5.1 – Bayesian Analyses and MCMC (Dr. Steve Presse)

Lecture 5.1

Title: Tutorial — Basics of Bayesian Analysis and MCMC

Lecturer: Prof. Steve Presse

Lecturer Website: https://cbp.asu.edu/content/steve-presse-lab

Lecturer Email: spresse@asu.edu

Learning Objectives:

      • Learn what is meant by Bayesian Analyses and  Markov Chain Monte Carlo Algorithms

Dr. Steve Pressé went to McGill University as an undergrad where he studied chemistry. He later pursued his doctorate in chemical physics at Massachusetts Institute of Technology (MIT) under the direction of Professor Robert J. Silbey. As a postdoctoral fellow in Professor Ken A. Dill’s lab, his research focus shifted to biophysics and dynamical processes in particular. His lab now uses both theory and experiments to address fundamental questions relevant to molecular science. On the theory side, his group develops, adapts and uses the tools of inference, statistical physics and stochastic processes, broadly defined, to understand living systems from single molecules to whole cells. A special emphasis is placed on interpreting spectroscopy and imaging data. On the experimental side, Pressé’s group investigates the role of hydrodynamics on bacterial interactions.

Title: Basics of Bayesian Analysis and MCMC

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Suggested Reading or Key Publications:

Links to Relevant Software: 

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