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          <h2>Gennaro Francesco</h2>
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              <span>Zurich, Switzerland</span>
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        <h1>Gennaro Francesco Landi</h1>
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        <h2>About Me</h2>
        <p>I am a Master's student in Computer Science at ETH Zurich, majoring in Data Management Systems with a minor in Machine Learning.</p>

        <p>I hold a Bachelor's degree in Computer Engineering from the University of Salerno, where I graduated with top marks and developed a strong foundation in algorithms, networks, operating systems, and software engineering. Simultaneously, I pursued a second Bachelor's degree in Statistics for Big Data, which enhances my ability to analyze and interpret large-scale data systems, equipping me with complementary skills crucial for addressing modern computational challenges.</p>

        <p>My curiosity drives me to uncover the "why" behind every problem, while my proactive nature ensures that I seek out challenges and opportunities for growth.</p>

        <h2>Research Interests</h2>
        <p>I'm interested in large-scale systems, cloud architectures, and intelligent data processing. At ETH Zurich, I aspire to collaborate with leading research groups that share my vision and contribute to advancing the state-of-the-art in these fields:</p>

        <h3>Efficient Architectures and Systems Lab (EASL)</h3>
        <p><strong>Led by Prof. Ana Klimović.</strong> <a href="https://systems.ethz.ch/research/easl.html" target="_blank">EASL</a> designs and builds computer systems for large-scale applications, spanning operating systems, cloud computing, and the use of machine learning for system optimization. Their focus on serverless computing and resource-efficient system design resonates strongly with my goal of making large-scale data platforms more robust and accessible.</p>

        <h3>Data Processing on Modern Hardware Group</h3>
        <p><strong>Led by Prof. Gustavo Alonso.</strong> This <a href="https://systems.ethz.ch/research/data-processing-on-modern-hardware.html" target="_blank">group</a> explores the implications of rapidly evolving hardware and heterogeneous architectures on data systems, from databases on GPUs and FPGAs to cloud-native processing engines. I am particularly drawn to their long-term vision of building innovative systems that exploit new hardware capabilities while ensuring scalability and efficiency in cloud deployments.</p>
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