Kaiyuan Zhang is a research-based master in the Computer Science Department at The University of Texas at Dallas, works with Professor Wei Yang.

New!! I’m looking for a Ph.D. position actively! If you are interested in working with me, please do not hesitate to send me an email directly.

Research Interests

  • Graph representation learning
  • Software engineering for Machine learning
  • Visual analytics of Large-scale Graph

Research Experience

  • Department of Computer Science, University of Illinois at Urbana-Champaign
    Advisor: Prof. Tao Xie, May 2019 - Present.
  • Department of Computer Science, The University of Texas at Dallas
    Advisor: Prof. Wei Yang, Nov 2018 - Present.
  • State Key Laboratory of CAD&CG, Zhejiang University
    Advisor: Prof. Wei Chen, Feb 2017 - Aug 2018.


  • Visualizing Large-scale High-dimensional Data via Hierarchical Embedding of KNN Graphs. (Revising)

  • DRGraph: An Efficient Graph Layout Algorithm for Large-scale Graphs by Dimensionality Reduction. (Revising)

  • Enhancing statistical charts: toward better data visualization and analysis.
    X. Luo, Y. Yuan, K. Zhang, J. Xia, Z. Zhou, L. Chang, T. Gu.
    Journal of Visualization (JOV), 2019.
    [bib] [Paper].

What’s New

  • I’m looking for a Ph.D. position.
  • 07/2019, GraphTour of Neo4j at Chicago.
  • 07/2019, Got Neo4j Certified Professional.
  • 05/2019, interned at UIUC.
  • 08/2018, enrolled in UTDallas as a CS graduate student.
  • 02/2017, interned at Zhejiang University.
  • 11/2016, received National Scholarship :-)

Selected Awards

  • Excellent Bachelor Thesis Award, 2017
    Awarded to students with excellent graduate thesis, top ~5% students.
  • National Scholarship, 2016
    Highest level of scholarship set by Ministry of Education of China, top ~1% students.
  • Third Place Award in National College Students Cloud Computing Application Innovation Contest, 2016
    Hold by Ministry of Education, Science and Technology Development Center of China.
  • Second Place Province Award in China Mathematical Contest in Modeling, 2015
    Out of 9773 teams (29319 students).