Contact Information:
445C West Hall Department of Statistics University of Michigan keanming @ umich.edu |
I am currently an assistant professor at the Department of Statistics at University of Michigan. Previously, I was an assistant professor at the School of Statistics at University of Minnesota, and a postdoctoral research associate supervised by Han Liu and Tong Zhang. I joined the Department of Biostatistics at University of Washington in 2011 for my PhD degree, under the supervision of Daniela Witten.
I am an applied statistician working on statistical machine learning methods for analyzing complex biomedical data sets. I develop multivariate statistical methods such as probabilistic graphical models, cluster analysis, discriminant analysis, and dimension reduction to uncover patterns from massive data set. Recently, I also work on topics related to robust statistics, non-convex optimization, and data integration from multiple sources. . |
Recent Papers: [Google scholar]
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks [arXiv] [link]
Tan KM, Lu J, Zhang T and Liu. H (2020)
Biometrics, in press
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv] [link]
Han L, Tan KM, Yang T, and Zhang T (2020)
The Annals of Statistics, 48(3):1770--1788.
Transformation of Speech Sequences in Human Sensorimotor Circuits [link]
Musch K, Himberger K, Tan KM, Valiante TA and Honey CJ (2020)
Proceedings of the National Academy of Sciences, 117(6):3203--3213.
Layer-wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models [link]
Tan KM, Lu J, Zhang T and Liu. H (2019)
Journal of Machine Learning Research, 20(119):1-38
Propagation of Information along the Cortical Hierarchy as a Function of Attention while
Reading and Listening to Stories [link]
Regev M, Simony E, Lee K, Tan KM, Chen J and Hasson U (2019)
Cerebral Cortex, 29(10):4017--4034.
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow [link] [arXiv] [R package rifle]
Tan KM, Wang Z, Liu H and Zhang T (2018)
Journal of the Royal Statistical Society: Series B, 80(5):1057-1086
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks [arXiv] [link]
Tan KM, Lu J, Zhang T and Liu. H (2020)
Biometrics, in press
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv] [link]
Han L, Tan KM, Yang T, and Zhang T (2020)
The Annals of Statistics, 48(3):1770--1788.
Transformation of Speech Sequences in Human Sensorimotor Circuits [link]
Musch K, Himberger K, Tan KM, Valiante TA and Honey CJ (2020)
Proceedings of the National Academy of Sciences, 117(6):3203--3213.
Layer-wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models [link]
Tan KM, Lu J, Zhang T and Liu. H (2019)
Journal of Machine Learning Research, 20(119):1-38
Propagation of Information along the Cortical Hierarchy as a Function of Attention while
Reading and Listening to Stories [link]
Regev M, Simony E, Lee K, Tan KM, Chen J and Hasson U (2019)
Cerebral Cortex, 29(10):4017--4034.
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow [link] [arXiv] [R package rifle]
Tan KM, Wang Z, Liu H and Zhang T (2018)
Journal of the Royal Statistical Society: Series B, 80(5):1057-1086