Dr Yan Wen
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Postdoctoral Research Assistant
Research, development, and implementation of advanced computer vision and biometric algorithms tailored for in-vehicle border security and XR devices.
Office
Room 121Building location
Polly VacherAreas of interest
Computer Vision, Machine Learning, Network Engineering, Internet of Things
Teaching
- Guest Lecturer at University of York (Feb 2025 – Present)
- STEM Guest Speaker/Workshop Lecturer at Lincoln Bishop University (Dec 2023)
- Assistant Lecturer, Demonstrator at University of Lincoln (Dec 2019 – Jun 2023)
Research centres and groups
Computational Vision Group
Research projects
Dr. Yan Wen is an accomplished AI scientist specializing in computer vision, medical imaging, and real-time object tracking. He currently serves as a Post-Doctoral Research Assistant (PDRA) in Biometrics and Identity Management at the University of Reading, where he develops advanced identity verification and in-vehicle computer vision algorithms for the EU AutoBorder project. Previously, he led high-performance UAV tracking at Drone Defence by engineering innovative cascaded predictive models, delivered an Innovate UK-funded AI medical platform for kinematic analysis at the University of Lincoln, and advanced edge computing edge applications on at the University of York. Holding a PhD in Computer Science with publications in top-tier venues like ICCV and MIDL, Yan excels at bridging complex AI research—from small-object lesion analysis to real-time PTZ camera control—with robust commercial and clinical applications, bolstered by extensive multidisciplinary collaborations across the UK healthcare and academic sectors.
Background
- Research Trainee at University of York (Jun 2022 – Dec 2023, Feb 2025 – Present)
- Principal Computer Vision Scientist at Drone Defence (May 2025 – Apr 2026)
- Research Assistant at University of Lincoln (Jul 2019 – Aug 2020, Apr 2023 – Apr 2025)
- STEM Guest Speaker/Workshop Lecturer at Lincoln Bishop University (Dec 2023)
- Assistant Lecturer, Demonstrator at University of Lincoln (Dec 2019 – Jun 2023)
- International Student Ambassador at University of Lincoln (Feb 2022 – Apr 2023)
- Computer Technician at Moorfields Eye Hospital NHS Trust & University of Lincoln (May 2018 – Aug 2018)
Academic qualifications
- University of Lincoln Doctor of Philosophy, Computer Science · (Sep 2017 - Sep2022)
- University of Lincoln Bachelor of Science, Computer Science · (Sep 2016 - Jun 2017)
Websites/blogs
Selected publications
[1] Zhang, L. and Wen, Y., 2021. A transformer-based framework for automatic COVID19 diagnosis in chest CTs. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 513-518).
[2] Wen, Y., Zhang, L., Meng, X. and Ye, X., 2023. Rethinking the transfer learning for FCN based polyp segmentation in colonoscopy. IEEE Access, 11, pp.16183-16193.
[3] Wen, Y., Verma, T., Whitehead, J.P. and Lee, P., 2025. Empirical Validation of a Streamlined Three-Repetition Sit-to-Stand Protocol Using MAI Motion. Applied Sciences, 15(10), p.5688.
[4] Armstrong, K., Wen, Y., Zhang, L., Ye, X. and Lee, P., Novel Clinical Applications of Marker-less Motion Capture as a Low-cost Human Motion Analysis Method in the Detection and Treatment of Knee Osteoarthritis. J Arthritis, 2022, 11(1), 001-005.
[5] Armstrong, K., Zhang, L., Wen, Y., Willmott, A.P., Lee, P. and Ye, X., 2024. A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders. Frontiers in Digital Health, 6, p.1324511.
[6] Yu, S., Wen, Y., Horst, C., Ganeshan, B., Thomas, S.A., Zwiggelaar, R., Lee, R., Ye, X. and Blackledge, M., 2024. Predicting non-visible future tumour from baseline low dose CT using deep learned features. In Medical Imaging with Deep Learning. Medical Imaging with Deep Learning, 2024.