Scholars@Duke
Scott C. Schmidler

Scott C. Schmidler

Associate Professor of Statistical Science
Statistical Science
scott.schmidler@duke.edu
Box 90251, Department of Statistical Science, Durham, NC 27708-0251
212 Old Chem, Durham, NC 27708-0251
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Research Interests

Monte Carlo methods; high-dimensional sampling algorithms; Mixing times of Markov chains; MCMC; Sequential Monte Carlo; probabilistic graphical models; Bayesian computation; probabilistic Machine Learning; Computational complexity of statistical inference.

Computational biology; Protein structure and folding; computational immunology; computational biophysics; statistical physics; computational statistical mechanics; molecular evolution.

Selected Grants

Evolutionary dynamics of zoonotic malaria

ResearchCo Investigator · Awarded by National Institutes of Health · 2023 - 2027

DMS/NIGMS 1: Challenges in Stochastic Modeling and Computation for Sequential Vaccine Design

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2024 - 2027

Deep Topological Sampling of Protein Structures - non-competing renewal for Year 4

ResearchSignificant Contributor · Awarded by National Institutes of Health · 2017 - 2022

Bioinformatics and Computational Biology Training Program

Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2005 - 2021

EMSW21-RTG: Geometric, Topological and Statistical Methods for Analyzing Massive Datasets

Inst. Training Prgm or CMECo-Principal Investigator · Awarded by National Science Foundation · 2011 - 2018

Evolutionary dynamics of zoonotic malaria

ResearchCo Investigator · Awarded by National Institutes of Health · 2023 - 2027

DMS/NIGMS 1: Challenges in Stochastic Modeling and Computation for Sequential Vaccine Design

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2024 - 2027

Deep Topological Sampling of Protein Structures - non-competing renewal for Year 4

ResearchSignificant Contributor · Awarded by National Institutes of Health · 2017 - 2022

Bioinformatics and Computational Biology Training Program

Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2005 - 2021

EMSW21-RTG: Geometric, Topological and Statistical Methods for Analyzing Massive Datasets

Inst. Training Prgm or CMECo-Principal Investigator · Awarded by National Science Foundation · 2011 - 2018

Advances in Scalable Monte Carlo Algorithms for Bayesian Statistics

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2014 - 2017

Structural Biology and Biophysics Training Program

Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 1994 - 2015

Mechanistic Studies of Complex Protein Folding Reactions

ResearchCo Investigator · Awarded by National Institutes of Health · 2008 - 2013

Bayesian Analysis of Shapes and Curves with Applications in Bioinformatics

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2006 - 2007

Statistical Models of Biopolymer Sequence and Folding

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2002 - 2005