Dr Dongjiao Ge

Department of Mathematical Sciences
Dr Dongjiao Ge



Dongjiao received her BS.c. and MS.c. in Applied Math from the College of Mathematics at Sichuan University, China, and obtained her Ph.D. in Machin Learning from the Department of Computer Science, University of Manchester, U.K. Before joining the University of Essex, she was a postdoctoral research associate (PDRA) working on the EPSRC project "Analytical Middleware for Informed Distribution Networks (AMIDiNe)" with Prof. David Wallom at the Oxford e-Research Center, Department of Engineering Science, University of Oxford, U.K. Her main research interests include computational intelligence, machine learning, real-time learning, and statistical learning.


  • Ph.D. University of Manchester, (2020)

  • MS.c. Sichuan University, (2015)

  • BS.c. Sichuan University, (2012)


University of Essex

  • Lecturer, Department of Mathematical Sciences, University of Essex (1/7/2021 - present)

Other academic

  • Postdoctoral Research Associate (PDRA), Department of Engineering Science, University of Oxford (16/3/2020 - 30/6/2021)

Research and professional activities

Research interests

Computational Intelligence

Fundamental and applied research related to Fuzzy Systems and Neural Fuzzy Networks. Students with Computer Science/ Math/ statistics backgrounds​ are welcome.

Open to supervise

Machine Learning

Exploring new machine learning theory and methods for streaming data and big data. Students with computer science/ mathematics/statistics background are welcome.

Open to supervise

Functional Data Analysis

Developing machine learning theory and learning methods for functional data. The research output is expected to be able to handle big data more efficiently. Students with math/ statistics/ computer science backgrounds are welcome.

Open to supervise

Teaching and supervision

Current teaching responsibilities

  • Network Analysis (MA214)

  • Databases and data processing with SQL (MA332)


Journal articles (5)

Ge, D. and Zeng, X-J., (2022). Functional Fuzzy System: A Nonlinear Regression Model and Its Learning Algorithm for Function-on-Function Regression. IEEE Transactions on Fuzzy Systems. 30 (4), 956-967

Hu, M., Ge, D., Telford, R., Stephen, B. and Wallom, DCH., (2021). Classification and characterization of intra-day load curves of PV and non-PV households using interpretable feature extraction and feature-based clustering. Sustainable Cities and Society. 75, 103380-103380

Ge, D. and Zeng, X-J., (2020). Learning data streams online — An evolving fuzzy system approach with self-learning/adaptive thresholds. Information Sciences. 507, 172-184

Ge, D. and Zeng, X-J., (2019). A Self-Evolving Fuzzy System Which Learns Dynamic Threshold Parameter by Itself. IEEE Transactions on Fuzzy Systems. 27 (8), 1625-1637

Ge, D. and Zeng, X-J., (2018). Learning evolving T–S fuzzy systems with both local and global accuracy – A local online optimization approach. Applied Soft Computing. 68, 795-810

Book chapters (1)

Ge, D. and Zeng, X-J., (2016). Modified Evolving Participatory Learning Algorithms for Takagi-Sugeno Fuzzy System Modelling from Streaming Data. In: Advances in Computational Intelligence Systems Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7–9, 2016, Lancaster, UK. Springer. 3319465619. 9783319465616

Conferences (1)

Zeng, X-J. and Ge, D., (2017). Learning evolving Mamdani fuzzy systems based on parameter optimization

+44 (0) 1206 876292


2.410, Colchester Campus