Projects per year
Personal profile
Academic Background
Dr Wang received his BEng (1982) and MEng (1985) degrees from NEU (NorthEastern University, China) in Electrical and Automatic Control Engineering, and PhD degree in Advanced Computing with Neural Networks and Genetic Algoirthm in 1996 from the University of Manchester Institute of Science and Technology(UMIST), UK.
Areas of Expertise
Aritificial Intelligence, Machine Learning, Deep Learning Neural Networks, Large Language Models(LLM), Natural Langauage Processing(NLP), ChatBot, Data mining for classification, clustering, regression, prediction, pattern recognition, feature selection, etc.
Merthods: Artificial Neural Networks; Deep Learning Neural Networks, Transformers, Belief Networks, Decision Tree Induction; Expert Systems, Feature Selection Ensemble; Clustering Ensemble, Hybrid ensemble systems;
Data: numerical data and multi-mediam or multi-modal data including text, image, vedio, autio and time series.
Applications in healthcare, marine science, insurance, finance, retails, accountancy, computational biology, and various business and industrial processes.
Career
Wenjia Wang is a Professor of Artificial Intelligence(AI) at the School of Computing Sciences (CMP), UEA. He leads a research laboratory in AI and conduct research and innovation in various areas of AI, Machine Learning, Deep neural Networks, Data Science, Large and Small Language Models. His research focuses on developing ensemble approach of AI and Machine Learning.
He welcomes and encourages any potentials to contact him to discuss possible research topics.
He has been the Director of MSc in Computer Science since 2003.
Key Research Interests
ueaeprints.uea.ac.uk/view/creators/wjw.html
Wenjia Wang is part of the Machine learning and statistics group
Dr Wang has been doing research in the areas of AI, Knowledge Discovery, Data Mining and Operational Research for many years. He holds the memberships of IEEE, IEEE Neural Networks Society and IEEE Computer Science Society.
His currents research interests include
- Artificial neural networks
- Decision tree induction
- Bayesian theory
- Evolutionary computing and Genetic Algorithm
- Machine learning ensemble methodology
- Generic ensemble: topology, diversity, and decision fusion strategies
- Classification ensemble
- Clustering ensemble
- Feature selection ensemble
- Feature Salince Estimation and Feature Selection
- Data/text and multi-media mining applications
- Heathcare and medical areas
- Bioinformatics
- Finance and insurance
- Security and crime data
- Sentiment and fake reviews/news identificaiton and classification
- Citizen Sciecnes
- Other areas
Past Research Grants
- RSSB/RRUKA grant: "Feasibility study on developing an intelligence ensemble system for predicting and preventing train delay"
- PI: Dr. Wenjia Wang
- Team: Prof Gerard Parr(CI), Douglas Fraser(Senior RA), Mary Symons, Bradley Thompson, Ryan McDonagh
- Collaborators: Greater Anglia and Network Rail
- EPSRC Grant: "Hybrid Artificial Intelligence Ensemble for Early Detection of Osteoposis
- PI: Dr. Wenjia Wang - Principal Investigator(PI);
- Team: Dr. Sarah Rae - Co-Investigator(CI), Rhumotology Consultant with Bedford Hospital; and Dr. Greame Richards (Research Fellow)
- ESRC Grant: "Identifying Relevant Factors and discovering Complex Patterns in Fuel Poverty"
- PI: Dr. Wenjia Wang(PI),
- Team: Professor Catherine Waddams (School of Management, UEA), Dr. Karl Brazier (Research Fellow)
- EPSRC Grant: "Feature Salience Identification and Methodological Diversity for Improved Prediction"
- PI: Dr. Wenjia Wang(PI),
- Team: Professor Derek Partridge (CI, Exeter University), Dr. Karl Brazier (Research Fellow), and Dr. John Etherington (Defence Service Medical Rehibilitation Centre)
Key Responsibilities
Deputy Director of Postgraduate Research
Director of MSc Computer Science
Admissions Officer for Overseas Applications
Teaching Interests
Dr. Wang teaches a variety of units to both undergraduate and postgratuate courses, including
- Artificial Intelligence,
- Internet Technology,
- Programming (Java) and Applications,
- Research Techniques,
- Research Methods,
- Data Mining.
He is the organiser of MSc Dissertation unit and Research Techniques/Methods units.
Biography
Website: http://www.cmp.uea.ac.uk/~wjw/
Follow this link for details of current PhD opportunities in Computing Sciences. But feel free to email me to discuss projects outside these areas and alternative sources of funding.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Keywords
- Computing Science (general)
Collaborations and top research areas from the last five years
-
Using Digital Technologies to Accelerate Healthy Snack Product Innovation
1/09/24 → 28/02/26
Project: Research
-
AIM4SafeBaby- Artificial Intelligence monitoring for Safe baby birth
Wang, W., De La Iglesia, B. & Lapeer, R.
1/01/24 → 30/06/26
Project: Research
-
-
AI techniques for improving Seabed Mapping
1/12/23 → 31/07/24
Project: Internal Funding › ADR Impact Fund
-
Some fundamental issues in ensemble methods
Wang, W., 2008, p. 2244-2251. 8 p.Research output: Contribution to conference › Paper
Open AccessFile49 Citations (Scopus)50 Downloads (Pure) -
A Novel Ensemble of Distance Measures for Feature Evaluation: Application to Sonar Imagery
Harrison, R., Birchall, R., Mann, D. & Wang, W., 2011, Intelligent Data Engineering and Automated Learning - IDEAL 2011. Yin, H., Wang, W. & Rayward-Smith, V. (eds.). Springer, p. 327-336 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
4 Citations (Scopus) -
Heterogeneous machine learning ensembles for predicting train delays
Al Ghamdi, M., Parr, G. & Wang, W., Jun 2024, In: IEEE Transactions on Intelligent Transportation Systems. 25, 6, p. 5138-5153 16 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile1 Citation (Scopus)27 Downloads (Pure) -
Quantitative and qualitative similarity measure for data clustering analysis
AlShaqsi, J., Wang, W., Drogham, O. & Alkhawaldeh, R. S., Dec 2024, In: Cluster Computing. 27, 10, p. 14977-15002 26 p.Research output: Contribution to journal › Article › peer-review
-
Tri-level robust clustering ensemble (TRCE) algorithm for clustering enhancement with comparative analysis
Alshaqsi, J., Wang, W. & Drogham, O., 9 Aug 2024, In: Engineered Science. 30, 13 p., 1186.Research output: Contribution to journal › Article › peer-review
Prizes
-
Best Poster Award
Alshaqsi, Jamil (Recipient) & Wang, Wenjia (Recipient), 2010
Prize: Prize (including medals and awards)
-
Best Student's Paper
Alyahyan, Saleh (Recipient) & Wang, Wenjia (Recipient), Dec 2018
Prize: Prize (including medals and awards)
-
-
UEA Innovation and Impact Awards
Wang, Wenjia (Recipient) & Milner, Ben (Recipient), May 2021
Prize: Prize (including medals and awards)
-
UEA Innovation and Impact Awards
Wang, Wenjia (Recipient) & Milner, Ben (Recipient), May 2022
Prize: Prize (including medals and awards)
Activities
-
Advance HE (External organisation)
Wenjia Wang (Member)
24 Oct 2024Activity: Membership › Network, Working Group or Professional Association
-
Cornell University
Wenjia Wang (Visiting researcher)
15 Mar 2024 → 25 Mar 2024Activity: Visiting an external institution › Visiting an external academic institution
-
Public Sector Future Connectivity 2024
Wenjia Wang (Speaker)
6 Mar 2024Activity: Participating in or organising an event › Invited talk