• What's New
  • 08/2020: serve as PC member for AAAI'21, IJCAI'21, PAKDD'21.
  • 08/2020: teach Data Structure in Fall'20.

  • Introduction
  • I am an assistant professor in the School of Computer Science at the University of Oklahoma. From 2017-2020 I was an assistant professor in the Department of Computer Science at the University of Wyoming. In 2017 I received my Ph.D. degree from the University of Kansas. Here is my CV.
  • My research interests lie in machine learning and its interactions with fairness, privacy and security. Currently, we are investigating a trade-off between algorithmic fairness and data privacy, i.e., how to learn fair models with restricted access to private data? We are grateful to be partly funded by NSF.
  • To Prospective Students

  • Teaching
  • Fall 2020. CS2413: Data Structure

  • Selected Works
  • [UAI'16] Chao Lan, Jianxin Wang and Jun Huan. Towards a theorectical understanding of negative transfer in collective matrix factorization. Conference on Uncertainty in Artificial Intelligence, 2016.
  • Recent Works
  • On Private Fair Learning
  • [CIKM'20] Yijun Liu and Chao Lan. Active query of private sensitive demographic data for learning fair models. Conference on Information and Knowledge Management, 2020. [code]
  • [PPAI'20] Hui Hu and Chao Lan. Inference attack and defense on the distributed private fair machine learning framework. AAAI Workshop on Privacy-Preserving Artificial Intelligence, 2020. [code]
  • [ICDM'19] Hui Hu, Yijun Liu, Zhen Wang and Chao Lan. A distributed fair machine learning framework with private demographic data protection. International Conference on Data Mining, 2019. [code] [data]
  • On Multi-View Anomaly Detection
  • [IJCAI'20] Zhen Wang and Chao Lan. Towards a hierarchical Bayesian model of multi-view anomaly detection. International Joint Conference on Artificial Intelligence, 2020. [code]
  • [ICBK'19] Zhen Wang, Suresh Muknahallipatna, Maohong Fan and Chao Lan. Inductive semi-supervised multi-view anomaly detection via probabilistic modeling. Int. Conf. Big Knowledge, 2019.
  • Other Topics
  • [ICTAI'19] Austin Okray, Hui Hu and Chao Lan. Fair kernel regression via fair feature embedding in kernel space. International Conference on Tools with Artificial Intelligence, 2019.
  • [ICTAI'19] Dheeraj Bhaskaruni, Hui Hu and Chao Lan. Improving prediction fairness via model ensemble. International Conference on Tools with Artificial Intelligence, 2019.
  • [IJCNN'19] Zhen Wang, Suresh Muknahallipatna, Maohong Fan, Austin Okray and Chao Lan. Music classification using an improved CRNN with multi-directional spatial dependencies in both time and frequency dimensions. International Joint Conference on Neural Network, 2019.
  • [ICPR'18] Dheeraj Bhaskaruni, Fiona Moss and Chao Lan. Estimating prediction qualities without ground truth: A revisit of the reverse testing framework. Int. Conf. Pattern Recognition, 2018.
  • [WWW'19] Fei Wu, Xiaoyuan Jing, Jun Zhou, Yimu Ji, Chao Lan, Qinghua Huang and Ruchuan Wang. Semi-supervised multi-view individual and sharable feature learning for webpage classification. The World Wide Web Conference, 2019.
  • [GlobalSIP'19] Zhuo Li, Zhenlong Xiao and Chao Lan. Anomalous sensor detection based on nonlinear graph filter. Global Conf. Signal and Information Processing, 2019.

  • Current Students
  • Yiting Cao, PhD student. (BS,MS:CWRU)

  • To Prospective Students
  • If you are applying to graduate school, I have funded research openings for motivated applicants who are currently studying in U.S., have good knowledge in probability and sufficient programming skills, and are majored in computer science, eletrical engineering, math, statistics or physics. If you are interested, please send me CV and transcripts. If you are on campus, just come to see me at DEH 341.
  • If you are an OU undergraduate student interested in gaining research experience with me, please consider doing so through official programs such as independent study, HERE or NSF REU. We look for highly motivated students with sufficient machine learning background and programming skills. Our prior undergraduate research assistants published papers, selected as finalist of national women-in-computing award, and recieved poster award at local event. Feel free to approach me at DEH 341.

  • Graduated Students
  • Zhen Wang, PhD, UWyo.
  • Dheeraj Bhaskaruni, MS, UWyo.

  • Contact
  • Office: DEH 341
  • Phone: (405) 325-5735