Matt Koslovsky

Matt Koslovsky is an Assistant Professor of Statistics at Colorado State University. He completed his PhD in Biostatistics at The University of Texas Health Science Center School of Public Health (UTHealth) in 2016 and served as a Post-Doctoral Research Associate at Rice University's Marina Vannucci lab from 2018-2020. Prior to joining CSU in 2020, he worked as a statistical consultant at Johnson Space Center's Biostatistics Lab.

• PhD, Biostatistics (2016), UTHealth School of Public Health
• Post-Doctoral Research Associate (2018-2020), Rice University
• Assistant Professor (2020-Present), Colorado State University

His research spans Bayesian methodology and its applications across diverse domains:

• Theory: Bayesian modeling, variable selection, graphical models, nonparametric Bayes
• Applications: Cancer prevention, mental health, microbiome analysis, space health, ecological momentary assessment

Recent publications demonstrate methodological advancements in:

• Bayesian variable selection for rare variants
• Integrated population modeling
• Compositional data analysis
• Continuous-time hidden Markov models
• mHealth data processing
• Microbiome mediation effects

Current advisees include:

• Hyungjoon Kim (PhD candidate)
• Brody Erlandson (PhD candidate)
• Suppapat Korsurat (PhD candidate)