Directory profile for Dr. Runlong Yu

Picture of Dr. Runlong Yu
Contact
  • 2124 Cyber Hall
  • Phone (205) 348-2172
  • Email
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Dr. Runlong Yu

Assistant Professor

Contact

  • 2124 Cyber Hall
  • phone (205) 348-2172
  • Email

Education

  • B.Eng., Computer Science, University of Science and Technology of China, 2017
  • Ph.D., Computer Science, University of Science and Technology of China, 2023

I am an Assistant Professor in the Department of Computer Science at The University of Alabama and an ALAAI Faculty Fellow for Frontier AI. Previously, I was a Postdoctoral Associate at the University of Pittsburgh. I earned my Ph.D. and B.Eng. in Computer Science from the University of Science and Technology of China (USTC). My research focuses on AI for open-world scientific discovery in complex natural systems. I develop AI methods to learn from limited data, reason with scientific knowledge, uncover hidden structures and mechanisms, and generate interpretable and transferable scientific insights. My work spans generative AI, foundation models, physics-guided machine learning, neural operators, geospatial intelligence, and computer vision, with applications in hydrology, aquatic systems, wildfire science, climate and agriculture, remote sensing, environmental extremes, and turbulence and flow simulation. At UA, I lead the AI for Science Lab and welcome students and collaborators interested in advancing AI for scientific discovery.

Affiliated Areas
Computer Science

Selected Publications

  • Yu, R., Qiu, C., Ladwig, R., Hanson, P., Xie, Y., Jia, X., “Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science,” Proceedings of the AAAI Conference on Artificial Intelligence, 39(27), 28548–28556, 2025.
  • Yu, R., Xie, Y., Jia, X., “Environmental Computing as a Branch of Science,” Communications of the ACM, 68(7), 92–94, 2025.
  • Yu, R., Qiu, C., Ladwig, R., Hanson, P.C., Xie, Y., Li, Y., Jia, X., “Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations,” Proceedings of the IEEE International Conference on Data Mining (ICDM), 580–589, 2024.
  • Yu, R., Xu, X., Ye, Y., Liu, Q., Chen, E., “Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction,” Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 3151–3161, 2023.
  • Yu, R., Liu, Q., Ye, Y., Cheng, M., Chen, E., Ma, J., “Collaborative List-and-Pairwise Filtering from Implicit Feedback,” IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(6), 2667–2680, 2022.

Awards and Honors

  • First Prize, IEEE ICDM Best BlueSky Paper Award, Nov. 2025
  • Champion, CCF BDCI Fighting Epidemics Big Data Charity Challenge, Jan. 2021
  • China National Scholarship, Dec. 2019
  • KDD CUP Regular ML Track, PaddlePaddle Special Award, Aug. 2019
  • First Prize, Chinese Physics Olympiad, Oct. 2012

The University of Alabama     |     Lee J. Styslinger Jr. College of Engineering