guojialegeographer.github.io/talks.html at main · GuojialeGeographer/guojialegeographer.github.io · GitHub

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                    <span lang="zh">地理空间数据科学</span>
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<h1>Presentations (e.g., Talks/Lectures) </h1>
<hr>
Welcome to reach out our slides! These slides follow a simple LaTeX template at our open-source GitHub repository (see <a href="https://github.com/xinychen/awesome-beamer">
  awesome-beamer</a>). Some basic rules for creating these slides would be: 1) Introducing methodological and theoretical stuff clearly and intuitively;
  2) Improving the insight and vision throughout the research presentation.
  Feel free to contact me if you have any questions or feedback.

<ul>
</ul>

<h2>2025</h2>
<ul>
  <li>
    <p> February 7, 2025: Department of Industrial & Systems Engineering, University of Tennessee, Knoxville (UTK), Knoxville, USA. <br>
      Topic: Machine learning and optimization for data-driven transportation analytics and beyond.
    <br>
    </p>
</ul>

<h2>2024</h2>
<ul>
  <li>
    <p> December 16, 2024: <a href="https://mlsm.man.dtu.dk/">Machine Learning for Smart Mobility (MLSM) group</a>, Technical University of Denmark (DTU), Denmark. <br>
        Topic: Machine learning and optimization for data-driven transportation analytics. <br>
        Invited by: <a href="https://fprodrigues.com/">Filpe Rodrigues</a>
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> December 6, 2024: School of Management, Technical University of Munich (TUM), Heilbronn, Germany. <br>
        Topic: Machine learning and optimization for data-driven transportation analytics.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> October 21, 2024: 2024 INFORMS Annual Meeting, Seattle, USA. <br>
      Slides: <a href="https://xinychen.github.io/slides/informs24.pdf">
        Modeling urban traffic data with matrix and tensor factorization approaches</a>. <br>
        Session format: Invited Session (See <a href="https://spatiotemporal-data.github.io/talks/informs24">talk post</a>)
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> July 11, 2024: Dalian University of Technology, Dalian, China. <br>
      Slides: <a href="https://xinychen.github.io/slides/LCR24.pdf">
        Laplacian convolutional representation for traffic time series imputation</a>. <br>
        Invited by: Chun Cheng (See <a href="https://spatiotemporal-data.github.io/talks/dut-2407">talk post</a> in Chinese)
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> May 16, 2024: <a href="https://sites.google.com/view/uirlab?pli=1">Ryan Wang Lab</a> at Northeastern University, Boston, USA. <br>
      Slides: <a href="https://xinychen.github.io/slides/temporal_modeling.pdf">
        Modeling temporal correlations and dynamics in spatiotemporal data systems</a>. <br>
        Invited by: Ryan Qi Wang, Weiyu Li
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> January 11, 2024: Reproducible Research Workshop of the 103rd Transportation Research Board (TRB) Annual Meeting, Washington, D.C., USA. <br>
      Slides: <a href="https://xinychen.github.io/slides/transdim.pdf">
        Open-source projects: Machine learning for transportation data imputation and prediction</a>. <br>
        Speakers: Nicolas Saunier, Xinyu Chen
      <br>
    </p>
</ul>

<h2>2023</h2>
<ul>
  <li>
    <p> December 28, 2023: SUSTech Forum with the Department of Statistics and Data Science (南方科技大学统计与数据科学系青年学者论坛), Shenzhen, China. (Online) <br>
      Slides: <a href="https://xinychen.github.io/slides/sustech23.pdf">
        Matrix and tensor models for spatiotemporal traffic data imputation and forecasting</a>.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> December 11, 2023: PhD Research Defense, Montreal, Canada. <br>
      Committee members: Francesco Ciari, Nicolas Saunier, Lijun Sun, James Goulet, and Guillaume Rabusseau <br>
      Slides: <a href="https://xinychen.github.io/slides/defense.pdf">
        Matrix and tensor models for spatiotemporal traffic data imputation and forecasting</a>.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> July 19, 2023: World Conference on Transport Research (WCTR 2023), Montreal, Canada. <br>
      Slides: <a href="https://xinychen.github.io/slides/LCR.pdf">
        Laplacian convolutional representation for traffic time series imputation</a>.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> May 22, 2023: Southern University of Science and Technology (SUSTech, 南方科技大学), Shenzhen, China. <br>
      Slides: <a href="https://xinychen.github.io/slides/traffic_data_modeling_v1.pdf">
        Low-rank matrix and tensor methods for spatiotemporal traffic data modeling</a>.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> April 20-21, 2023: Sichuan University (SCU, 四川大学) & University of Electronic Science and Technology of China (UESTC, 电子科技大学), Chengdu, China. <br>
      Slides: <a href="https://xinychen.github.io/slides/stdata_modeling.pdf">
        Low-rank matrix and tensor methods for spatiotemporal data modeling</a>.
      <br>
    </p>
</ul>

<ul>
  <li>
    <p> March 9, 2023: Research Group of Transport, Polytechnique Montreal, Montreal, Canada. <br>
      Slides: <a href="https://xinychen.github.io/slides/MF_TF_SFR.pdf">
        Low-rank matrix and tensor factorization for speed field reconstruction</a>.
      <br>
    </p>
</ul>

<h2>2022</h2>
<ul>
  <li>
    <p> May 24, 2022: IVADO Project Workshop, Montreal, Canada. <br>
      Slides: <a href="https://xinychen.github.io/slides/phd_project_22summer.pdf">
        Spatiotemporal traffic data imputation and forecasting with tensor learning</a>.
      <br>
    </p>
</ul>

<h2>2021</h2>
<ul>
  <li>
    <p> March 18, 2021: <a href="https://www-labs.iro.umontreal.ca/~grabus/courses/ift6760a-w21.html">
      IFT 6760A: Matrix and tensor factorization techniques for machine learning</a>, University of Montreal & Mila lab. <br>
      Slides: <a href="https://doi.org/10.5281/zenodo.4693404">
        Bayesian temporal factorization for multidimensional time series prediction</a>.
      <br>
    </p>
</ul>

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