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<h1 class="sr-only">Leonid Petrov - Integrable Probability</h1>
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                        <span>About</span>
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            About &bull; (<a href="{{ site.url }}/research/">papers</a>) &bull;
            (<a href="{{ site.url }}/research/petrovCVbrief.pdf">CV</a>)
        </h2>

        <p><strong>Professor of Mathematics, University of Virginia</strong>.</p>

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            <p>
                Leonid Petrov works in integrable probability, an area of
                mathematical research at the interface between probability /
                statistical physics on the one hand and representation
                theory/quantum integrability on the other. He applies tools from
                integrability (symmetric functions and Yang-Baxter equations for
                solvable lattice models) to analyze the asymptotic behavior of
                stochastic models motivated by a wide range of real-world questions,
                including the structure of ice and other condensed matter,
                magnetism, quantum spin systems, thermodynamics, traffic models, and
                directed polymers.
            </p>
            <p>
                Petrov completed his Ph.D. in 2010 in Moscow with advisor Grigori
                Olshanski. Following a postdoctoral position at Northeastern
                University (2011-2014), he joined the University of Virginia as
                faculty in Department of Mathematics. He has held visiting positions
                at MIT (2017-2018), MSRI (Fall 2021), and IPAM (Spring 2024).
            </p>
            <p>
                Recently, he is also involved in broadening access to AI tools for
                working mathematicians by
                <a href="https://lpetrov.cc/AI-math/">sharing</a>
                <a
                    href="https://storage.lpetrov.cc/research_files/talks/AI_UVA_Oct10.pdf"
                    >best practices,</a
                >
                participating in panel discussions, and
                <a href="{{site.url}}/simulations/">utilizing AI to build interactive simulations</a>
                of cutting-edge research advances
                in integrable probability and beyond (see below for a few comprehensive examples).
            </p>

            <p><strong>Keywords</strong>: Integrable probability, KPZ universality, interacting
            particle systems, six vertex model, Yang-Baxter equation, stochastic
            vertex models, Bethe ansatz, Macdonald processes, random tilings,
            symmetric functions, algebraic combinatorics</p>

            <ul class="mt-3">
                <li>
                    NSF grant
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153869"
                        >2153869</a
                    >
                    "Random Systems from Symmetric Functions and Vertex Models"
                    (2022-2025).
                </li>
                <li>
                    <a href="http://frg.int-prob.org/" target="_blank"
                        >Focused Research Group in Integrable Probability<span class="sr-only"> (opens in new tab)</span></a
                    >
                    (2017-2022) supported by the NSF grant
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664617"
                        target="_blank"
                        >1664617<span class="sr-only"> (opens in new tab)</span></a
                    >
                    and companion grants
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664531"
                        target="_blank"
                        >1664531<span class="sr-only"> (opens in new tab)</span></a
                    >,
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664619"
                        target="_blank"
                        >1664619<span class="sr-only"> (opens in new tab)</span></a
                    >,
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664650"
                        target="_blank"
                        >1664650<span class="sr-only"> (opens in new tab)</span></a
                    >.
                </li>
            </ul>
        </div>
        <div class="d-none d-md-block">
            <p>
                Leonid Petrov works in integrable probability, an area of
                mathematical research at the interface between probability /
                statistical physics on the one hand and representation
                theory/quantum integrability on the other. He applies tools from
                integrability (symmetric functions and Yang-Baxter equations for
                solvable lattice models) to analyze the asymptotic behavior of
                stochastic models motivated by a wide range of real-world questions,
                including the structure of ice and other condensed matter,
                magnetism, quantum spin systems, thermodynamics, traffic models, and
                directed polymers.
            </p>
            <p>
                Petrov completed his Ph.D. in 2010 in Moscow with advisor Grigori
                Olshanski. Following a postdoctoral position at Northeastern
                University (2011-2014), he joined the University of Virginia as
                faculty in Department of Mathematics. He has held visiting positions
                at MIT (2017-2018), MSRI (Fall 2021), and IPAM (Spring 2024).
            </p>
            <p>
                Recently, he is also involved in broadening access to AI tools for
                working mathematicians by
                <a href="https://lpetrov.cc/AI-math/">sharing</a>
                <a
                    href="https://storage.lpetrov.cc/research_files/talks/AI_UVA_Oct10.pdf"
                    >best practices,</a
                >
                participating in panel discussions, and
                <a href="{{site.url}}/simulations/">utilizing AI to build interactive simulations</a>
                of cutting-edge research advances
                in integrable probability and beyond (see below for a few comprehensive examples).
            </p>
        </div>

        {%include sims.html%}

        <div class="d-none d-md-block">
            <p><strong>Keywords</strong>: Integrable probability, KPZ universality, interacting
            particle systems, six vertex model, Yang-Baxter equation, stochastic
            vertex models, Bethe ansatz, Macdonald processes, random tilings,
            symmetric functions, algebraic combinatorics</p>

            <ul class="mt-3">
                <li>
                    NSF grant
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153869"
                        >2153869</a
                    >
                    "Random Systems from Symmetric Functions and Vertex Models"
                    (2022-2025).
                </li>
                <li>
                    <a href="http://frg.int-prob.org/" target="_blank"
                        >Focused Research Group in Integrable Probability<span class="sr-only"> (opens in new tab)</span></a
                    >
                    (2017-2022) supported by the NSF grant
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664617"
                        target="_blank"
                        >1664617<span class="sr-only"> (opens in new tab)</span></a
                    >
                    and companion grants
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664531"
                        target="_blank"
                        >1664531<span class="sr-only"> (opens in new tab)</span></a
                    >,
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664619"
                        target="_blank"
                        >1664619<span class="sr-only"> (opens in new tab)</span></a
                    >,
                    <a
                        href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664650"
                        target="_blank"
                        >1664650<span class="sr-only"> (opens in new tab)</span></a
                    >.
                </li>
            </ul>
        </div>

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