一、个人简介

杨宜澄博士，现任河北工业大学人工智能与数据科学学院讲师，硕士生导师。美国爱荷华州立大学智慧城市专业博士，近年主要从事大数据挖掘及机器学习与智慧城市交叉应用等方面的研究，以第一作者在数据挖掘TOP期刊 IEEE TKDE 等国际学术期刊发表论文数篇，引起国内外同行广泛关注。

二、教育经历

2022.01-2023.05， 美国爱荷华州立大学，计算机科学，硕士

2018.08-2021.12，美国爱荷华州立大学，智慧城市，博士

2016.06-2018.05，美国爱荷华州立大学，结构工程，硕士

2012.08-2016.05，美国爱荷华州立大学，土木工程，学士

三、科研论文

[1] Y. Yang, Y. Kwon, J. Kim, and I. Cho, 2023. Ultra Data-Oriented Parallel Fractional Hot-Deck Imputation with Efficient Linearized Variance Estimation, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 35(9), 9754 – 9768.

[2] Y. Yang, J. Kim, and I. Cho. Curing Incomplete Earthquake Catalog Data Using General-Purpose Ultra Data-Oriented Fractional Hot Deck Imputation, 12th National Conference on Earthquake Engineering, Salt Lake City, Utah, June 21 – July 1, 2022.

[3] Y. Yang and I. Cho, 2021. Multiple Target Machine Learning Prediction of Capacity Curves of Reinforced Concrete Shear Walls, Journal of Soft Computing in Civil Engineering, 5(4), 90 – 113.

[4] M. Bazroun, Y. Yang, and I. Cho, 2021. Flexible and Interpretable Generalization of Self-Evolving

Computational Materials Framework, Computers & Structures, 260, Article Number: 106706.

[5] Y. Yang, J. Kim, and I. Cho, 2020. Parallel Fractional Hot Deck Imputation and Variance Estimation for Big Incomplete Data Curing, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE),34(8), 3912 – 3926.

[6] I. Song, Y. Yang, J. Im, T. Tong, C. Halil, and I. Cho, 2019. Impacts of Fractional Hot-Deck Imputation on Learning and Prediction of Engineering Data, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 32(12), 2363 – 2373.

[7] Y. Yang, S. Yemmaleni, I. Song, and I. Cho, 2018. Cell Network-Based Formulas for Fast Determination of Stiffness Reduction of U-Shaped Core Shear Walls, Earthquake Spectra, 34(2), 867 – 892.

四、研究方向

大数据挖掘：缺失数据补全，高性能计算

人工智能：机器学习与智慧城市的交叉应用

五、科研项目

[1] 分数插补法与机器学习耦合的大数据缺失值补全的方法研究, 天津市教委, 2023.12-2026.12

六、招生信息

现招收硕士研究生，欢迎感兴趣的同学加入，请邮件联系：2023071@hebut.edu.cn