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:
- 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
- Martin Schiemer
- Yuheng Wang
- Mario Moreno Rocha
- Yaxiong Lei
- Krzysztof Marianski
- Chloe Hequet
Selected publications
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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
DynamicRead: exploring robust gaze interaction methods for reading on handheld mobile devices under dynamic conditions
Lei, Y., Wang, Y., Caslin, T., Wisowaty, A., Zhu, X., Khamis, M. & Ye, J., 18 May 2023, In: Proceedings of the ACM on Human-Computer Interaction. 7, ETRA, 17 p., 158.Research output: Contribution to journal › Article › peer-review
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Open access
Online continual learning for human activity recognition
Schiemer, M., Fang, L., Dobson, S. & Ye, J., 8 Jul 2023, In: Pervasive and Mobile Computing. 93, 20 p., 101817.Research output: Contribution to journal › Article › peer-review
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An exploratory study on academic reading contexts, technology, and strategies
Moreno Rocha, M. A., Nacenta, M. A. & Ye, J., 13 Jan 2022. 10 p.Research output: Contribution to conference › Paper › peer-review
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Open access
Automated call detection for acoustic surveys with structured calls of varying length
Wang, Y., Ye, J. & Borchers, D. L., 1 Jul 2022, In: Methods in Ecology and Evolution. 13, 7, p. 1552-1567 16 p.Research output: Contribution to journal › Article › peer-review
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Open access
VisuaLizations As Intermediate Representations (VLAIR): an approach for applying deep learning-based computer vision to non-image-based data
Jiang, A., Nacenta, M. A. & Ye, J., 24 Sept 2022, In: Visual Informatics. 6, 3, p. 35-50 16 p.Research output: Contribution to journal › Article › peer-review
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Open access
Bayesian inference federated learning for heart rate prediction
Fang, L., Liu, X., Su, X., Ye, J., Dobson, S., Hui, P. & Tarkoma, S., 2021, Wireless Mobile Communication and Healthcare: 9th EAI International Conference, MobiHealth 2020, Virtual Event, November 19, 2020, Proceedings. Ye, J., O'Grady, M. J., Civitarese, G. & Yordanova, K. (eds.). Cham: Springer, p. 116-130 15 p. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; vol. 362 LNICST).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Open access
Collaborative activity recognition with heterogeneous activity sets and privacy preferences
Civitarese, G., Ye, J., Zampatti, M. & Bettini, C., 23 Nov 2021, In: Journal of Ambient Intelligence and Smart Environments. 13, 6, p. 433-452 20 p.Research output: Contribution to journal › Article › peer-review
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Open access
Continual activity recognition with generative adversarial networks
Ye, J., Nakwijit, P., Schiemer, M., Jha, S. & Zambonelli, F., 27 Mar 2021, In: ACM Transactions on Internet of Things. 2, 2, p. 1-25 25 p., 9.Research output: Contribution to journal › Article › peer-review
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Open access
Continual learning in sensor-based human activity recognition: an empirical benchmark analysis
Jha, S., Schiemer, M., Zambonelli, F. & Ye, J., 16 Apr 2021, (E-pub ahead of print) In: Information Sciences. In Press, p. 1-35 35 p.Research output: Contribution to journal › Article › peer-review