Data Science & Artificial Intelligence

The Group has core research strength in mathematical foundation of AI and Data Science and its applications. This ranges from better understanding of AI, to advancing the state-of-the-art in deep learning and statistical data science, and tackling real-world problems in science, industry and society. The Group’s work tends to be cross-disciplinary, collaborating with domain experts within and outside the university.

Artificial Intelligence has significantly driven the growth of ICT research and application in modern society. The Data Science & AI group focuses on both theoretical and applied artificial intelligence research in a wide range of real-world applications.

The group has increasingly strengthened the core research on mathematical foundation of machine learning and artificial intelligence computing algorithms and its applications to computer vision, computer graphics, visual activity and motion recognition, and natural language processing and understanding. In addition, there is contemporary strong research on evolutionary computation and fuzzy systems and their applications in facial emotion recognition and video processing.

The Data Science & AI (DSAI) group continues to provide fundamental research on multiagent systems, audio computation and complex networks. The group is actively involved in tackling United Nations sustainable developments including digital health screening technology and precision agriculture. There is synergy on natural computing and computing vision research applied to solving various UK and worldwide industrial challenges including wearable sensing devices, anomaly detection and predictive maintenance, and autonomous vehicles. The Data Science & AI group played a key role in developing impactful knowledge transfer partnerships with regional companies through integrating computer vision and natural computing into company’s existing technologies. Our research is regularly supported by EPSRC, Royal Society, Innovate UK and other industrial collaborations.

Group leadership and contacts

Group Leader:

Prof. Wai Lok Woo

Interests: Artificial Intelligence, Machine learning/deep learning, Data Science, Signal Processing, Smart sensing, Digital Health and Wellbeing

Deputy:

Dr Ammar Belatreche

Interests: Bio-inspired intelligent systems, machine learning, face detection and recognition, structured and unstructured data analytics, capital markets engineering, image processing and understanding

Second Deputy:

Dr Ossama Alshabrawy

Interests: Artificial Intelligence, Machine learning/deep learning, Computer Vision, Digital Health and Wellbeing, Wearable Computing, Computational Behaviour Analysis

This research group forms part of the Department of Computer and Information Sciences.

Academic team

	Group Member: Prof. Longzhi Yang Research interests:
	Group Member: Dr Fouad Khelifi Research interests:
	Group Member: Dr Yilun Shang Research interests:
	Group Member: Dr Honglei Li Research interests:
	Group Member: Dr Hua Mao Research interests: Artificial Intelligence, Deep learning, Formal methods, Graph representation learning, Explainable AI, Multiview clustering.
	Group Member: Dr Farah Ahmed Research interests:
	Group Member: Dr Bing Zhai Research interests:
	Group Member: Dr Yulei Li Research interests: Large Language Models, Machine Learning/Deep Learning, Artificial Intelligence, Digitalisation/Digital Transformation, Information System
	Group Member: Dan Hodgson Research interests:
	Group Member: Chris Rook Research interests:
	Group Member: Dr Sharnil Pandya Research interests: AI for Sensors and information processing, AI for wellness, AI for Acoustics, AI for Computer Vision.

Doctoral students

Coming soon ...

Exemplar Projects Research relationships

Research from this group was submitted to REF2021 under UoA 11: Computer Science and Informatics.

To view research papers emanating from this group, please click here to view Northumbria Research Link, our open access repository of research output from Northumbria University.

More details coming soon..

Centre for Doctoral Training in Data Intensive Science

We lead an STFC Centre for Doctoral Training in Data Intensive Science, called NUdata, which is a collaboration between Northumbria and Newcastle Universities, STFC, and a portfolio of over 40 industrial partners, including SMEs, large/multinational companies, Government and not-for profit organisations, and international humanitarian organisations.

The Centre for Doctoral Training will train a new generation of PhD students with the skills required to address the data challenges presented by the STFC core-science programme, as well as applying those skills to different sectors of the broader economy. This will be done in an environment that is inclusive and values contributions to Equality, Diversity and Inclusion at all levels.

You can find out details of the Centre for Doctoral Training at https://research.northumbria.ac.uk/nudata/ including details of our 40+ industry partners.