Contact Dr Jun Li
- Tel: +44 (0) 1234 754920
- Email: Jun.Li@cranfield.ac.uk
- ORCID
Background
Dr Jun Li has a BSc, MSc and PhD in Computer Science, Software Engineering and Neural Networks respectively, obtained from QingDao University and LondonMet University. Before joining Cranfield University, Dr Jun Li taught at University of Wolverhampton and LondonMet University for five years, and also worked as a Research Associate at University of Cambridge and University of Oxford for six years. His teaching and research expertise are in the areas of Data Analytics, Machine Learning, Deep Learning, Computer Science and Mathematical Modelling applied to various domains.
Current activities
Dr Jun Li is a lecturer in Mathematics and Computer Science at Centre for Computational Engineering Sciences, Cranfield University. He specializes in Machine Learning, High Performance Computing and Mathematical Modelling with topics such as large-scale simulations of Neural Networks based on integrated Neuroscience and Deep Learning, automatic aircraft engine borescope inspection defect detection using Deep Learning and computer vision, Neural Network language modelling with noises, transport flow analysis using complex networks, urban agglomeration formation modeling and imbalanced economy recovery modeling. Currently he teaches and supervises MSc and PhD students in Artificial Intelligence, Machine Learning and Big Data, and Software Engineering - for example, statistical modeling using Big Data techniques in the finance domain by leveraging the Alpha Vantage Open Stock API.
For pursuing PhD study and supervision in the areas listed above, one may refer to the university's Research Opportunities (found on top of the personal page) web page for procedures.
Publications
Articles In Journals
- Schaller T, Li J & Jenkins KW. (2025). A data-driven approach for automatic aircraft engine borescope inspection defect detection using computer vision and deep learning. Journal of Experimental and Theoretical Analyses, 3(1)
- Alanazi MSM, Jenkins KW & Li J. (2024). Predicting passengers’ feedback rate for airport service quality. Transportation Research Interdisciplinary Perspectives, 24
- Alanazi MSM, Li J & Jenkins KW. (2024). Multiclass sentiment prediction of airport service online reviews using aspect-based sentimental analysis and machine learning. Mathematics, 12(5)
- Alanazi MSM, Li J & Jenkins KW. (2024). Evaluating Airport Service Quality Based on the Statistical and Predictive Analysis of Skytrax Passenger Reviews. Applied Sciences, 14(20)
- Upadhyay A, Li J, King S & Addepalli S. (2023). A deep-learning-based approach for aircraft engine defect detection. Machines, 11(2)
- Xu Z, Maria A, Chelli K, De Premare TD, Bilbao X, .... (2023). Vortex and core detection using computer vision and machine learning methods. European Journal of Computational Mechanics, 32(5)
- Ouazzane K, Polykarpou T, Patel Y & Li J. (2022). An Integrated Machine Learning Framework for Fraud Detection. International Journal of Information Security and Privacy, 16(1)
- Fangqu N & Jun L. (2019). Visualizing the intercity highway network in Mainland China. Environment and Planning A: Economy and Space, 51(6)
- Niu F & Li J. (2019). An activity-based integrated land-use transport model for urban spatial distribution simulation. Environment and Planning B: Urban Analytics and City Science, 46(1)
- Niu F & Li J. (2018). Visualizing the intercity railway network in Mainland China. Environment and Planning A: Economy and Space, 50(5)
- Niu F & Li J. (2018). Modeling the population and industry distribution impacts of urban land use policies in Beijing. Land Use Policy, 70
- Li J, Crawford‐Brown D, Syddall M & Guan D. (2013). Modeling Imbalanced Economic Recovery Following a Natural Disaster Using Input‐Output Analysis. Risk Analysis, 33(10)
- Crawford-Brown D, Syddall M, Guan D, Hall J, Li J, .... (2013). Vulnerability of London’s Economy to Climate Change: Sensitivity to Production Loss. Journal of Environmental Protection, 04(06)
- Ouazzane K, Aigbodi M, Mitchell D, Vassilev V & Li J. (2013). An Innovative Custom Cyber Security Solution for Protecting Enterprises and Corporates’ Assets. International Journal of E-Entrepreneurship and Innovation, 4(3)
- Li J, Ouazzane K, Kazemian HB & Afzal MS. (2013). Neural Network Approaches for Noisy Language Modeling. IEEE Transactions on Neural Networks and Learning Systems, 24(11)
- Ouazzane K, Li J, Kazemian HB, Jing Y & Boyd R. (2012). An Artificial Intelligence-based language modeling framework. Expert Systems with Applications, 39(5)
- Li J, Ouazzane K, Kazemian H, Jing Y & Boyd R. (2011). A neural network based solution for automatic typing errors correction. Neural Computing and Applications, 20(6)