Research Assistant Professor
- ST516
- +852 2766 4283
- fyj026@gmail.com
- Machine Learning and Artificial Intelligence
ORCID ID
SCOPUS IDBiography
Dr Fu is very interested in interdisciplinary research that applies artificial intelligence, machine learning, deep learning, signal processing and multimedia computing to human-centered problems . His prior work has covered diverse fields ranging from fight detection, behaviour understanding, physiological signal measurement, mental stress monitoring to eye healthcare and firefighting engineering. He has presented his research at prestigious conferences and published in reputable journals including AAAI, ACMMM, COMPSAC, IJHCI, and FSJ. He has also been invited to serve as program committee member and reviewer for multiple renowned conferences and journals, such as CHI, ACMMM, and IJHCS.
His current focus is on AI systems using multimodal human-centered signals (e.g., physiological signals, gaze interaction, body movement, image/video signals, etc.) to infer users’ health problems, and eventually, ensure their health.
Research Interests
Research Output
- Wang, J., Fu, E. Y., Ngai, G., & Leong, H. V. (2021). Investigating differences in gaze and typing behavior across writing genres. International Journal of Human–Computer Interaction, 1-21.
- Fu, E. Y., Tam, W. C., Wang, J., Peacock, R., Reneke, P., Ngai, G., Leong, H. V., & Cleary, T. (2021). Predicting flashover occurrence using surrogate temperature data. In Proceedings of the AAAI Conference on Artificial Intelligence (vol. 35, no. 17, pp. 14785-14794).
- Fu, E. Y., Yang, Z., Leong, H. V., Ngai, G., Do, C. W., & Chan, L. (2020). Exploiting active learning in novel refractive error detection with smartphones. In Proceedings of the 28th ACM International Conference on Multimedia (pp. 2775-2783).
- Wang, J., Fu, E. Y., Ngai, G., Leong, H. V., & Huang, M. X. (2019). Detecting stress from mouse-gaze attraction. In Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (pp. 692-700).
- Fu, E. Y., Huang, M. X., Leong, H. V., & Ngai, G. (2018). Cross-species learning: A low-cost approach to learning human fight from animal fight. In Proceedings of the 26th ACM International Conference on Multimedia (pp. 320-327).
