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<!DOCTYPE HTML>
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<head>
  <title>Chang Deng</title>

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<body>
  <div class="section">
      <p class="name">
        Chang Deng
      </p>
      <h1> Hi there 👋! </h1>
      <p>
        I am a fourth-year PhD student in Econometrics and Statistics at the University of Chicago (UChicago)
        <a href="https://www.chicagobooth.edu/">Booth School of Business</a>.
        Before joining Booth, I earned a Master&rsquo;s degree in
        <a href="https://cam.uchicago.edu/">Computational and Applied Mathematics</a> at UChicago.
        Prior to coming to UChicago, I obtained my Bachelor&rsquo;s degree in Applied Mathematics at the <a href="https://www.sustech.edu.cn/">Southern University of Science and Technology (SUSTech)</a>.
      </p>
      <p>
        My research primarily centers on causal discovery, mainly learning structure from data, with a particular emphasis on learning causal structure.
      </p>

      <p style="text-align:center">
        <a href="https://scholar.google.com/citations?user=51voxF8AAAAJ&hl=en">
          <img src="icons/icons8-google-scholar-50.png" alt="Google Scholar Icon" style="vertical-align: middle;" width="35"></a>
          &nbsp|&nbsp
        <a href="https://www.linkedin.com/in/chang-deng-0094a5144/">
          <img src="icons/icons8-linkedin-50.png" alt="Linkedin Icon" style="vertical-align: middle;" width="50"> </a>
           &nbsp|&nbsp
        <a href="https://twitter.com/ChangDeng3">
          <img src="icons/icons8-twitter-50.png" alt="Twitter Icon" style="vertical-align: middle;" width="35"> </a>
            &nbsp|&nbsp
        <a href="https://github.com/Duntrain">
          <img src="icons/icons8-github-100.png" alt="Github Icon" style="vertical-align: middle;" width="45"> </a>
          &nbsp|&nbsp
        <a href="mailto:changdeng@uchicago.edu">
          <img src="icons/icons8-email-64.png" alt="Email Icon" style="vertical-align: middle;" width="40"> </a>
      </p>
  </div>

