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<!DOCTYPE html>
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    <meta name="description" content="Personal portfolio of Florent Draye, a PhD student in Machine Learning. Discover research, projects, and experiences.">
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<body>
    <header>
        <div class="container">
            <h1>  </h1>
            <nav>
                <ul>
                    <li><a href="#about-section">About</a></li>
                    <li><a href="#cv-section">CV</a></li>
                    <li><a href="#news-section">News</a></li>
                    <li><a href="#research-section">Research</a></li>
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    <main>
        <!-- About Section -->
        <section id="about-section" class="about-section">
            <div class="container">
                <div class="profile-wrapper">
                    <div class="left-column">
                        <h2>About Me</h2>
                        <p>
                            Hi! I'm a first year ELLIS PhD student in mechanistic interpretability and AI safety at the MPI for Intelligent Systems advised by Prof. Bernhard Schölkopf, and supported by the Hector Fellow Academy.
                        </p>
                        <p>
                            I am interested in understanding the internal mechanisms of large language models (LLMs), particularly their "world models"—the structured representations they develop to interpret and make sense of data.

                            My current projects center around cross-layer transcoders and attribution graphs.
                        <p>
                            Before starting my PhD, I did a BSc in mathematics at EPFL and spent one year at ENS in Paris (Ulm). I then transitioned to pursue a MSc in Neural Systems and Computation at ETH Zürich. During my master, I worked by Prof. Maneesh Sahani at the Gatbsy Unit in London on non-generative representation learning.
                        </p>
                    </div>
                    <div class="right-column">
                        <img src="images/Flo_Yvo4.jpg" alt="Profile Picture">
                        <h2>Florent Draye</h2>
                        <p class="title">PhD Student in Machine Learning</p>
                        <p class="institution">MPI-IS, Germany</p>
                        <div class="social-links">
                            <a href="mailto:draye.florent@gmail.com" title="Email">📧</a>
                            <a href="https://github.com/florentdraye" target="_blank" title="GitHub">🐙</a>
                            <a href="https://www.linkedin.com/in/florent-draye-2ab42a152/" target="_blank" title="LinkedIn">🔗</a>
                            <a href="https://x.com/flodraye" target="_blank" title="Twitter">🐦</a>
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        </section>

        <!-- CV Section -->
        <section id="cv-section" class="cv-section">
            <div class="container">
                <h2>Education</h2>
                <ul class="education-list">
                    <li>
                        <b>PhD, Machine Learning</b>
                        <p>Max Planck Institute | 2025–Present</p>
                    </li>
                    <li>
                        <b>MSc, Neural Systems and Computation</b>
                        <p>ETH Zürich | 2022–2024</p>
                        <p>GPA: 5.9/6</p>
                    </li>
                    <li>
                        <b>Exchange Program, Mathematics</b>
                        <p>Ecole Normale Supérieure (Ulm) | 2021–2022</p>
                        <p>GPA: 18.3/20</p>
                    </li>
                    <li>
                        <b>BSc, Mathematics</b>
                        <p>EPFL | 2019–2022</p>
                        <p>GPA: 5.88/6</p>
                    </li>
                </ul>
                <h3>Prizes</h3>
                <ul class="education-list">
                    <li>
                        <b>Best Bachelor Average Grade (1500$)</b>
                        <p>
                            <small>
                                Awarded for achieving the highest bachelor average (5.88/6) among 1214 graduates, 2022.
                            </small>
                        </p>
                        <p>EPFL, 2019–2022</p>
                    </li>

                    <li>
                        <b>Part III International Scholarship – University of Cambridge</b>
                        <p>
                            <small>
                                Awarded based on academic potential for the Master of Applied Mathematics (Part III), declined.
                            </small>
                        </p>
                        <p>University of Cambridge, 2022</p>
                    </li>
                </ul>
                <h3>Experiences</h3>
                <ul class="education-list">
                    <li>
                        <b>Machine Learning Research Intern</b>
                        <p>Gatsby Unit UCL, 09/2023-02/2023</p>
                    </li>
                    <li>
                        <b>Data Science Intern</b>
                        <p>Mindmaze, Summer 2023</p>
                    </li>
                </ul>
            </div>
        </section>

        <section id="news-section" class="news-section">
            <div class="container">
                <h2>News</h2>

                <div class="news-item">
                    <h3>Released CLT-Forge library</h3>
                    <p>March 2026</p>
                    <p>
                        I released <a href="https://github.com/LLM-Interp/CLT-Forge" target="_blank">
                        CLT-Forge</a>, a library for Cross-Layer Transcoders and mechanistic interpretability.
                    </p>
                </div>

                <div class="news-item">
                    <h3>Just started my PhD with Prof. Bernhard Schölkopf</h3>
                    <p>January 2025</p>
                </div>

            </div>
        </section>

        <section id="research-section" class="research-section">
            <div class="container">
                <h2>Research</h2>
                <div class="research-item">
                    <h3>A Review on the Universal Approximation Theorems of Artificial Neural Networks</h3>
                    <p>U Faure<sup>†</sup>, F Draye<sup>†</sup>, Bachelor Thesis 2022</p>
                    <p><small>† Equal contribution</small></p>
                    <a href="https://www.researchgate.net/profile/Florent-Draye/publication/381002345_A_Review_on_the_Universal_Approximation_Theorems_of_Artificial_Neural_Networks/links/6658c0b1479366623a333562/A-Review-on-the-Universal-Approximation-Theorems-of-Artificial-Neural-Networks.pdf" target="_blank">PDF</a>
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