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.
Dr Wang received his BEng (1982) and MEng (1985) degrees from NEU (NorthEastern University, China) in Automatic Control Engineering, and PhD degree in Advanced Computing in 1996 from the University of Manchester Institute of Science and Technology(UMIST), UK.
A Novel Ensemble of Distance Measures for Feature Evaluation: Application to Sonar Imagery,
in Intelligent Data Engineering and Automated Learning - IDEAL 2011.
pp. 327-336Full Text UEA Repository
Some fundimental issues in ensemble methods,UEA Repository
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Automatic Counting of Wheat Spikes from Wheat Growth Images,
in 7th International Conference on Pattern Recognition Applications and Methods.
SCITEPRESS – Science and Technology Publications
ISBN 978-989-758-276-9Full Text UEA Repository
Clustering ensemble method,
in International Journal of Machine Learning and CyberneticsFull Text UEA Repository
(E-pub ahead of print)
Feature Level Ensemble Method for Classifying Multi-Media Data,
in International Conference on Innovative Techniques and Applications of Artificial Intelligence : SGAI 2017: Artificial Intelligence XXXIV.
ISBN 978-3-319-71077-8Full Text UEA Repository
Expression and X-Ray Structural Determination of the Nucleoprotein of Lassa Fever Virus,
in Hemorrhagic Fever Viruses : Methods and Protocols.
ISBN 978-1-4939-6980-7Full Text UEA Repository
Determining appropriate approaches for using data in feature selection,
in International Journal of Machine Learning and Cybernetics
pp. 915–928Full Text UEA Repository
Dynamic ensemble selection methods for heterogeneous data mining,
in 12th World Congress on Intelligent Control and Automation (WCICA), 2016.
ISBN 978-1-4673-8415-5Full Text UEA Repository
Heterogeneous Ensemble for Imaginary Scene Classification,
in Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR.
ISBN 978-989-758-203-5Full Text UEA Repository
Modelling the role of catastrophe, crossover and Katanin in the self organisation of cortical microtubules,
in IET Systems Biology
pp. 277-284Full Text UEA Repository
Weighted Heuristic Ensemble of Filters,UEA Repository
Retinal vessel segmentation using multi-scale textons derived from keypoints,
in Computerized Medical Imaging and Graphics
pp. 47-56Full Text UEA Repository
A New Consensus Function based on Dual-Similarity Measurements for Clustering Ensemble,UEA Repository
An Algorithm for Identifying the Learning Patterns in Big Data,UEA Repository
Comparative performance of Texton based vascular tree segmentation in retinal images,
in 2014 IEEE International Conference on Image Processing (ICIP).
pp. 952-956Full Text UEA Repository
Autoimmune hemolytic anemia after allogeneic hematopoietic stem cell transplantation: Analysis of 533 adult patients who underwent transplantation at King’s College Hospital,
in Biology of Blood and Marrow Transplantation
pp. 60-66Full Text UEA Repository
Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF),
in Machine Learning and Data Mining in Pattern Recognition : 11th International Conference, MLDM 2015, Hamburg, Germany, July 20-21, 2015, Proceedings.
Springer International Publishing
ISBN 978-3-319-21023-0Full Text
(Other chapter contribution)
Reliability and Effectiveness of Cross-validation in Feature Selection,UEA Repository
Object-Neighbourhood based Clustering Ensemble Method,UEA Repository
A Graph based Methodology for Web Structure Mining: with a Case Study on the Webs of UK Universities,UEA Repository
Heuristic Ensemble of Filters for Reliable Feature Selection,Full Text UEA Repository
Retinal vessel segmentation using Gabor Filter and Textons,Full Text UEA Repository
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Key Research Interests
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
- 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)
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.
Deputy Director of Postgraduate Research
Director of MSc Computer Science
Admissions Officer for Overseas Applications