# Probability: Difference between revisions

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== Tenured and tenure-track faculty == | == Tenured and tenure-track faculty == | ||

[ | [https://www.math.wisc.edu/~anderson/ David Anderson] (Duke, 2005) applied probability, numerical methods, mathematical biology. | ||

[ | [https://hanbaeklyu.com/ Hanbaek Lyu] (Ohio State, 2018) discrete probability, dynamical systems, networks, optimization, machine learning | ||

[ | [https://www.math.wisc.edu/~roch/ Sebastien Roch] (UC Berkeley, 2007) applied discrete probability, mathematical and computational biology, networks. | ||

[ | [https://www.math.wisc.edu/~seppalai/ Timo Seppäläinen] (Minnesota, 1991) motion in a random medium, random growth models, interacting particle systems, large deviation theory. | ||

[ | [https://math.wisc.edu/staff/shcherbyna-tatiana/ Tatyana Shcherbyna] (Kharkiv, 2012) mathematical physics, random matrices | ||

[ | [https://www.math.wisc.edu/~hshen3/ Hao Shen] (Princeton, 2013) stochastic partial differential equations, mathematical physics, integrable probability | ||

[https://www.math.wisc.edu/~valko/ Benedek Valko] (Budapest, 2004) interacting particle systems, random matrices. | |||

[ | |||

== Emeriti == | == Emeriti == | ||

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Peter Ney (Columbia, 1961) | Peter Ney (Columbia, 1961) | ||

== Postdocs == | |||

[https://www.ewbates.com/ Erik Bates] (Stanford, 2019) | |||

David Keating (UC Berkeley, 2021) | |||

David Clancy (UWashington, 2022) | |||

== Graduate students == | == Graduate students == | ||

Max Bacharach | |||

[ | [https://sites.google.com/wisc.edu/evan-sorensen Evan Sorensen] | ||

Yu Sun | |||

Jiaming Xu | |||

Shuqi Yu | |||

== [[Probability Seminar]] == | |||

Thursdays at 2:30pm, VV901 | |||

[https://groups.google.com/a/g-groups.wisc.edu/forum/#!forum/probsem General email list] | |||

[https://groups.google.com/a/g-groups.wisc.edu/forum/#!forum/lunchwithprobsemspeaker Email list for lunch/dinner with a speaker] | |||

==[[Graduate student reading seminar]]== | ==[[Graduate student reading seminar]]== | ||

[https://groups.google.com/a/g-groups.wisc.edu/forum/#!forum/grad_prob_seminar Email list] | |||

Tuesdays, 2: | Tuesdays, 2:30pm, 901 Van Vleck | ||

== [[Probability group timetable]]== | == [[Probability group timetable]]== | ||

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''' | '''2022 Fall''' | ||

Math/Stat 733 Theory of Probability I | |||

Math/Stat 735 Stochastic Analysis | |||

Math/ECE/Stat 888 Topics in Mathematical Data Science | |||

Math 717 Stochastic Computational Methods | |||

'''2023 Spring''' | |||

Math/Stat 734 Theory of Probability II | |||

Math 833 Topics in Probability: Stochastic Partial Differential Equations | |||

Math/ECE/Stat 888 Topics in Mathematical Data Science |

## Revision as of 19:29, 22 August 2022

**Probability at UW-Madison**

## Tenured and tenure-track faculty

David Anderson (Duke, 2005) applied probability, numerical methods, mathematical biology.

Hanbaek Lyu (Ohio State, 2018) discrete probability, dynamical systems, networks, optimization, machine learning

Sebastien Roch (UC Berkeley, 2007) applied discrete probability, mathematical and computational biology, networks.

Timo Seppäläinen (Minnesota, 1991) motion in a random medium, random growth models, interacting particle systems, large deviation theory.

Tatyana Shcherbyna (Kharkiv, 2012) mathematical physics, random matrices

Hao Shen (Princeton, 2013) stochastic partial differential equations, mathematical physics, integrable probability

Benedek Valko (Budapest, 2004) interacting particle systems, random matrices.

## Emeriti

David Griffeath (Cornell, 1976)

Jim Kuelbs (Minnesota, 1965)

Tom Kurtz (Stanford, 1967)

Peter Ney (Columbia, 1961)

## Postdocs

Erik Bates (Stanford, 2019)

David Keating (UC Berkeley, 2021)

David Clancy (UWashington, 2022)

## Graduate students

Max Bacharach

Yu Sun

Jiaming Xu

Shuqi Yu

## Probability Seminar

Thursdays at 2:30pm, VV901

Email list for lunch/dinner with a speaker

## Graduate student reading seminar

Tuesdays, 2:30pm, 901 Van Vleck

## Probability group timetable

## Undergraduate courses in probability

## Graduate Courses in Probability

**2022 Fall**

Math/Stat 733 Theory of Probability I

Math/Stat 735 Stochastic Analysis

Math/ECE/Stat 888 Topics in Mathematical Data Science

Math 717 Stochastic Computational Methods

**2023 Spring**

Math/Stat 734 Theory of Probability II

Math 833 Topics in Probability: Stochastic Partial Differential Equations

Math/ECE/Stat 888 Topics in Mathematical Data Science