Biography
I am a Reader in the School of Computer Science at the University of St Andrews. My research interests centre around adaptive pervasive systems, specialising in sensor-based human activity recognition, sensor fusion, context awareness, ontologies, and uncertainty reasoning. I have a PhD degree in computer science from University College Dublin, Ireland and a BSc and MSc degree from Wuhan University, China.
Teaching
Over the years, I have been teaching the following modules:
- CS3105 - Artificial Intelligence
- CS3301 - Component Technologies
- CS5014 - Machine Learning
I also supervise projects at a variety levels across our school, and research internships funded by the St Andrews Research Internship Scheme, Laidlaw Research Program, and other funding bodies.
Research areas
My research is to make best use of sensor data in understanding the environment and the people, and thus in making informed decisions. Unlike classical machine learning problems, sensor data analytics is significantly challenged by the complexity in real-world environments, the inherently imperfect nature of sensing technologies, constantly changing inhabitants’ behaviours, and the unpredictability of situations or events occurring in an environment. The state-of-the-art methodology that is cultivated from short-term lab or testbed experimentation, i.e., relying on well-annotated sensor data and assuming no change in the models, is no longer suitable for long-term, large-scale, real-world deployment.
My research goal is to take sensor data analytics to the next level, by both transforming the ways in which machine learning technologies are applied and by developing new, continual-learning frameworks that can support a wider range of applications with high impacts.
PhD supervision
- Weiye Li
- Zipei Li
Selected publications
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Open access
Continual learning in sensor-based human activity recognition with dynamic mixture of experts
Rahman, F., Schiemer, M., Rosales Sanabria, A. & Ye, J., 1 May 2025, In: Pervasive and Mobile Computing. 110, 18 p., 102044.Research output: Contribution to journal › Article › peer-review
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Open access
Hadamard domain training with integers for class incremental quantized learning
Schiemer, M., Schaefer, C. J., Horeni, M. J., Wang, Y. E., Ye, J. & Josh, S., 17 Feb 2025, Proceedings of The 3rd conference on lifelong learning agents. Lomonaco, V., Melacci, S., Tuytelaars, T., Chandar, S. & Pascanu, R. (eds.). PMLR, p. 198-220 (Proceedings of machine learning research; vol. 274).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Identity deepfake threats to biometric authentication systems: public and expert perspectives
He, S., Lei, Y., Zhang, Z., Sun, Y., Li, S., Zhang, C. & Ye, J., 7 Jun 2025, arXiv, p. 1-21, 21 p.Research output: Working paper › Preprint
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MAC-Gaze: motion-aware continual calibration for mobile gaze tracking
Lei, Y., Zhao, M., Wang, Y., He, S., Sugano, Y., Khamis, M. & Ye, J., 28 May 2025, arXiv, p. 1-24, 24 p.Research output: Working paper › Preprint
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Open access
Opportunistic dynamic architecture for class-incremental learning
Rahman, F., Rosales Sanabria, A. & Ye, J., 31 Mar 2025, In: IEEE Access. 13, p. 1-11 11 p., 10946184.Research output: Contribution to journal › Review article › peer-review
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Privacy perspectives and practices of Chinese smart home product teams
He, S., Lei, Y., Zhan, X., Zhang, C., Ye, J., Abu-Salma, R. & Such, J., 6 Jun 2025, arXiv, p. 1-19, 19 p.Research output: Working paper › Preprint
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Quantifying the impact of motion on 2D gaze estimation in real-world mobile interactions
Lei, Y., Wang, Y., Buchanan, F., Zhao, M., Sugano, Y., He, S., Khamis, M. & Ye, J., 14 Feb 2025, (Submitted) arXiv, p. 1-27, 27 p.Research output: Working paper › Preprint
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Open access
An end-to-end review of gaze estimation and its interactive applications on handheld mobile devices
Lei, Y., He, S., Khamis, M. & Ye, J., 1 Feb 2024, In: ACM Computing Surveys. 56, 2, 38 p., 34.Research output: Contribution to journal › Article › peer-review
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Open access
SelfVis: self-supervised learning for human activity recognition based on area charts
Jiang, A. & Ye, J., 3 May 2024, (E-pub ahead of print) In: IEEE Transactions on Emerging Topics in Computing. Early Access, p. 1-12 12 p.Research output: Contribution to journal › Article › peer-review
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Open access
Towards automated animal density estimation with acoustic spatial capture-recapture
Wang, Y., Ye, J., Li, X. & Borchers, D. L., Sept 2024, In: Biometrics. 80, 3, 12 p., ujae081.Research output: Contribution to journal › Article › peer-review