  <div class="section">
    <h1>Publications 📚</h1>

      <div class="content">
        <ul>

            <li>
              <p> <a href="https://arxiv.org/abs/2509.21658"><span class="paper" style="color: #C4820E;">Differentiable Structure Learning and Causal Discovery for General Binary Data</span> </a>
                <br>
                <span class="author"><strong>Chang Deng</strong>, Bryon Aragam</span><br>
                <span class="venue">NeurIPS 2025</span>
              </p>
          </li>
          <li>
          <p> <a href="https://arxiv.org/abs/2410.06163"><span class="paper" style="color: #C4820E;">Markov Equivalence and Consistency in Differentiable Structure Learning</span> </a>
                <br>
                <span class="author"><strong>Chang Deng</strong>, Kevin Bello, Pradeep Ravikumar, Bryon Aragam</span><br>
                <span class="venue">NeurIPS 2024</span>
          </p>
          </li>
        <li>
          <p> <a href="https://onlinelibrary.wiley.com/doi/10.1002/nav.22190"><span class="paper" style="color: #C4820E;">Data-driven Forecasting and Reference Prices with Exposure Effect</span> </a>
            <br>
            <span class="author">Opher Baron, <strong>Chang Deng</strong>, Simai He, Hongsong Yuan</span><br>
            <span class="venue">Naval Research Logistics 2024</span>
          </p>
        </li>
        <li>
          <p> <a href="https://link.springer.com/article/10.1007/s11222-024-10399-4"><span class="paper" style="color: #C4820E;">High-dimensional sparse single–index regression via Hilbert–Schmidt independence criterion</span> </a>
            <br>
            <span class="author">Xin Chen, <strong>Chang Deng</strong>, Shuaida He, Runxiong Wu, Jia Zhang</span><br>
            <span class="venue">Statistics and Computing 2024</span>
          </p>
        </li>
        <li>
          <p> <a href="https://arxiv.org/abs/2306.17378"><span class="paper" style="color: #C4820E;">Global Optimality in Bivariate Gradient-based DAG Learning</span> </a>
            <br>
            <span class="author"><strong>Chang Deng</strong>, Kevin Bello, Bryon Aragam, Pradeep Ravikumar</span><br>
            <span class="venue">NeurIPS 2023</span>
          </p>
        </li>
        <li>
          <p> <a href="https://arxiv.org/abs/2305.17277"><span class="paper" style="color: #C4820E;">Optimizing NOTEARS objective via topological swaps</span> </a>
            <br>
            <span class="author"><strong>Chang Deng</strong>, Kevin Bello, Bryon Aragam, Pradeep Ravikumar</span><br>
            <span class="venue">ICML 2023 &nbsp|&nbsp <a href="https://github.com/Duntrain/TOPO"> Code </a> &nbsp|&nbsp <a href=""> Proceedings </a></span>
          </p>
        </li>
        <li>
          <p> <a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9671640"><span class="paper" style="color: #C4820E;">A simple approach to balance task loss in multi-task learning</span> </a>
            <br>
            <span class="author">Sicong Liang, <strong>Chang Deng</strong>, Yu Zhang</span><br>
            <span class="venue">IEEE Big Data 2021</span>
          </p>
        </li>
        <li>
          <p> <a href="https://link.springer.com/chapter/10.1007/978-3-030-86486-6_33"><span class="paper" style="color: #C4820E;">Deep multi-task augmented feature learning via hierarchical graph neural network</span> </a>
            <br>
            <span class="author">Pengxin Guo, <strong>Chang Deng</strong>, Linjie Xu, Xiaonan Huang, Yu Zhang</span><br>
            <span class="venue">ECML PKDD 2021</span>
          </p>
          </li>
        </ul>
      </div>
  </div>

  <div class="section">
    <h1>Preprint 📄</h1>
      <div class="content">
        <ul>
        </ul>
      </div>
  </div>


  <div class="section">
    <h1>Professional Service 📖</h1>
      <div class="content">
        <ul>
            <li>Conference reviewer: NeurIPS, ICLR, AISTATS, CLeaR, ICML, UAI, AAAI, TMLR</li>
            <li>TA: Business Statistics, Data Analysis </li>
        </ul>
      </div>
  </div>

  <div class="section">
    <h1>Misc 📌</h1>
    <div class = "content">
      <ul>
        <li> 🇨🇳 👨‍🎓 🌞 🌅 🌆 🎵 🎧 🏃‍♂️ 🎮 🏀 📈 👨‍💻 💻 🐶 🏞️ 🏕️ 🏖️ ⛰️ 🌊 🌈 🍉 🥤 🟦</li>
      </ul>
    </div>
  </div>

  <div class="section">
    <h1>Link 🔗</h1>
    <div class="content">
      <ul>
      <li><a href="https://www.chicagobooth.edu/faculty/research-workshops/econometrics-and-statistics" style="color: #8a1905;"> Booth Econometrics and Statistics Colloquium</a></li>
      <li><a href="https://www.chicagobooth.edu/faculty/research-workshops/operations-management-science" style="color: #8a1905;"> Booth Operation Management Colloquium</a></li>
      <li><a href="https://stat.uchicago.edu/events/statistics-colloquium/" style="color: #8a1905;"> UChicago Statistics Colloquium</a></li>
      <li><a href = 'https://www.chicagobooth.edu/faculty/research-workshops/ai-workshop' style="color: #8a1905;">AI Workshop</li>
      <li><a href="https://www.ttic.edu/colloquium/" style="color: #8a1905;"> TTIC Colloquium</a></li>
      </ul>
    </div>
  </div>

  <div class="section">
    <div class="content">
      <p style="text-align:right;font-size:14px;margin-top:100px;">
        <a href="https://github.com/jonbarron/website" style="color: #FF5733;">Template source</a>
      </p>
    </div>
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