Zhongxing Zhang

Zhongxing Zhang

About

Hello! I’m Zhongxing Zhang, a Ph.D. student in Computer Science at the University of Minnesota (Twin Cities), where I am advised by Prof. Jaideep Srivastava. My research interests include Machine Learning, Natural Language Processing, and Computational Social Science, particularly in human behavior analysis and social computing. Prior to that, I received my Master and Bachelor degrees in Shandong University of Finance and Economics, where I was advised by Prof. Hui Liu.

Research Interests

  • Image Restoration: Innovating approaches to enhance image quality and recover image details.
  • Image Super-resolution: Developing algorithms for improving image resolution using low-rank prior and probability-inducing nuclear norm minimization.
  • Multimodality Data Analytics: Exploring techniques for multimodal data sources, including textual, visual, and behavioral data, to uncover complex patterns.
  • Computational Social Science: Leveraging computational models to analyze social behaviors, interactions, and networks, with applications in misinformation detection, social network analysis, and online content veracity classification.

Education

  • Ph.D. in Computer Science, University of Minnesota, Twin Cities, 2029 Expected
  • M.Eng. in Digital Media Technology, Shandong University of Finance and Economics, 2023
  • B.Eng. in Computer Science and Technology, Shandong University of Finance and Economics, 2018

Publications

  • Zhongxing Zhang, Hui Liu, Qiang Guo, et al. Single image super-resolution reconstruction using non-local low-rank prior. The 3rd International Conference on Machine Learning for Cyber Security, Guangzhou, China, 2020.10. (doi: 10.1007/978-3-030-62463-7 27)
  • Zhongxing Zhang, Hui Liu, Qiang Guo, et al. Super-resolution reconstruction using probability model combined with non-local low-rank prior. Journal of Computer-Aided & Computer Graphics, 2021.01. (doi: 10.3724/SP.J.1089.2021.18389)
  • Zhongxing Zhang, Hui Liu, Qiang Guo. Image restoration using probability-inducing nuclear norm minimization. The 29th IEEE International Conference on Image Processing, Bordeaux, France, 2022.10. (doi: 10.1109/ICIP46576.2022.9897237)
  • Jingqi Song, Hui Liu, Yuxiu Lin, Zhongxing Zhang. Medical images super-resolution based on similarity learning. The 2019 Asia Pacific Conference on Medical and Health Science, Seoul, South Korea, 2019.07. (doi: 10.1111/bcpt.13266)

Technical Skills

  • Programming Languages: Python, MATLAB, Java, C/C++, SQL, JavaScript, HTML/CSS
  • Developer Tools: PyCharm, Git, Visual Studio Code, Microsoft Visual Studio, Eclipse
  • Libraries: PyTorch, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn

Experience

  • Graduate Research Assistant
    • Conducted extensive experiments on image super-resolution and denoising using various datasets.
    • Developed innovative algorithms for image enhancement and reconstruction.
  • Volunteer Teacher
    • Taught multiple subjects including Chemistry, English, Mathematics, and Computer Science.
    • Organized environmental protection actions and public welfare activities.

Achievements and Awards

  • National Scholarship for Graduate Student
  • Postgraduate Research Scholarship
  • President Scholarship
  • Excellent Volunteer of China Western Volunteer Program
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