Keith G. Mills

Assistant Professor

Contact

keith.mills@lsu.edu
Office 3270A
Patrick F. Taylor Hall

Educational Background

Ph.D. Software Engineering and Intelligent Systems, University of Alberta, 2025

M.Sc. Computer Engineering, University of Alberta, 2020

B.Sc. Computer Engineering with Distinction, University of Alberta, 2018

Keith Mills

  • CSC 7344: Foundational AI
  • CSC 4700/HNRS 3025: AI & LLM Development
  • CSC 4444: Artificial Intelligence
  • CSC 2730: Data Science and Analytics
  • Artificial Intelligence
  • Machine Learning
  • Generative Models
  • Data Mining
  • Knowledge Extraction and Representation
  • Computer Vision
  • Kim, J. H., Thai, N., Saha Dip, S., Lao, D., & Mills, K. G. (2026, March). Naive PAINE: Lightweight text-to-image generation improvement with prompt evaluation. arXiv preprint arXiv:2603.12506.
  • Lu, S., Liu, B., Mills, K. G., He, J., & Niu, D. (2024, July). EiG-Search: Generating edge-induced subgraphs for GNN explanation in linear time. In International Conference on Machine Learning (ICML).
  • Mills, K. G., Han, F. X., Salameh, M., Lu, S., Zhou, C., He, J., Sun, F., & Niu, D. (2024, June). Building optimal neural architectures using interpretable knowledge. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 5726-5735).
  • Lu, S., Mills, K. G., He, J., Liu, B., & Niu, D. (2024, May). GOAt: Explaining graph neural networks via graph output attribution. In International Conference on Learning Representations (ICLR).
  • Han, F. X., Mills, K. G., Chudak, F., Riahi, P., Salameh, M., Zhang, J., Lu, W., Jui, S., & Niu, D. (2023, April). A general-purpose transferable predictor for neural architecture search. In SIAM International Conference on Data Mining (SDM) (pp. 721-729).
  • Lu, S., Liu, B., Mills, K. G., Jui, S., & Niu, D. (2022, April). R5: Rule discovery with reinforced and recurrent relational reasoning. In International Conference on Learning Representations (ICLR).
  • Mills, K. G., Han, F. X., Zhang, J., Rezaei, S. S. C., Chudak, F., Lu, W., Lian, S., Jui, S., & Niu, D. (2021, November). Profiling neural blocks and design spaces for mobile neural architecture search. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM).
  • Mills, K. G., Han, F. X., Salameh, M., Rezaei, S. S. C., Kong, L., Lu, W., Lian, S., Jui, S., & Niu, D. (2021, November). L2NAS: Learning to optimize neural architectures via continuous-action reinforcement learning. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM)
  • 2026: ÃÛÌÒAPP College of Engineering Longwell Award for Instructor Excellence
  • 2025: George Walker Award for Best Doctoral Thesis
  • 2024: Alberta Innovates Graduate Student Scholarship
  • 2023/2022: Floyd Derkat Graduate Award in Artificial Intelligence and Machine Learning
  • 2022/2019: Alberta Graduate Excellence Scholarship
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