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<!DOCTYPE html>
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  <title>Matt Poncini | ML & Optimization</title>
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<body>
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    <!-- Header -->
    <h1>Matt Poncini</h1>
    <p>
      Graduate Computer Science student specializing in
      <strong>machine learning, optimization, and algorithm design</strong>,
      with a military and education background.
    </p>

    <p class="links">
      🔗 <a href="https://github.com/MPoncini96">GitHub</a>
      <a href="https://www.linkedin.com/in/matt-poncini/">LinkedIn</a>
    </p>

    <!-- About Section -->
    <section>
      <h2>About Me</h2>

      <div class="about">
        <img
          src="images/marathon.jpeg"
          alt="Matt Poncini after completing a marathon"
          class="about-photo"
        />

        <div class="about-text">
          <p>
            I’m a graduate student in Computer Science with a strong focus on machine
            learning, optimization, and algorithm design. Prior to graduate school,
            I served six years in the military as a reservist and began my career in
            education.
          </p>

          <p>
            My work sits at the intersection of theory and practice, where I build,
            evaluate, and document models that solve complex, real-world problems.
          </p>
        </div>
      </div>
    </section>

    <!-- Projects -->
    <section>
      <h2>Selected Projects</h2>

      <ul>
        <li>
          <strong>QLoRA Fine-Tuning of LLaMA-2-7B</strong><br />
          Domain-specific fine-tuning using QLoRA, PEFT, and Hugging Face.
          <a href="https://github.com/MPoncini96/QLoRA-FineTuning-Llama2-Finance-Alpaca">
            View on GitHub
          </a>
        </li>

        <li>
          <strong>Bottleneck Traveling Salesman Problem</strong><br />
          Simulated Annealing, Niching Genetic Algorithms, and an LKH baseline.
          <a href="https://github.com/MPoncini96/Bottleneck-TSP-Solutions-with-SA-and-Niching-GA-and-a-LKH-Baseline">
            View on GitHub
          </a>
        </li>

        <li>
          <strong>Peptide Unsupervised Clustering</strong><br />
          UMAP and HDBSCAN for exploratory bioinformatics analysis.
          <a href="https://github.com/MPoncini96/Peptide-Unsupervised-Clustering-with-UMAP-and-HDBSCAN">
            View on GitHub
          </a>
        </li>

        <li>
          <strong>OSSP Wisdom-of-Crowds GA Hybrid</strong><br />
          Crowd-inspired genetic algorithm for open shop scheduling optimization.
          <a href="https://github.com/MPoncini96/OSSP-Scheduler-WoC-GA-Hybrid">
            View on GitHub
          </a>
        </li>
      </ul>
    </section>

    <!-- Interests -->
    <section>
      <h2>Interests</h2>
      <p>
        Machine learning, optimization, metaheuristics, large language models,
        applied AI, and data-driven decision making.
      </p>
    </section>

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