Research

Methodological Interests:

• Model Selection: Bayesian methods for model selection in linear models and graphical models.
• Bayesian Statistics: Computational and Inferential techniques from a Bayesian perspective.
• Multivariate Statistics and Functional Analysis.
• Clustering: Model-based Clustering; Integrative Clustering.
• Time series and Spectral Analysis.

Application Interests:

• Neuroimaging: Statistical modelling and inferences on Electroencephalography (EEG).

Software:

Multi-level Integrative Clustering (R package, JASA publication): on Github

Hierarchical Functional Model (R package, preprint): on Github

Selective Publications (Google Scholar):

1. Li, Qian, et al. "Inferring Brain Signals Synchronicity From a Sample of EEG Readings." Journal of the American Statistical Association 114.527 (2019): 991-1001.

2. Tajbakhsh, N., Jeyaseelan, L., Li, Q., Chiang, J. N., Wu, Z., & Ding, X.. Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation. Medical Image Analysis (2020), 101693.

3. Li, Qian, et al. "Region-Referenced Spectral Power Dynamics of EEG Signals: A Hierarchical Modeling Approach." arXiv preprint arXiv:1811.05566 (2018).