Dr Elias Eze
Intelligent Technologies Research Group, Research Enhanced Learning and Teaching Research Group, Smart City Research Group.
, School of Architecture, Computing and Engineering
Dr Elias Eze is a Lecturer in Computer Science & Digital Technology (CDT) at the Department of Computing and Engineering at the University of East London (UEL). He joined CDT, at the UEL in July 2022. Prior to joining UEL, he worked as a Research Fellow in Big Data analytics and Associate Lecturer at the University of Bedfordshire. Dr Eze began his academic career in Nigeria when he joined the Department of Computer Science in Ebonyi State University in February 2010. Dr Eze has a number of research articles published in peer-review research journals, edited books, and international conferences.
- Certified Ethical Hacker (CEH)
- Associate Member of the British Computer Society (AMBCS)
- Member of the Institution of Engineering and Technology (MIET)
- Member of the Institute of Electrical and Electronics Engineers (MIEEE)
Areas Of Interest
- Cyber security.
- Networks and network security.
- Intelligent Systems.
- Legal, social and ethical issues in the context of IT and Computing.
Dr Elias Eze is a specialist in Big data analytics, data mining, modelling, data security, and artificial intelligence (deep neural networks and machine learning). Dr Eze has almost 12 years' experience of working in the UK and overseas Higher Education (HE) sector and rich experiences in research and applications of deep neural networks in data pre-processing, modelling and analysis. He is a Certified Ethical Hacker (CEH), and an associate member of the British Computer Society. Dr Eze received his BSc in Computer Science from Ebonyi State University, Nigeria. He obtained MSc in Computer Networking (2012) and PhD in Computer Science in 2012 and 2017, respectively, from University of Bedfordshire.
Dr Eze has taught different computing modules (and large number of students) since joining the HE sector. His teaching/research interests are wide and varied and currently include Computers and Networks Security, Artificial Intelligence, Deep Learning, Cyber Security, Machine Learning, and the use of virtualisation technologies.
Dr Eze is accepting new national and international postgraduate research students and is willing to discuss the novelty of their applications.
RESEARCH AND IMPACT
One of Dr Eze's recent research projects is in application of deep neural network and machine learning algorithms for improved Big Data Analytics in Advancing Digital Precision Aquaculture in China (ADPAC) - project funded by the Newton Fund through Innovate UK & Biotechnology and Biological Sciences Research Council (BBSRC) to bring state-of-the-art sensing technology, 5G wireless connectivity and Big Data Analytics together to revolutionise aquaculture in China.
The ADPAC project in China with the aims to advance aquaculture towards 'Aquaculture 4.0' – a highly connected and automated cyber-physical system using digital technologies. In other words, a remote network of wirelessly connected sensor packages for monitoring water quality conditions. This is to allow the farm operators to make informed management and husbandry decisions in real-time and support automated systems such as feeding. This was achieved by bringing together state-of-the-art sensors, 5G-IoT connectivity and Big Data analytics into one integrated package. This project has been made possible by the Newton Fund delivering support through UK Research and Innovation (UKRI) and BBSRC and delivered by colleagues from industry and academia in UK and China.
The Aquaculture 4.0 initiative aims to drive a digital transformation of traditional, extensive aquafarming towards modern precision farming to improve efficiency and yields to meet the protein requirements of an expanding global population while reducing the industry's environmental footprint. The project has seen design and installation of a multi-parameter cabinet system equipped with an advanced sensor suite and 5G wireless connectivity. The data visualization and operational control is available through a dedicated, cloud-based software.
MOST RECENT RESEARCH
- Eze E, Halse S, Ajmal T. "Developing a Novel Water Quality Prediction Model for a South African Aquaculture Farm", Water. 13(13):1782, 2021.
- Eze, E., Sant, P., Zhang, S., Feng, X., Shukla, M., Eze, J. and Liu, E. "Mobile Computing and IoT: Radio Spectrum Requirement for Timely and Reliable Message Delivery Over Internet of Vehicles (IoVs)", In Internet of Things (IoT), Springer, Cham, pp. 235-256, 2020.
- E. Eze, S. Zhang, E. Liu, J. Eze, and S. Muhammed, "Reliable and Enhanced Cooperative Cross-layer Medium Access Control Scheme for Vehicular Communication" IET Networks, vol. 7, no. 5, pp. 200-209, 2018.
- Supervision of final-year projects.
- Supervision of Master Dissertations
- Supervision of Doctoral Students
- CN6003 - Computers and Network Security.
- CN7031 - Big Data Analytics.
Reviewer in Scientific Journals
- IEEE Access
- IEEE Transactions on Intelligent Transportation Systems
- IET Networks
- IET Internet of Things
- IEEE Transactions on Automatic Control
- IEEE Transactions on Automation Science and Engineering
- IEEE Transactions on Cognitive Communications and Networking
- Journal of Communications and Networks
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
- Computing in Science & Engineering
- MDPI Sensors
- MDPI Social Sciences
- MDPI Water