- Ph.D., Statistics, Texas A&M University
- B.S, Mechanical Engineering, Tianjin University
- machine learning
- survival analysis
- image analysis
Yanqing Wang is an assistant professor in the Institute for Insight at the J. Mack Robinson College of Business. Before joining Robinson, Yanqing got her PhD in statistics from Texas A & M University and received a postdoc training at Fred Hutchison Cancer Research Center in Washington State.
Yanqing’s research interests lie in the investigation of complex and high dimensional "big data" problems, specifically at the intersection of machine learning, survival analysis and image analysis. In particular, Yanqing’s research focuses on three areas: learning-based methods for individualized treatment rules, model selection principles for misspeciﬁed models in longitudinal analysis, and statistical analysis for error assessment and prediction in image matching.
Yanqing teaches IFI8410 (Programming for Business) and IFI8420 (Business Machine Learning) for AI certificate students, and MBA 8045 (Analytic Experience)for MBA students, and MSA8600 (Deep Learning) for MSA students.
- Wang, Y., Zhao, Y. and Zheng Y. (2020) Learning-based Biomarker-assisted Rules for Optimized Clinical Benefit under a Risk-constraint. Biometrics,76, 853-862.
- Ma, S., Ma, Y.,Wang, Y., Kravitz, E. and Carroll, R. J. (2017) A Semiparametric Single-Index Risk Score Across Populations. Journal of the American Statistical Association,112, 1648-1662.
- Wang, Y., Wang, S. and Carroll, R. J. (2015) The Direct Integral Method for Confidence Intervals for the Ratio of Two Location Parameters. Biometrics, 71, 704-713.
- Wang, Y., Sutton, M., Ke, X., Schreier, H., Reu, P. and Miller, T. (2011) On Error Assessment in Stereo-based Deformation
Measurements, Part I: Theoretical Developments for Quantitative Estimates. Experimental Mechanics, 51, 405--422.
- Ke, X., Schreier, H., Sutton, M. and Wang, Y. (2011) Error Assessment in Stereo-based Deformation Measurements,
Part II: Experimental Validation of Uncertainty and Bias Estimates. Experimental Mechanics, 51, 423--441.
- Ning, J., Braxton, V., Wang, Y., Sutton, M., Wang, Y. and Lessner, S. (2011) Speckle Patterning of Soft Tissues for Strain Field Measurement Using Digital Image Correlation: Preliminary Quality Assessment of Patterns. Microscopy and Microanalysis, 17, 81--90.
- Wang, Y., Sutton, M., Bruck H. and Schreier, H. (2009) Quantitative Error Assessment in Pattern Matching: Effects of Intensity Pattern Noise, Interpolation, Subset Size and Image Contrast on Motion Measurements. Journal of Strain, 45, 160--178.
- Wang, Y., Sutton, M., Reu, P. and Miller, T. Image Matching Error Assessment in Digital Image
Correlation, Proceedings of the 2009 SEM Annual Conference.
- Reu, P., Sutton, M., Wang, Y., Miller, T. Uncertainty quantification for digital image correlation. Proceedings of the 2009 SEM Annual Conference.