Overview
Recent research interests are in generative models, tree-based models and methods, nonparametric methods, high-dimensional inference, scalable inference, Bayesian modeling, statistical computation and applied statistics. Tackling statistical and computational challenges in analyzing big data. Go to my website at lm186.github.io for the most up-to-date information.
Current Appointments & Affiliations
Professor of Statistical Science
·
2023 - Present
Statistical Science,
Trinity College of Arts & Sciences
Professor in Biostatistics and Bioinformatics
·
2023 - Present
Biostatistics & Bioinformatics,
Basic Science Departments
Recent Publications
Efficient in-situ image and video compression through probabilistic image representation
Journal Article Signal Processing · February 1, 2024 Fast and effective image compression for multi-dimensional images has become increasingly important for efficient storage and transfer of massive amounts of high-resolution images and videos. In this paper, we present an efficient in-situ method for multi- ... Full text CiteHidden Markov Pólya Trees for High-Dimensional Distributions
Journal Article Journal of the American Statistical Association · January 1, 2024 The Pólya tree (PT) process is a general-purpose Bayesian nonparametric model that has found wide application in a range of inference problems. It has a simple analytic form and the posterior computation boils down to beta-binomial conjugate updates along ... Full text CiteCoarsened Mixtures of Hierarchical Skew Normal Kernels for Flow and Mass Cytometry Analyses
Journal Article Bayesian Analysis · January 1, 2024 Cytometry is the standard multi-parameter assay for measuring single cell phenotype and functionality. It is commonly used for quantifying the relative frequencies of cell subsets in blood and disaggregated tissues. A typical analysis of cytometry data inv ... Full text CiteRecent Grants
NSF Engineering Research Center for Precision Microbiome Engineering (PreMiEr)
ResearchInvestigator · Awarded by National Science Foundation · 2022 - 2027Collaborative: Bayesian Residual Learning and Random Recursive Partitioning Methods for Gaussian Processes Modeling
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2022 - 2026Statistical modeling of cross-sample variation and learning of latent structures in microbiome sequencing data
ResearchPrincipal Investigator · Awarded by National Institute of General Medical Sciences · 2020 - 2025View All Grants
Education, Training & Certifications
Stanford University ·
2011
Ph.D.
The University of Chicago ·
2006
A.B.
The University of Chicago ·
2006
M.S.