李卓麟,，男,，博士,。2024年6月畢業(yè)于上海大學計算機應用技術專業(yè),，獲工學博士學位,。主要研究方向為時空數(shù)據挖掘及其在城市科學,、智能交通,、氣象科學等方面的應用,。近五年在國內外知名期刊發(fā)表科研論文10余篇,，包括Pattern Recognition,、Expert Systems with Applications、Engineering Applications of Artificial Intelligence等,。長期擔任Pattern Recognition,、Advanced Engineering Informatics、IEEE Transactions on Industrial Informatics,、Expert Systems with Applications等期刊審稿人,。

聯(lián)系方式：

工作郵箱：[email protected] 

主要學習與工作經歷：

2010.09-2014.07  山西農業(yè)大學，計算機科學與技術專業(yè),，學士

2016.09-2019.07  內蒙古科技大學,，計算機科學與技術專業(yè)，碩士

2019.09-2024.06  上海大學,，計算機應用技術專業(yè),，博士

2024.07-至今    安徽工程大學，計算機與信息學院,，計算機科學與技術系,，講師

學術網站：

ResearchGate: https://www.researchgate.net/profile/Zhuolin-Li-lizhuolin

ORCID: https://orcid.org/my-orcid?orcid=0000-0002-5050-654X

谷歌學術：https://scholar.google.com/citations?user=rUSp6igAAAAJ&hl=en

Scopus ID：https://www.scopus.com/authid/detail.uri?authorId=57212510411

參與項目：

[1] 國家重點研發(fā)項目《海洋大數(shù)據分析與預測技術研究》(2016YFC1401902)

[2] 國家重點研發(fā)項目《基于大數(shù)據和人工智能的海洋環(huán)境快速預報技術研究與應用》(2021YFC3101603)

發(fā)表論文：

[1] ZhuoLin Li, Gao Wei Zhang, Jie Yu, Ling Yu Xu. Dynamic Graph Structure Learning for Multivariate Time Series Forecasting[J]. Pattern Recognition, 2023: 109423.(SCI，中科院一區(qū),，期刊推薦)

[2] ZhuoLin Li, Jie Yu, GaoWei Zhang, LingYu Xu. Dynamic spatio-temporal graph network with adaptive propagation mechanism for multivariate time series forecasting[J]. Expert Systems with Applications, 2023, 216: 119374. (SCI,，中科院一區(qū))

[3] ZhuoLin Li, ZiHeng Gao, GaoWei Zhang, JingJIng Liu, LingYu Xu. Dynamic Personalized Graph Neural Network with Linear Complexity for Multivariate Time Series Forecasting. Engineering Applications of Artificial Intelligence. 2024, 127: 107291.(SCI，中科院二區(qū))

[4] Zhuolin Li, Ziheng Gao, XiaoLin Zhang, GaoWei Zhang, Lingyu Xu. Time-aware Personalized Graph Convolutional Network for Multivariate Time Series Forecasting. Expert Systems with Applications. 2024, 240: 122471. (SCI,，中科院一區(qū))

[5] ZhuoLin Li, Jie Yu, XiaoLin Zhang, LingYu Xu, BaoGang Jin. A Multi-Hierarchical attention-based prediction method on Time Series with spatio-temporal context among variables[J]. Physica A: Statistical Mechanics and its Applications, 2022, 602: 127664. (SCI,，中科院三區(qū))