• 教授课程
• 简历/背景
• 研究方向
• 研究项目
• 研究成果
• 获奖信息
• 社会活动

机器学习
运营量化决策与分析

教育背景
博士，工业工程与管理，俄克拉荷马州立大学，2019.08-2023.08
学士，经济统计学，中国人民大学，2015.09-2019.07

基于工业应用的统计与机器学习模型，智能医疗系统数据管理，数据驱动的先进制造监控与控制，基于机器学习的电力系统优化

Li, Y., Shi, Z., & Liu, C. (2023). Transformer-enabled Generative Adversarial Imputation Network with Selective Generation (SGT-GAIN) for Missing Region Imputation, IISE Transactions. 1-13.
Li, Y., Zhao, C., & Liu, C. (2023). Model-Informed Generative Adversarial Network (MI-GAN) for Learning Optimal Power Flow. IISE Transactions.
Li, Y., Shi, Z., Liu, C., Tian, W., Kong, Z., & Williams, C. B. (2022). Augmented time regularized generative adversarial network (atr-gan) for data augmentation in online process anomaly detection. IEEE Transactions on Automation Science and Engineering, 19 (4), 3338-3355.
Li, Y., VanOsdol, J., Ranjan, A., & Liu, C. (2022). A multilayer network-enabled ultrasonic image series analysis approach for online cancer drug delivery monitoring. Computer Methods and Programs in Biomedicine, 213, 106505.
Li, Y., Dogan, A., & Liu, C. (2022, August). Ensemble Generative Adversarial Imputation Network with Selective Multi-Generator (ESM-GAIN) for Missing Data Imputation. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (pp. 807-812). IEEE.
Li, Y., Zhao, C., & Liu, C. (2022). Solving Non-linear Optimization Problem in Engineering by Model- Informed Generative Adversarial Network (MI-GAN), The IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 198-205). IEEE.

Doctoral Phoenix Award, Oklahoma State University, 2023
SDM23 Doctoral Student Travel Scholarship, SDM23, 2023
INFORMS 2022 Data Science Workshop Student Scholarship, INFORMS Annual Meeting, 2022
Roy and Virginia Dorrough Distinguished Graduate Fellowship, Oklahoma State University, 2021
Best Poster Award, BOOM Workshop, the 29th International Joint Conference on Artificial Intelligence (IJCAI), 2021

审稿人: ANOR，TASE，TPS，JIM，JCISE，Healthcare Analytics