معرفی
Dr Siyuan Chen is a Lecturer at the School of Electrical Engineering and Telecommunications, UNSW Sydney. Her research focuses on physiological computing, particularly eye activity analysis for mental state recognition using wearable technology. She has contributed to signal processing and machine learning methodologies for non-invasive cognitive load and task transition detection.
- Ph.D. in Electrical Engineering (UNSW Sydney)
- M.E. in Microelectronics (RMIT University)
- Research Intern, NII Tokyo
- Research Fellow, University of Melbourne
- Research Visitor, INRIA France
Chen's research investigates eye behavior through infrared video datasets and multimodal sensor signals. Her work addresses physiological computing for applications in human-computer interaction, wearable mental state analysis, and biomedical signal processing. Key contributions include the IREye4Task dataset and novel methods for blink-saccade synchronization and pupillary response analysis.
Recent publications demonstrate trends in wearable eye tracking using acoustic sensors, low-power facial expression tracking, and event-based task transition detection. Her work spans both journal and conference venues including IEEE Transactions, ACM, and INTERSPEECH.
- NICTA Postgraduate Scholarship (2011-2013)
- Commercialization Training Scheme Scholarship (2012)
- Australia Endeavor Fellowship (2015)
- $711K US Army grant for wearable behavioral signal modeling (2019)
Chen contributes to teaching in electronics, signal processing, and engineering ethics, covering courses from first-year design to postgraduate leadership modules. She serves as a topic editor for Frontiers in Computer Science special issues.
