Chengfei Wang

(He, Him, His)
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Assistant Professor of Artificial Intelligence, Engineering
Main Building, 220P

Dr. Chengfei Wang is an assistant professor of artificial intelligence. He teaches courses in foundations of AI and analytics programming in Python. His research interests include the robustness problem of deep learning models applied in life-critical missions and business intelligence based on natural language analysis of customer reviews on social media. His research on the robustness of the computer vision model was published at the top-tier AI conference CVPR.

  • Robustness of the artificial intelligence and machine learning models
  • Artificial intelligence generated fake reviews detection

Selected Publications

Wang, Chengfei; Qin, Xiao; and Gupta, Ashish, "Developing App from User Feedback using Deep Learning" (2022). Proceedings of the 2022 Pre-ICIS SIGDSA Symposium. 11.

Longwei Wang*, Chengfei Wang*, Yupeng Li, and Rui Wang. "Improving robustness of deep neural networks via large-difference transformation." Neurocomputing 450 (2021): 411-419.

Alcorn, Michael A., Qi Li, Zhitao Gong, Chengfei Wang, Long Mai, Wei-Shinn Ku, and Anh Nguyen. "Strike (with) a pose: Neural networks are easily fooled by strange poses of familiar objects." In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 4845-4854. 2019.

  • Ph.D., Computer Science, Auburn University
  • M.S., Computer Science, Auburn University
  • M.S., Biophysics, University of Electronic Science and Technology of China
  • B.S., Biotechnology, University of Electronic Science and Technology of China