- University of Birmingham
- 19:06
(UTC) - https://orcid.org/0000-0002-6502-9934
- in/qianfu
- @mikeqfu
- @mikeqfu.bsky.social
🔬 Postdoctoral researcher specialising in data integration & analytics.
🌱 Developing and maintainingPyHelpers,PyDriosm andPyRCS.
🛠️ Solving real-world transport challenges with data-driven solutions.
📚 Exploring advanced techniques in data science.
I'm passionate about making data science tools more accessible to the transport research community—bridging the gap between complex methodologies and real-world applications. I'm also working to enhance open-source Python tools for transport data analysis, scalable computing and usability.
- Jiang, Y.,Fu, Q., Thomopoulos, N., Chen, J.L. (2025). Understanding the influence of past driving experience on electric vehicle purchase intention in China. Transport Policy, 270-282.https://doi.org/10.1016/j.tranpol.2024.11.025
- Fu, Q., Nicholson, G.L., Easton, J.M. (2024). Understanding data quality in a data-driven industry context: Insights from the fundamentals. Journal of Industrial Information Integration, 100729.https://doi.org/10.1016/j.jii.2024.100729
- Yu, Y.,Fu, Q., Zhang, D., Gu, Q. (2024). Understanding User Experience with Smart Home Products. Journal of Computer Information Systems, 1-23.https://doi.org/10.1080/08874417.2024.2408006
PinnedLoading
- network-rail-weather-rail-incident-prediction
network-rail-weather-rail-incident-prediction PublicA (prototype) model for prediction of weather-related rail incidents in Great Britain
- network-rail-track-fixity-layer
network-rail-track-fixity-layer PublicThis project develops a data mining tool for analysing and predicting track movements using asset data, environmental factors and track design knowledge to model key parameters and generate fixity …
Python
- smart-home-product-reviews-analysis
smart-home-product-reviews-analysis PublicUnderstanding user experience using text mining & analysis: A case study of Amazon.com reviews for smart-home products
Python
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