Dr. Qi Li

Assistant Professor of Computer Science
qli2@fisk.edu

Education: 

  • Ph.D. in Computer Science, Auburn University, Auburn, Alabama, 2024
  • M.S. in Computer Science and Software Engineering, Auburn University, Auburn, Alabama, 2020
  • B.S. in Computer Science and Software Engineering, Southeast University, Nanjing, China, 2006

 

Brief Bio sketch: I am an Assistant Professor of Computer Science at Fisk University. I received his Ph.D. in Computer Science from Auburn University in 2024, where I was advised by Dr. Wei-Shinn (Jeff) Ku and Dr. Anh Nguyen. My research spans artificial intelligence, neural network robustness and interpretability, human motion analysis, generative models, and interdisciplinary applications in healthcare and bioinformatics. My recent work includes fine-grained sports action recognition, AI-based human motion analysis, large language models for functional genomics, and computational methods for predicting disease progression. My research has been published in venues including CVPR, ACCV, IEEE BigData, IEEE Access, and Briefings in Bioinformatics. My work at ACCV received the Huawei Best Application Paper Honorable Mention. At Fisk University, Dr. Li teaches courses including Introduction to Computing, Theory of Computation, Natural Language Processing and Applications, and Programming Languages. He mentors undergraduate researchers in machine learning, artificial intelligence, and bioinformatics and participates in NSF funded research.

Selected Publications:

  • Li, Q., Nichols, C., Welner, R. S., Chen, J. Y., Ku, W. S., & Yue, Z. (2026). GOLDEN fusion: A graph-oriented learning with domain-embedding network fusion for generating super gene sets in functional genomics. Briefings in Bioinformatics, 27(3), bbag244.
  • Li, Q., Chiu, T. C., Huang, H. W., Sun, M. T., & Ku, W. S. (2024). VideoBadminton: A Video Dataset for Badminton Action Recognition. IEEE International Conference on Big Data (BigData).
  • Chen, P., Li, Q., Biaz, S., Bui, T., & Nguyen, A. (2022). gScoreCAM: What Objects Is CLIP Looking At? Asian Conference on Computer Vision (ACCV). Oral Presentation.
  • Li, Q., Mai, L., Alcorn, M. A., & Nguyen, A. (2020). A Cost-Effective Method for Improving and Re-purposing Large, Pre-trained GANs by Fine-tuning Their Class-Embeddings. Asian Conference on Computer Vision (ACCV). Huawei Best Application Paper Honorable Mention.
  • Alcorn, M. A., Li, Q., Gong, Z., Wang, C., Mai, L., Ku, W. S., & Nguyen, A. (2019). Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).