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, 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 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
- Alanazi MSM, Jenkins K & 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)
- 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, Premare TDD, 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)
Conference Papers
- Belmekki Z, Li J, Jenkins K, Reuter P & Gomez Jauregui DA. (2022). An Empirical Evaluation of Generative Adversarial Nets in Synthesizing X-ray Chest Images
- Ouazzane K, Aigbodi M & Li J. (2013). Real life pilot solution with artificial intelligence for disabled computer users
- Li J. (2012). A Study on Noisy Typing Stream Analysis Using Machine Learning Approach
- Li J, Ouazzane K, Afzal M & Kazemian H. (2011). PATTERNS IDENTIFICATION FOR HITTING ADJACENT KEY ERRORS CORRECTION USING NEURAL NETWORK MODELS
- Ouazzane K, Li J & Kazemian HB. (2011). An Intelligent Keyboard Framework for Improving Disabled People Computer Accessibility
- Ouazzane K, Afzal M, Kazemian H & Li J. (2011). AN E-BUSINESS FRAMEWORK DESIGN USING ENHANCED WEB 2.0 TECHNOLOGY
- Li J, Ouazzane K, Jing Y, Kazemian H & Boyd R. (2009). Evolutionary Ranking on Multiple Word Correction Algorithms Using Neural Network Approach
- Li J, Ouazzane K, Kazemian H, Jing Y & Boyd R. (2009). Focused time-delay neural network modeling towards typing stream prediction
- Ouazzane K, Li J & Brouwer M. (2008). A hybrid framework towards the solution for people with disability effectively using computer keyboard
Books
- Li J. (2018). Foreign Aid, Urbanization and Green Cities In Huang Y & Pascual U (eds), Aid Effectiveness for Environmental Sustainability. Springer Singapore.
- Barker T & Crawford-Brown D. (2014). Decarbonising the World's Economy In Barker T & Crawford-Brown D (eds), Decarbonising the Global Economy: Assessing the Feasibility of Policies to Reduce Greenhouse Gas Emissions. IMPERIAL COLLEGE PRESS.