Chang Awarded the First Prize of the 19th Fok Ying Tung Education Foundation Higher Education Youth Science Award

Recently, a ceremony to present the 19th Fok Ying Tung Education Foundation (FYTEF) Higher Education Youth Science Award and Education and Teaching Award was held in Nanjing, Jiangsu. According to the decision made by the expert review organized by the Ministry of Education and the joint meeting of the Foundation’s Board of Directors and Advisory Committee, a total of 10 teachers nationwide were awarded the First Prize of Fok Ying Tung Education Foundation Higher Education Youth Science Award and Education and Teaching Award (5 in each category). Professor Jinyuan Chang was awarded the First Prize of the Youth Science Award.

Chang’s Paper Accepted by JASA

The paper “On the Modeling and Prediction of High-Dimensional Functional Time Series”, co-authored by Prof. Jinyuan Chang from our team, Assistant Prof. Qin Fang of the University of Sydney, Prof. Xinghao Qiao of the University of Hong Kong, and Prof. Qiwei Yao of the London School of Economics and Political Science, has been officially accepted by the Journal of the American Statistical Association, one of the top journals in the field of statistics.

Chang Awarded Funding by NSFC

The National Natural Science Foundation of China (NSFC) has recently announced the evaluation results of its Major Programs for 2024. The Major Program titled “Statistical Management Theory of Large-Scale Business Scenarios”, led by Prof. Jinyuan Chang from the Joint Laboratory of Data Science and Business Intelligence at Southwestern University of Finance and Economics (SWUFE), has been officially approved. The project is a joint effort with Prof. Weidong Liu of Shanghai Jiao Tong University, Researcher Xinyu Zhang from the Academy of Mathematics and Systems Science of the Chinese Academy of Sciences, Prof. Gang Kou of SWUFE, and Prof. Hansheng Wang of Peking University.

He Awarded Funding by NSFC

The National Natural Science Foundation of China recently announced the project evaluation results for 2024. The General Project titled “Ultra High-Dimensional (Conditional) Independence Tests and Their Applications in Economics”, led by Prof. Jing He, has been officially approved for funding.

Chang’s Paper Accepted by AoS

The paper “Edge Differentially Private Estimation in the β-Model via Jittering and Method of Moments”, co-authored by Prof. Jinyuan Chang and doctoral student Qiao Hu from our team, Prof. Eric D. Kolaczyk of McGill University (Canada), Prof. Qiwei Yao of the London School of Economics and Political Science (UK), and Assistant Prof. Fengting Yi of Yunnan University, has been officially accepted by the Annals of Statistics, one of the world’s leading journals in the field of statistics.

Huang’s Paper Accepted by Contemporary Economics Doctoral Innovation Project

Congratulations to our postdoctoral fellow Dr. Guanglin Huang, for his paper “Research on High-Dimensional Dynamic High-Order Moment Investment Portfolio Based on Factor Structure: Optimization and Semi-Parametric Estimation” (supervised by Prof. Wanbo Lu) has been selected for the 2023 Contemporary Economics PhD Innovation Project!

Chang and He’s Paper Accepted by JASA

The paper “Statistical Inferences for Complex Dependence of Multimodal Imaging Data”, co-authored by Prof. Jinyuan Chang, Prof. Jing He, and doctoral student Mingcong Wu from our team, and Prof. Jian Kang of the University of Michigan, has been officially accepted by Journal of the American Statistical Association, one of the most prestigious journals in the field of statistics.

Chang’s Paper Accepted by Bernoulli

The paper “Central Limit Theories for High-Dimensional Dependent Data”, co-authored by Prof. Jinyuan Chang from our team, Prof. Xiaohui Chen of the University of Illinois at Urbana-Champaign, and Ph.D. student Mingcong Wu of Southwestern University of Finance and Economics, has been officially accepted by Bernoulli, an internationally renowned academic journal in probability and statistics.

Chang’s Paper Accepted by JoE

The paper “An Autocovariance-Based Learning Framework for High-Dimensional Functional Time Series”, co-authored by Prof. Jinyuan Chang and postdoctoral researcher Cheng Chen from our team, and Prof. Xinghao Qiao and Prof. Qiwei Yao of the London School of Economics and Political Science, has been officially accepted by the Journal of Econometrics, a leading international journal in the field of econometrics.