
Yuan WangAssociate ProfessorOffice: Neill 409Phone: (509) 335-3161Fax: (509) 335-1188Email: yuan.wang@wsu.edu |
Employment
- 2021, Associate Professor, Department of Mathematics and Statistics, Washington State University
- 2015 - 2021, Assistant Professor, Department of Mathematics and Statistics, Washington State University
- 2013 - 2015, Postdoctoral Fellow, Department of Biostatistics, The University of Texas MD Anderson Cancer Center
Education
- 2008 - 2013 Ph.D. in Statistics, Colorado State University
- 2004 - 2008 B.S. in Statistics, The University of Science and Technology of China
Research Interest
- Statistical learning of complex data objects including trees, curves and images
- Bayesian variable selection
- compressive sensing and system design
Selected Publication
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Y. Wang, J. S. Marron, L. A. Aydin, E. Bullitt and H. Wang (2012). A Nonparametric Regression Model with Tree-structured Response, Journal of the American Statistical Association, 107: 1272-1285.
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Y. Wang, H. Wang, and L. L. Scharf (2014). Optimum Compression of a Noisy Measurement for Transmission over a Noisy Channel, IEEE Transactions on Signal Processing, 62: 1279-1289.
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Y. Wang, H. Wang, and L. L. Scharf (2014). The Geometry of Fusion Inspired Channel Design, Signal Processing, 99: 136-146.
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Y. Wang, B. P. Hobbs, J. Hu, C. S. Ng, and K. A. Do (2015). Predictive Classification of Correlated Targets with Application to Detection of Metastatic Cancer using Functional CT Imaging, Biometrics, 71(3):792-802.
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Y. Wang, B. P. Hobbs, and C. S. Ng (2015). CT Perfusion Characteristics Identify Metastatic Sites in Liver, BioMed Research International, 120749 (invited).
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Z. Zhang, Y. Wang, E. K. P. Chong, and A. Pezeshki (2017). Subspace Selection for Projection Maximization with Matroid Constraints, IEEE Transactions on Signal Processing, 65: 1339-1351.
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I. Santamaria, L. Scharf, J. Via, H. Wang, Y. Wang (2017). Passive Detection of Correlated Subspace Signals in Two MIMO Channels, IEEE Transactions on Signal Processing, 65: 5266-528.
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Y. Wang, J. Hu, K. Do, and B. P. Hobbs (2019). An Efficient Nonparametric Estimate for Spatially Correlated Functional Data, Statistics in Bioscience, 11:162-183.
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L. Paxton, Y. Caog, K. Vixie, Y.Wang, C. S. Ng, B. P. Hobbs (2019), A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors, Journal of Abstract and Computational Mathematics, 4: 081-093.
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Y. Wang, J. Hu, C. S. Ng, and B. P. Hobbs (2020). A Functional Model for Classifying Metastatic Lesions Integrating Scans and Biomarkers, Statistical Methods in Medical Research, 29(1):137-150.
- STAT 360 Probability and Statistics (Fall 15, 16, 17, 18)
- STAT 370 Introductory Statistics for Engineers (Spring 16, Fall 19)
- STAT 423/523 Statistical Methods for Engineers and Scientists (Spring 17, 19, 20)
- MATH 583 Topic Class in Bayesian Analysis (Fall 16)
- STAT 574 Linear and Nonlinear Mixed Model (Fall 17)
- STAT 576 Bayesian Analysis (Fall 18)
- STAT 575 Theory of Multivariate Analysis (Fall 19)
- Yufeng Cao. Experiments in Medical Image Segmentation, Spring 2019, jointed with K. Vixie.
- Yuanhong Song. Modeling Spatial-Temporal Variability of LANDSAT-MODIS Fused NDVI for Crops in the Palouse Region, Summer 2019, joint with Z. Zhang.
- Hang Guo. Deep Learning for Lung Cancer Classification, Summer 2019.
- Syed Badruddoza. Classification with Sparse and Irregular Sampled Observations, Spring 2020.