Seminar on Stochastic Processes 2017

The Seminar on Stochastic Processes (SSP) in 2017 was held from Wednesday, March 8, through Saturday, March 11. It was hosted by the University of Virginia. Conference website.

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Mont Puget at Luminy

2017 travel

January

23-25 • Cleveland • Case Western Reserve University

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Front of percolation

MATH 3100 • Introduction to Probability

[Spring 2017 semester]

Probability seminar

In 2014-2017 I co-organized the UVA probability seminar, and will return to it in Fall 2018
Yosemite waterfall in March 2016

2016 travel

January

28 • Madison • University of Wisconsin-Madison

All travel in 2016 »

A fragment of a random heart

Reading seminar on integrable probability in Spring 2017

In the Spring 2017 me and Axel Saenz will continue with the Integrable Probability Reading Seminar. This time the topic will be “From random tilings to Kardar-Parisi-Zhang universality.” In terms of content, this is not a continuation of the Fall’s seminar. In the Spring, the seminar’s aim is to give a user-friendly introduction to modern and rapidly developing topics in probability theory with connections to combinatorics, algebra, representation theory on one side, and statistical physics and many other applications on the other side.

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A flowchart for Macdonald processes and some of their specializations and limits (from talks of the authors on the subject)

5 years of Macdonald Processes

[2016/11/18]

Today marks a 5-year anniversary of the paper “Macdonald Processes” by A. Borodin and I. Corwin. It was posted on the arXiv on November 18, 2011 (arxiv.org/abs/1111.4408) and was subsequently published at Probability Theory and Related Fields (2014), Volume 158, Issue 1, pp 225–400. As of this day, Google Scholar counts 178 citations to this paper.

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Coupling of q-TASEPs and the stochastic higher spin six vertex model

Stochastic higher spin six vertex model and q-TASEPs

[2016/10/30]

We present two new connections between the inhomogeneous stochastic higher spin six vertex model in a quadrant and integrable stochastic systems from the Macdonald processes hierarchy.

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