The paper “Statistical Inferences for Complex Dependence of Multimodal Imaging Data”, co-authored by Prof. Jinyuan Chang, Associate Prof. Jing He, and doctoral student Mingcong Wu from the Joint Laboratory of Data Science and Business Intelligence at Southwestern University of Finance and Economics (SWUFE), in collaboration with Prof. Jian Kang from 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.

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

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 the Joint Laboratory of Data Science and Business Intelligence at Southwestern University of Finance and Economics, in collaboration with Prof. Xinghao Qiao and Prof. Qiwei Yao from 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.

The paper “Modeling Matrix Time Series via a Tensor CP-Composition”, co-authored by Prof. Jinyuan Chang, Jing He, and doctoral student Lin Yang from the Joint Laboratory of Data Science and Business Intelligence at Southwestern University of Finance and Economics, along with Prof. Qiwei Yao from the London School of Economics and Political Science, has been officially accepted by the Journal of the Royal Statistical Society: Series B, one of the top international journals in the field of statistics.