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            <h1>Iddo Drori</h1>
            <p class="subtitle">Associate Professor of Computer Science</p>
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        <article class="bio-content">
            <p>Iddo Drori is an Associate Professor of Computer Science focusing on artificial general and super intelligence. He has taught at <a href="https://www.stanford.edu">Stanford</a>, <a href="https://www.mit.edu">MIT</a>, <a href="https://www.columbia.edu">Columbia</a>, <a href="https://www.nyu.edu">NYU</a>, and <a href="https://www.bu.edu">BU</a> with excellent formal evaluations.</p>

            <p>He has conducted research at <a href="https://www.orie.cornell.edu">Cornell ORIE</a>, <a href="https://www.eecs.mit.edu/new-algorithm-aces-university-math-course-questions">MIT EECS</a>, <a href="https://cds.nyu.edu">NYU Center for Data Science</a>, <a href="https://cims.nyu.edu">Courant Institute</a>, and <a href="https://engineering.nyu.edu">Tandon</a>. He was a postdoctoral research fellow in statistics at <a href="https://statistics.stanford.edu">Stanford University</a> and holds a Ph.D. in computer science.</p>

            <p>He holds an MBA in organizational behavior and entrepreneurship, and has a decade of industry research and leadership experience.</p>

            <div class="stats">
                <a href="https://idrori.github.io/#publications" class="stat">
                    <div class="stat-number">85+</div>
                    <div class="stat-label">Publications</div>
                </a>
                <a href="https://scholar.google.com/citations?hl=en&user=DDIjoEUAAAAJ" class="stat">
                    <div class="stat-number">7,300+</div>
                    <div class="stat-label">Citations</div>
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                <a href="https://idrori.github.io/#teaching" class="stat">
                    <div class="stat-number">60+</div>
                    <div class="stat-label">Courses Taught</div>
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            <p>His current research is in artificial superintelligence (ASI) for math and science, and verifiable automated scientific discovery. He developed the first Deep Learning class at Columbia in 2017, Meta Learning class at MIT in 2020, and AGI class at Columbia in 2023.</p>

            <div class="books">
                <div class="books-title">Books</div>
                <p class="book-item"><a href="https://dlbook.org">The Science of Deep Learning</a><span class="book-publisher">, <a href="https://www.cambridge.org">Cambridge University Press</a>, 2023</span></p>
                <p class="book-item"><a href="https://agibook.org">Artificial General Intelligence: Mathematical Foundations</a><span class="book-publisher">, <a href="https://www.cambridge.org">Cambridge University Press</a>, 2026</span></p>
            </div>

            <p>He has won multiple competitions in machine learning, AI, and <a href="https://www.cs.columbia.edu/2019/cs-team-wins-the-iccv-2019-learning-to-drive-challenge">computer vision</a> <a href="https://www.cs.columbia.edu/2021/columbia-team-wins-top-3-in-the-fg-2021-families-in-the-wild-kinship-verification">conferences</a>, and received multiple best paper awards.</p>

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