Jiang Gui, PhD
Title(s)
Professor of Biomedical Data Science
Professor of The Dartmouth Institute
Professor of Community and Family Medicine
Department(s)
Biomedical Data Science
The Dartmouth Institute
Community and Family Medicine
Education
2000-2005 University of California, Davis
Ph.D. in Statistics
Dissertation: Regularized Estimation in the High-Dimension and Low-Sample Size Settings, With Applications to Genomic Data
1996-2000 Peking University, P.R. China
B.S. in Statistics
Programs
The Dartmouth Institute for Health Policy and Clinical Practice
Contact Information
HB 7927
Lebanon NH 03756
Office: 603-646-5476
Email: jiang.gui@dartmouth.edu
Professional Interests
Dr. Gui's main interest lies in development and application of statistical methods for high-dimensional data (i.e. Microarray, SNP array and Proteomics data). His current research focuses on FDR control, penalized regression and dimension reduction methods.
Courses Taught
Small group leader, DMS Epidemiology and Biostatistics.
Timescale of FLASH Sparing Effect Determined by Varying Temporal Split of Dose Delivery in Mice. Integration of elemental imaging and spatial transcriptomic profiling for proof-of-concept metals-based pathway analysis of colon tumor microenvironment. Maternal Diet Quality in Pregnancy and Human Milk Extracellular Vesicle and Particle microRNA. Blood Pressure and Late Pregnancy Circulating miRNAs in the MADRES Study. Altered auditory brainstem responses are post-acute sequela of SARS-CoV-2 (PASC). Prenatal per- and polyfluoroalkyl substances and blood pressure trajectories in the New Hampshire Birth Cohort Study. Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population. Maternal diet quality and circulating extracellular vesicle and particle miRNA during pregnancy. Transcriptome-wide association study identifies genes associated with bladder cancer risk. Investigating the Differential Impact of Psychosocial Factors by Patient Characteristics and Demographics on Veteran Suicide Risk Through Machine Learning Extraction of Cross-Modal Interactions. |
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