or the users of the controller have changed, the controller will be able to catch the changes up in real time. It has been reported that around 40% residential energy use is consumed to deliver ‘unused’ energy services. The proposed approach will potentially provide significant help in reducing energy waste and CO2 emission but in the same time improving the quality of life.
PI: Dr. Longzhi Yang
Simpson Group is one of the UK’s leading manufactures of posters and 3D displays for promotions. The company has a number of customers we are all very familiar with, such as Next, Morrison's, and Danbenhams. A promotion usually involves multiple display objects, and a display object is typically produced in a sequence of operations. In addition, an operation can be alternatively conducted by different capable machines with different costs. This project developed a software prototype which intelligently schedules the manufacturing production line use CI techniques and thus improves production efficiency.
This project aims to teach robots to write in an analogy to how humban being writes. PI: Dr. Fei Chao at Xiamen University, China
Interaction based on motion analysis. PI: Dr. Hubert P.H. Shum at Nothumbria University
MEXT Top Global University Project Scholarship: £5,500, Contributing Researcher (PI: Prof. Shigeo Morishima). Received from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT)To support 1 Japanese PhD (Waseda University) working in the UK for 6 months .
You are welcome to discuss any of my work with me to promote their potential in research/industrial collaboration, knowledge transfer, commercialisation, and so on.
Paras is working on developing Athelete Monitoring System App, a KTP partnership between Northumbria University and SportsAid. He is a full stack developer developing scalable web applications. His experience include working with Indian and German tech startups. You can find see some of his previous works at GitHub and projects at LinkedIn.
More details are on its way......
More details are on its way......
Lead Developer of MSc AI
1. EAE0004: Placement year tutor - Accenture and HMRC
2. CM0645: Individual Project
3. IS0749: MSc Individual Project
1. KV7003: AI and Digital Technologies
1. KF6007: Artificial Intelligence and Robotics
2. KV6002: Professionalism and Team Project
3. KF5004: Advanced Operating Systems
4. EN0402: Programming Fundamentals with Robots
Founding Chair of IEEE Special Interest Group of Big Data for Cyber Security and Privacy
General Co-chair, UKCI 2019
Poster Chair, BMVC 2018
Lead Chair of Annual Special Session Fuzzy Logic Systems for Security and Forensics:
- Special Session 04 "Fuzzy Logic Systems for Security and Forensics" at FUZZ-IEEE 2017
Associated Editor of IEEE ACCESS (IF=4.098)
Leading Guest Editor for Special of Recent advances in Data Science and Systems in Expert Systems (IF=1.505)
Leading Guest Editor for Special Issue on emerging Trends and Applications in Cloud Computing in Springer journal of Wireless Networks (IF=2.405)
Guest Editor for Special Issue on Intelligent, Smart and Scalable Cyber-Physical Systems in the Journal of Intelligent and Fuzzy Systems (IF=1.637)
Guest Editor of Multimedia Tools and Applications for special issue on “Soft computing Techniques and Applications for Intelligent Multimedia Systems”
IEEE Transaction on Fuzzy Systems
IEEE Transaction on Cybernetics
IEEE Transaction on Big Data
IEEE Transaction on Circuits and Systems for Video Technology
IEEE Journal of Biomedical and Health Informatics
The IEEE/CAA Journal of Automatica Sinica
Fuzzy Sets and Systems (Elsevier)
Expert Systems (Wiley)
Neural Computing and Applications (Elsevier)
Computers and Electrical Engineering (Elsevier)
Knowledge Based Systems
International Journal of Machine Learning and Cybernetics
2018: Fuzzy Rule Interpolation Systems, Department of Computer Science, Aberystwyth University
2018: Fuzzy Rule Interpolation Systems, Department of Computer Science and Technology, University of Bedfordshire
2017: Fuzzy Rule Interpolation Systems, School of Computing, the University of Portsmouth
2015: Fuzzy Interpolation and Its Application in Smart Home, the 12th Haiyun Lecturer of 2015 at Xiamen University
2014: AI Techniques and Their Potential Application in Print Industry, Simpson Group, Newcastle upon Tyne, UK
2012: Data Quality Assessment: from Computing Point of View - CSOMOS Symposium: A Roadmap to Navigate from Databases to Adverse Outcome Pathways, Bradford, UK
2012: Data Quality Assessment and Control - SEURAT-1 Summer School, Oeiras, Portugal
2011: Fuzzy Interpolation and Its Adaptation - Research Seminar of SCIM, University of Bradford, UK
The IEEE International Conference on Fuzzy Systems
The IEEE International Conference on Tools with Artificial Intelligence
The International Conference on Fuzzy Systems and Knowledge Discovery
The UK and Ireland Workshop on Computational Intelligence
The IEEE International Symposium on Multimedia
The International Conference on on Information Science and Security
The International Conference on IT Convergence and Security
The International Conference on Information Science and Applications
The International Conference on Advanced Computational Intelligence
Open positions for different level of researchers or students are available, with a wide range of research projects for selection (See "Research Projects" page for details), please feel free to contact if you are interested.
Highly motivated PhD candidates are welcomed to join, and self-funded student can be accepted all year around.
Internship students and vistings students are welcome to join us for summer projects.
Motivated visiting scholars are particularly welcome, and we will provide support for candidate to apply the fund for visiting.
Motivated post-docs candidates are also welcome, self-funded ones will be particularly encouraged to apply, support will be provided to apply for other funding opportunities, such as Newton International fellowships.