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  • Open service 46.23.81.157:443 · chrisgeoga.com

    2026-01-10 14:20

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    Page title: Chris Geoga
    
    <!DOCTYPE html>
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        <title>Chris Geoga</title>
        <link href="styles.css" rel="stylesheet" ></link>
    
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    <header>
        <h1>
          Chris Geoga
        </h1>
    </header>
    
    
    <p>
    I am a statistician and applied mathematician with broad interests in
    statistical methodology and computing in the physical sciences. My primary
    interest is modeling complicated dependence structure in real-life
    temporal/spatial/spatio-temporal processes, and I'm particularly interested in
    theoretical questions that are motivated by computationally scalable methods and
    approximations.
    </p>
    
    <h2>Education:</h2>
    
    <ul>
    
      <li>
        Ph.D. Statistics, Rutgers University (2018 &#8211 2023)
      </li>
      <ul>
        <li>
          Dissertation: Models and Computation for Nonstationary Processes at Scale
          <br>
          Adv. Michael L. Stein
        </li>
      </ul>
    
      <li>
        B.S. Mathematics / B.A. Statistics, University of Chicago (2012 &#8211 2016)
      </li>
    
    </ul>
    
    <h2>Employment:</h2>
    
    <ul>
    
      <li>
        University of Wisconsin-Madison, Dept. of Statistics 
      </li>
      <ul>
        <li>
          Assistant Professor (2023 &#8211 )
        </li>
      </ul>
    
      <li>
        Argonne National Laboratory, Division of Mathematics and Computer Science
      </li>
      <ul>
        <li>
          Visiting Student (2022 &#8211 2023)
        </li>
        <li>
          Argonne Associate (2018 &#8211 2022)
        </li>
        <li>
          Assistant Computational Mathematician (RD1) (2016 &#8211 2018)
        </li>
      </ul>
    
    </ul>
    
    <h2>Publications:</h2>
    
    <p>
    Clicking on the title of the paper will take you to ArXiv or some other direct
    PDF source, and the DOI link will take you to the official journal version.
    Direct PDF links marked (ArXiv vXXX) mean that the ArXiv version differs from
    the journal version somehow. I try to do a good job about uploading substantial
    revisions to arXiv, so the differences are in general limited to small revisions
    that don't really change the substance of the paper very much. But if you want a
    journal version and can't get access, please shoot me a note and I'll send one
    over.
    </p>
    
    <p>
    You can also see my publications on My <a
      href="https://scholar.google.com/citations?user=L24G8isAAAAJ&hl=en&oi=ao">
      google scholar </a> profile. <span style="color:maroon;">Authors in maroon</span>
      are/were graduate students working with me at the time of initial submission.
    </p>
    
    <ul>
        <li>
          <span style="color:maroon;">H. Xiong</span>, P. Muradyn, and <strong>C.J. Geoga</strong>. <a href="https://arxiv.org/abs/2512.04217"> High-Resolution Retrieval of Atmsopheric Boundary Layers with Nonstationary Gaussian Processes</a>.
          Submitted.
        </li>
    
        <li>
          <strong>C.J. Geoga</strong>, P.G. Beckman. <a href="https://arxiv.org/abs/2503.00492"> Fast nonparametric spectral density estimation from irregularly sampled data</a>.
          Submitted.
        </li>
    
        <li>
          P.G. Beckman, <strong>C.J. Geoga</strong>.
          <a href="https://arxiv.org/abs/2404.19053">Fast Adaptive Fourier
            Integration for Spectral Densities of Gaussian Processes</a>.
          Statistics and Computing. <a href="https://doi.org/10.1007/s11222-024-10519-0">DOI link</a>.
        </li>
    
    
        <li>
          <strong>C.J. Geoga</strong>.
          <a href="https://arxiv.org/abs/2404.16583">Fast Machine-Precision Spectral
          Likelihoods for Stationary Time Series</a>, SISC. <a href="https://doi.org/10.1137/24M1660632">DOI link</a>.
        </li>
    
        <li>
          <strong>C.J. Geoga</strong>, M.L. Stein.
          <a href="https://arxiv.org/abs/2208.06877">A Scalable Method to Exploit
            Screening in Gaussian Process Models with Noise</a> (Arxiv v2).
          Journal of Computational and Graphical Statistics.
          <a href
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  • Open service 46.23.81.157:80 · chrisgeoga.com

    2026-01-10 14:20

    HTTP/1.1 302 Moved Temporarily
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    Date: Sat, 10 Jan 2026 14:20:13 GMT
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chrisgeoga.com
CN:
chrisgeoga.com
Key:
ECDSA-256
Issuer:
E7
Not before:
2026-01-10 13:20
Not after:
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