Dr Jing Lu joined the University of Winchester in August 2016 as a Senior Lecturer in Data Analytics. She is a research-active academic in data science and business analytics with extensive experience of teaching in higher education previously as an Associate Professor at Southampton Solent University and in China.
Jing was awarded a PhD from the Department of Computing and Information Systems at the University of Bedfordshire in 2006 and became a Fellow of the HE Academy in 2009. Her research activities have extended across computer applications and information systems through data mining and visualisation to business analytics and knowledge discovery, including modelling of real-world problems using digital technologies.
Jing’s research output comprises over 30 peer-reviewed publications in applied computing, where she has provided full submissions both for RAE 2008 and REF 2014. Her published research has featured in international journals covering business intelligence, data mining, modelling and management, and data warehousing as well as international conferences on data science, machine learning, medical informatics, data mining and knowledge discovery.
Jing's experience from research and knowledge exchange has helped to inform her teaching in various ways through supervision of projects and dissertations as well as curriculum development, e.g. for BSc Digital and Technology Solutions (Data Analytics) and BSc Data Science.
Higher Education Teaching Qualification
Higher Education Academy Fellowship (FHEA)
Areas of expertise
- Data Mining, Modelling and Management
- Information Systems Applications
- Knowledge Discovery in Databases
- Business Analytics and Management Science
Journal Publications / Book Chapters
- Lu, J. (2019) Data analytics research-informed teaching in a digital technologies curriculum. INFORMS Transactions on Education. In Press.
- Lu, J. (2019) Data science in the business environment: Skills analytics for curriculum development. In: G. Nicosia et al. (Eds.) Machine Learning, Optimization and Data Science. Lecture Notes in Computer Science, Vol. 11331, Springer International Publishing AG, pp.116-128. ISBN 978-3-030-13708-3
- Lu, J. (2018) A data-driven framework for business analytics in the context of big data. In: A. Benczr et al. (Eds.) New Trends in Databases and Information Systems. Communications in Computer and Information Science, Vol. 909, Springer Cham, pp.339-351. ISBN 978-3-030-00062-2
- Lu, J., Hales, A., Rew, D. (2017) Modelling of cancer patient records: A structured approach to data mining and visual analytics. In: M. Bursa et al. (Eds.) Information Technology in Bio- and Medical Informatics. Lecture Notes in Computer Science, Vol. 10443, Springer International Publishing AG, pp.30-51. ISBN 978-3-319-64264-2
- Lu, J., Wang, C.Q., Keech, M. (2017) A novel approach to knowledge discovery and representation in biological databases. International Journal of Bioinformatics Research and Applications Vol. 13, No. 4, pp.352-375
- Lu, J., Keech, M., Chen, W.R., Wang, C.Q. (2013) Concurrent sequential patterns mining and frequent partial orders modelling. International Journal of Business Intelligence and Data Mining Vol. 8, No. 2, pp.132-154
- Chen, W.R., Lu, J., Keech, M. (2010) Discovering exclusive patterns in frequent sequences. International Journal of Data Mining, Modelling and Management Vol. 2, No. 3, pp.252-267
- Lu, J., Chen, W.R., Keech, M. (2010) Graph-based modelling of concurrent sequential patterns. International Journal of Data Warehousing and Mining Vol. 6, No. 2, pp.41-58
International Conference Proceedings
- Lu, J., Hales, A., Rew, D., Keech, M. (2016) Timeline and episode-structured clinical data: Pre-processing for data mining and analytics. Proceedings of the 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki Workshop on Health Data Management and Mining, pp.64-67. ISBN 978-1-5090-2109-3
- Mills-Mullett, A., Lu, J. (2015) Mining fuzzy time-interval patterns in clinical databases. Proceedings of the 35th International Conference on AI, Cambridge; Proceedings AI-2015, Springer International Publishing Switzerland, pp.399-404. ISBN 978-3-319-25030-4
- Lu, J., Hales, A., Rew, D., Keech, M., Fröhlingsdorf, C., Mills-Mullett, A., Wette, C. (2015) Data mining techniques in health informatics: A case study from breast cancer research. Proceedings of the 6th International Conference on IT in Bio- and Medical Informatics, Valencia; LNCS 9267, Springer International Publishing Switzerland, pp.56-70. ISBN 978-3-319-22740-5
- Lu, J., Keech, M. (2015) Emerging technologies for health data analytics research: A conceptual architecture. 2nd International Workshop on NoSQL Databases, Valencia; Proceedings of DEXA 2015, IEEE Computer Society, pp.225-229. ISBN 978-1-4673-7581-8
- Lu, J., Keech, M., Wang, C.Q. (2014) Protein data modelling for concurrent sequential patterns. 5th International Workshop on Biological Knowledge Discovery and Data Mining, BIOKDD 2014, Munich; Proceedings of DEXA 2014, IEEE Computer Society, pp.5-9. ISBN 978-1-4799-5721-7
- Wang, C.Q., Lu, J., Keech, M. (2014) Applications of concurrent sequential patterns in protein data mining. Proceedings of the 10th International Conference on Machine Learning and Data Mining, MLDM 2014, St. Petersburg; LNAI 8556, Springer International Publishing Switzerland, pp.243-257. ISBN 978-3-319-08978-2
- Lu, J., Keech, M., Wang, C.Q. (2013) Applications of concurrent access patterns in web usage mining. Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013, Prague; LNCS 8057, Springer-Verlag Berlin Heidelberg, pp.339-348. ISBN 978-3-642-40130-5