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    <title>Liam Jemison</title>
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      <title>Poisson Boltzmann Equations</title>
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      <pubDate>Fri, 17 Apr 2026 15:31:05 -0500</pubDate>
      
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      <description>
      Between 2022-2025 I worked as a research assistant for Dr. Dexuan Xie on an NSF grant to develop computational models of Voltage Dependent Anion Channels (VDAC). We wrote a paper describing some electrostatic computations using finite elmenent codes Dr. Xie developed earlier, which was published in the Journal of Computational Chemistry. &amp;amp;ndash;&amp;amp;gt; I worked with Dr. Xie to develop &amp;amp;ldquo;nonlocal&amp;amp;rdquo; extensions of the traditional PB theory. We published a paper in the Journal of Computational and Applied Mathematics describing a nonlocal PB model for biomolecules in ionic solutions that include ion size effects. In my dissertation, I developed a nonlocal PB model for ion channels, such as VDAC.

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      <title>Sporophyte Detection</title>
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      <pubDate>Sun, 12 Apr 2026 15:49:53 -0500</pubDate>
      
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      <description>
      Working with biologists in the Alberto lab at UW Milwaukee, I created a new dataset of over 1300 microscope images of Giant Kelp and Nereocystis sporophytes with hand labelled bounding boxes around sporophytes and eggs. Using this data, I trained object detection machine learning models to identify sporophytes automatically. I contributed a blog post about this project to SIAM news, and I gave a contributed presentation about the topic at the SIAM MPE22 conference in the summer of 2022. I have also created a hugging face space to demonstrate the network we trained. 
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      <title>DC Functions</title>
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      <pubDate>Wed, 17 Jun 2020 16:35:15 -0500</pubDate>
      
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      As an undergraduate at Portland State University I wrote an honors thesis about DC (difference- or perhaps delta-) convex functions under Dr. Mau Nam Nguyen. DC functions are a superset of convex functions &amp;amp;ndash; any function expressible as the difference of two convex functions is a DC function &amp;amp;ndash; and are of interest as the subject of efficient optimization algorithms.

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