Projects per year
Personal profile
Academic Background
Areas of Expertise
Aritificial Intelligence, Machine Learning, Data mining for classification, clustering, regression, prediction, pattern recognition, feature selection, etc.
Merthods: Artificial Neural Networks; Decision Tree Induction; Expert Systems, Feature Selection Ensemble; Clustering Ensemble, Hybrid ensemble systems;
Data: numerical data and multi-mediam data including text, image, vedio, autio and time series.
Applications in healthcare, insurance, finance, accountancy, computational biology, and various business and industrial processes.
Career
Dr. Wang joined the School of Computing Sciences (CMP), UEA, as a senior lecturer in September 2002. He and his PhD students conduct research in the areas of data mining/knowledge discovery, ensemble approach and artificial intelligence. 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 and the organiser for Masters Dissertation projects, and admissions officer for Overseas applications.
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)
Network
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Developing an Artificial Intelligence Ensemble for Enhancing Seabed Mapping of the GeoSwath System
1/04/21 → 31/03/23
Project: Research
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Developing an Artificial Intelligence Ensemble for Enhancing Seabed Mapping of the GeoSwath System
1/04/21 → 31/03/23
Project: Research
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Smart Environments Research Facility
Lettice, F., Aung, M. H., Bagnall, T., Buckley, O., Cawley, G., Day, A., De La Iglesia, B., Finlayson, G., Harvey, R., Huber, K., Kulinskaya, E., Laycock, S., Lines, J., Mackiewicz, M., Milner, B., Moulton, V., Parr, G., Ren, E. & Wang, W.
Engineering and Physical Sciences Research Council
10/01/20 → 8/07/22
Project: Research
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Developing a hybrid artificial intelligence method for improving seabed mapping accuracy
Wang, W., Milner, B. & Websdale, D.
6/01/20 → 10/07/20
Project: Research
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Developing a hybrid artificial intelligence method for improving seabed mapping accuracy
Wang, W., Milner, B., Holmes, M. & Websdale, D.
6/01/20 → 10/07/20
Project: Research
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Some fundamental issues in ensemble methods
Wang, W., 2008, p. 2244-2251. 8 p.Research output: Contribution to conference › Paper
Open AccessFile40 Citations (Scopus)27 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) -
Novel methods for imputing missing values in water level monitoring data
Khampuengson, T. & Wang, W., Jan 2023, In: Water Resources Management. 37, 2, p. 851-878 28 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Downloads (Pure) -
Creating Variant Features to Enhance Covid-19 Predictions with Machine Learning Ensemble
Wood, J. & Wang, W., 21 Jan 2022, Preprints.org.Research output: Working paper › Preprint
Open Access -
Decision level ensemble method for classifying multi-media data
Alyahyan, S. & Wang, W., Apr 2022, In: Wireless Networks. 28, 3, p. 1219–1227 9 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile46 Downloads (Pure)
Prizes
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Best Poster Award
Alshaqsi, J. (Recipient) & Wang, Wenjia (Recipient), 2010
Prize: Prize (including medals and awards)
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Best Student's Paper
Alyahyan, S. (Recipient) & Wang, Wenjia (Recipient), Dec 2018
Prize: Prize (including medals and awards)
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UEA Innovation and Impact Awards
Wang, Wenjia (Recipient) & Milner, Ben (Recipient), May 2021
Prize: Prize (including medals and awards)
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UEA Innovation and Impact Awards
Wang, Wenjia (Recipient) & Milner, Ben (Recipient), May 2022
Prize: Prize (including medals and awards)
Activities
- 2 Invited talk
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Innovate UK First of a Kind Rail Funding Competition and Demonstration Event
Wenjia Wang (Speaker)
5 May 2022Activity: Participating in or organising an event › Invited talk
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DelayExplorer – A tool for exploring train delay relationships
Wenjia Wang (Speaker)
Sep 2020Activity: Participating in or organising an event › Invited talk