Chao Lan

I am an assistant professor in the School of Computer Science, Gallogly College of Engineering, at the University of Oklahoma (OU). I am also affiliated with the Data Science and Analytics Institute at OU.
I work on machine learning. My research explores those provable probabilistic natures of a learning task and exploits them to better understand or improve task efficiency and trustworthiness such as model fairness, data privacy and learner security. My current research focuses on randomized learning.
I received my Ph.D. degree from the University of Kansas. Here is my CV.

What's New
03/2024: I'll serve as an Area Chair for NeurIPS'24.
01/2024: I'll serve as a reviewer for UAI'24.
12/2023: I'll serve as a reviewer for ICML'24.
08/2023: Shayan received the Gallogly College of Engineering Scholarship. Congratulations.
05/2023: I'm selected as a Top Reviewer for UAI'23.
05/2023: Yiting successfully defended her doctoral dissertation and graduated. Congratulations!
03/2023: I'll serve as an associate editor for ACM Transactions on Probabilistic Machine Learning.
02/2023: I'm selected as a Top Reviewer for AISTATS'23.

Selected Publications
[ICML'22] Yiting Cao and Chao Lan. A model-agnostic randomized learning framework based on random hypothesis subspace sampling. in Proc. of the 39th International Conference on Machine Learning (ICML), 2022.
[UAI'22] Yiting Cao and Chao Lan. Active approximately metric-fair learning. in Proc. of the 38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022.
[UAI'16] Chao Lan, Jianxin Wang and Jun Huan. Towards a theorectical understanding of negative transfer in collective matrix factorization. in Proc. of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016.
Ph.D. Students
Shayan Shafaei, 2022-
Luyuan Yang, 2023-