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November 29 - December 5, 2020

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Nov

Geosciences Seminar: Dr. Michele Cooke

Conference/Seminar

Dr. Cooke is from University of Massachusetts. Her presentation is titled "What can Tiny Faults Tell Us about Earthquakes?"

3:30 pm - 4:30 pm |
02
Dec

Hansen Seminar: Amy Rosenzweig

Lecture/Readings

Methane emissions, which are among the most potent greenhouse gases, are a critical concern because of their ability to absorb the sun’s heat and warm the Earth’s atmosphere. Bioinorganic chemist Amy Rosenzweig says methanotrophic bacteria, commonly found in soils, wetlands and marshes, use copper from the environment to convert harmful methane into useful energy and chemicals.

Rosenzweig, Weinberg Family Distinguished Professor of Life Sciences at Illinois’ Northwestern University, discusses this process as featured speaker for USU's 2020 R. Gaurth Hansen Seminar series, Wednesday Dec. 2. She presents “Biological Methane Oxidation” at 4 p.m. Mountain via Zoom. Hosted by USU’s Department of Chemistry and Biochemistry, the lecture is open to all. For Zoom access information, visit: https://chem.usu.edu/seminars/index

Rosenzweig is the 13th annual Hansen Seminar speaker. The seminar series honors the late R. Gaurth Hansen (1920-2002), a renowned USU professor, researcher and administrator.

4:00 pm - 5:00 pm |
02
Dec

USU Data Science Club: Machine Learning in Economics & Finance

Conference/Seminar

Join us as Huntsman School professor Dr. Pedram Jahangiry discusses applications of machine learning in economics and finance.

Follow this link for more details on how to attend: https://math.usu.edu/flyers/Data-Science-Club-Dec-2nd.pdf

4:30 pm - 5:30 pm | Online/Virtual |
04
Dec

Applied Mathematics Seminar: MCMC or: how I learned to stop worrying and love randomness

Conference/Seminar

Speaker: Luis Gordillo, Associate Professor, Department of Math & Statistics, USU
ZOOM ID: 945 1753 3441 PWD: USUAMS

Abstract: Markov Chain Monte Carlo (MCMC) is a useful computer-intensive tool that has received lots of attention. By using MCMC ideas it is possible to write algorithms for sampling from complicated target distributions. In this talk, aimed at undergraduate and graduate students, I will present the main ideas of MCMC and show examples of how the techniques can be used to solve some difficult problems, including the inference of parameters in stochastic epidemic models of the SIR type.

3:30 pm - 4:30 pm |
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