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 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
  • Keith G. Mills, Mohammad Salameh, Ruichen Chen, Negar Hassanpour, Wei Lu and Di Niu. 鈥淨ua2SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models鈥�. In Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI-25).
  • Shengyao Lu, Bang Liu, Keith G. Mills, Jiao He and Di Niu. 鈥淓iG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time鈥�, accepted to the Forty-first International Conference on Machine Learning (ICML鈥�24).
  • Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun and Di Niu. 鈥淏uilding Optimal Neural Architectures using Interpretable Knowledge鈥�, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR鈥�24).
  • Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu and Di Niu. 鈥淕OAt: Explaining Graph Neural Networks via Graph Output Attribution鈥�, published in the 12th International Conference on Learning Representations (ICLR 2024).
  • Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun and Di Niu. 鈥淎utoGO: Automated Computation Graph Optimization for Neural Network Evolution.鈥� In Advances in Neural Information Processing Systems (NeurIPS 2023).
  • Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu and Shangling Jui. 鈥淎IO-P: Expanding Neural Performance Predictors Beyond Image Classification.鈥� In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23).
  • Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari Mamaghani, Mohammad Salameh, Wei Lu, Shangling Jui and Di Niu. 鈥淕ENNAPE: Towards Generalized Neural Architecture Performance Estimators.鈥� In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23).
  • Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui and Di Niu. 鈥淩5: Rule Discovery with Reinforced and Recurrent Relational Reasoning,鈥� published in the 10th International Conference on Learning Representations (ICLR 2022).
  • Keith G. Mills, Fred X. Han, Jialin Zhang, Seyed Saeed Changiz Rezaei, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. 鈥淧rofiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search.鈥� In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 鈥�21).
  • Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. 鈥淟2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.鈥� In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 鈥�21).
  • 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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