Chen Zhao, Ph.D.

Senior R&D Engineer

Chen Zhao, Ph.D. is a senior R&D engineer on Kitware’s Computer Vision Team located in Clifton Park, New York. He is part of the research team that is involved in establishing graph convolutional networks for activity recognition for one of our government customers. The innovative model utilizes balance theory to correctly aggregate and propagate the information across layers of a signed GCN mode. It handles the availability of both positive and negative relationships between actors.

Chen received his Ph.D. in computer science from the University of Texas at Dallas in 2021. In 2016 he received dual master’s degrees in computer science and biomedical science from The State University of New York at Albany and Albany Medical College, respectively. 

Education

Ph.D. in computer science from the University of Texas at Dallas, 2021

M.S. in computer science from The State University of New York at Albany, 2016

M.S. in biomedical science from Albany Medical College, 2016

Awards

Dissertation Research Award presented by the University of Texas at Dallas, 2021

Student Travel Award presented by the IEEE International Conference on Data Mining, 2020

Get to Know Chen

What made you want to become a Kitwarean? I was drawn to the research environment and the people.

What do you love most about what you do? I enjoy doing research that involves machine learning, data mining, and computer vision.

Share something interesting about yourself that is not on your resume. I love cooking, especially Chinese food, making new friends, and traveling.

Professional Associations & Service

  • Program committee member for the IEEE International Conference on Data Mining, 2021
  • Reviewer for the International Conference on Artificial Intelligence and Statistics, 2021
  • Program committee member for the ACM Conference on Knowledge Discovery and Data Mining, 2020 – 2021
  • Editorial manager/reviewer for the Journal of Big Data Research, 2020

 

Publications

Chen’s publication list is below. To see all of Kitware’s computer vision publications, please visit the Computer Vision Publications page.

  1. F. Mi, Z. Wang, C. Zhao, J. Guo, F. Ahmed, and L. Khan, "VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning," in 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2021. [URL]
  2. C. Zhao, F. Chen, and B. Thuraisingham, "Fairness-Aware Online Meta-learning," in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021. [URL]
  3. Z. Wang, Y. Chen, C. Zhao, Y. Lin, X. Zhao, H. Tao, Y. Wang, and L. Khan, "CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining," in Proceedings of the Web Conference 2021, 2021. [URL]
  4. C. Zhao, F. Chen, Z. Wang, and L. Khan, "A Primal-Dual Subgradient Approach for Fair Meta Learning," in 2020 IEEE International Conference on Data Mining (ICDM), 2020. [URL]
  5. C. Zhao, C. Li, J. Li, and F. Chen, "Fair Meta-Learning For Few-Shot Classification," in 2020 IEEE International Conference on Knowledge Graph (ICKG), 2020. [URL]
  6. C. Zhao and F. Chen, "Unfairness Discovery and Prevention For Few-Shot Regression," in 2020 IEEE International Conference on Knowledge Graph (ICKG), 2020. [URL]
  7. C. Zhao and F. Chen, "Rank-Based Multi-task Learning for Fair Regression," in 2019 IEEE International Conference on Data Mining (ICDM), 2019. [URL]
  8. J. Li, L. Miao, C. Zhao, W. Shaikh Qureshi, D. Shieh, H. Guo, Y. Lu, S. Hu, A. Huang, L. Zhang, C. Cai, L. Wan, H. Xin, P. Vincent, H. Singer, Y. Zheng, O. Cleaver, Z. Fan, and M. Wu, "CDC42 is required for epicardial and pro-epicardial development by mediating FGF receptor trafficking to the plasma membrane," Development, vol. 144, no. 9, pp. 1635-1647, May 2017. [URL]
  9. C. Zhao, H. Guo, J. Li, T. Myint, W. Pittman, L. Yang, W. Zhong, R. Schwartz, J. Schwarz, H. Singer, M. Tallquist, and M. Wu, "Numb family proteins are essential for cardiac morphogenesis and progenitor differentiation," Development, vol. 141, no. 2, pp. 281-295, Jan. 2014. [URL]

Bibliography generated 2021-08-20-09:00:07 (4671)