Shanshan Chen
Statistical Signal Processing, Wearable Sensing & Digital Health
Research · Software · Publications · Teaching · Notes
I’m an Associate Professor of Biostatistics at Virginia Commonwealth University. My work focuses on developing statistical methods and software for data collected from wearable devices, ambient sensors, and real-time monitoring systems, with primary applications in physical activity, sleep, energy metabolism, and behavioral health, among other areas. I am particularly interested in translating high-frequency time-series data into accessible, interpretable, and reproducible measures that advance clinical and public health research.
Education
Ph.D, Electrical Engineering, University of Virginia – 2013
Contact
schen3 at vcu dot edu
Research Areas
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Wearable and real-time sensor analytics
- Methods for processing data from accelerometers, inertial sensors, and ambient monitoring systems
- Validation and evaluation of algorithms for wearable-derived measures
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Time-series segmentation and change-point detection
- Methods for detecting structural changes in behavioral and physiolgoical time series
- Models capturing multi-state and transition dynamics
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Bayesian hierarchical and state-space modeling
- Latent-state modeling for intensive longitudinal data
- Uncertainty quantification
- Information integration of self-reported survey or ecological momentary assessment (EMA) data
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Machine learning and model evaluation
- Unsupervised learning methods with emphasis on interpretability and generalizability
- Fair and transparent evaluation and monitoring of predictive models
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Reproducible data workflows and research software
- Open-source R packages and Shiny applications for reproducible sensor data analytics
- Tools for automating clinical data workflows