赵峰

访问学者

H指数:0

被引数:0

个人简介

"u赵峰,男，工学博士，教授，山东工商学院首批“近知学者”青年专家，硕士研究生导师，清华大学自动化系访问学者，美国北卡罗来纳大学教堂山分校医学影像中心访问学者。现任山东省高等学校黄河文化与生态保护数字智能技术协同创新中心主任，烟台市医学影像智能处理工程研究中心主任，山东工商学院数智赋能产业创新研究院负责人，烟台市数据赋能技术示范科普团队负责人，中国图学学会大数据专委会委员、中国人工智能学会粒计算与知识发现专委会委员、中国人工智能学会知识工程与分布智能专委会委员、山东省计算机学会理事、山东省人工智能学会理事。荣获“山东省优秀学士学位论文”指导教师、“山东省优秀硕士学位论文”指导教师、山东工商学院“凤凰拔尖人才”、“科研标兵”、“最美优秀教师”、“优秀共产党员”等称号。\n主要研究方向包括：人工智能、机器学习、医学图像分析、数据分析与预测。主持国家自然科学基金面上项目2项、山东省自然科学基金面上项目2项、山东省研究生教育优质课程建设项目1项、中央引导地方科技发展资金项目1项、山东省高等学校“青年创新人才引育计划”项目1项，在《Knowledge-Based Systems》、《IEEE Transactions on Biomedical Engineering》、《自动化学报》等国内外学术期刊上发表论文40余篇，其中SCI检索30余篇；出版学术专著1部；获山东省技术发明奖二等奖1项（首位）、山东高等学校优秀科研成果奖二等奖、三等奖各1项（首位）；获山东省教学成果奖一等奖、全国煤炭行业教学成果奖特等奖各1项（第2位）。\nu联系方式:E-mail: zhaofeng1016@126.com, 个人网址：www.sdtbuzhaofeng.com\nu教育经历\n[1]2005-3至2008-3, 西安电子科技大学, 计算机应用技术, 博士,\n[2]2002-7至2005-3, 西安电子科技大学, 计算机应用技术, 硕士,\n[3]1993-7至1997-7, 曲阜师范大学, 数学教育, 学士\nu工作经历\n[1]2015-4至2016-4, 美国北卡罗来纳大学教堂山分校, 生物医学影像研究中心（BRIC）, 访问学者\n[2]2010-9至2011-9, 清华大学, 自动化系, 访问学者\n[3]2008-7至现在, 山东工商学院, 计算机科学与技术学院, 教授\n[4]1997-7至2008-7, 济南大学, 理学院, 讲师\nu科研项目（主持）\n[1] 基于fMRI/EEG多模态特征融合的抑郁症自杀风险预测研究；No: 62176140;国家自然科学基金面上项目，2022.01-2025.12\n[2]多源多模态图像特征融合研究及在自闭症早期诊断中的应用；No：61773244；国家自然科学基金面上项目， 2018.01-2021.12\n[3] 基于增量式多核学习的颅脑CT图像病理诊断语义标注研究；No: 2015ZRB01675; 山东省自然科学基金项目， 2015-2017\n[4] KPCA在线学习及在人脸识别中的应用; No: ZR2011FM035; 山东省自然科学基金项目， 2011-2014.\n[5]随机过程，2021年山东省研究生教育优质课程建设项目，课程负责人, 2022-2023.\n[6] 实景三维辅助决策关键技术研究及示范推广；No.YDZX2022093 2022年中央引领地方（山东省）科技发展资金项目，2023.01-2024.12\n[7] 面向智慧全息路口的多传感器融合感知与交通信号优化关键技术研究及应用示范；No.2023XDRH001；烟台市科技创新发展计划（校地融合类），2023.01-2025.12.\nu学术论文（第一或通讯*）\n[1] Zhao F, Wang X, Li X, et al. A hybrid medium-long-term photovoltaic power forecasting model based on symplectic geometry mode decomposition and Mamba[J]. Energy Reports, 2025, 14: 2658-2669.\n[2] Zhao F, Liu M, Gao Y, et al. Personalized similarity regression models based on maximum correntropy criterion for stock series prediction[J]. Knowledge and Information Systems, 2025, 67(7): 5925-5945.\n[3] Wen Jiang, Mengyang Liu, Mingyan Xu, Shuoru Chen, Kai Shi, Pingping Liu, Caiming Zhang, Feng Zhao*. New Reinforcement Learning based on Representation Transfer for Portfolio Management. Knowledge-Based Systems. 2024.3. (JCR: Q1, IF: 8.8)\n[4] Feng Zhao, Ke Lv, Shixin Ye, Xiaobo Chen, Hongyu Chen, Sizhe Fan, Ning Mao，Yande Ren. Integration of temporal & spatial properties of dynamic functional connectivity based on two-directional two-dimensional principal component analysis for disease analysis. PeerJ. 2024.2. (JCR: Q2, IF: 2.7)\n[5] Na Li, Jinjie Xiao, Ning Mao, Dapeng Cheng, Xiaobo Chen,Yuan Li, Zhenghao Shi, Feng Zhao*. Joint learning of multi-level dynamic brain networks for autism spectrum disorder diagnosis. Computers in Biology and Medicine. 2024.1. (JCR: Q1, IF: 7.7)\n[6] Feng Zhao, Fan Feng, Shixin Ye , Yanyan Mao, Xiaobo Chen,Yuan Li,Mao Ning,MingLi Zhang. Multi-head self-attention mechanism-based global feature learning model for ASD diagnosis. Biomedical Signal Processing and Control. 2024.1. (JCR: Q2, IF: 5.1)\n[7] Feng Zhao, Shixin Ye, Mingli Zhang, Ke Lv, Xiaoyan Qiao, Yuan Li, Ning Mao, Yande Ren, Meiying Zhang. Multi-classifier fusion base on belief-value for the diagnosis of neuropsychiatric disorders. Frontiers in Human Neuroscience. 2023.10. (JCR: Q2, IF: 2.9)\n[8] Feng Zhao, Jinyu Hao , Huanjia Zhang, Xiaoning Yu, Zhenzhen Yan, Fucun Wu. Quality Recognition Method of Oyster based on U-Net and Random Forest. Journal of Food Composition and Analysis. 2023.10. (JCR: Q2, IF: 4.3)\n[9] Hongxin Pan, Yanyan Mao, Peiqiang Liu, Yuan Li, Guanglan Wei, Xiaoyan Qiao, Yande Ren, Feng Zhao*. Extracting transition features among brain states based on coarse-grained similarity measurement for autism spectrum disorder analysis. Medical Physics. 2023.03. (JCR: Q2, IF: 4.506)\n[10] Feng Zhao, Tianyu Gao, Zhi Cao, Xiaobo Chen, Yanyan Mao, Ning Mao and Yande Ren. Identifying depression disorder using multi-view high-order brain function network derived from electroencephalography signal. Frontiers in Computational Neuroscience. 2022.10.（JCR:Q2, IF: 3.387）\n[11] Feng Zhao, Hongxin Pan,Na Li, Xiaobo Chen, Yuan Li, Haicheng Zhang, Ning Mao and Yande Ren. High-Order Brain Functional Network Based on EEG for Diagnosis of Major Depressive Disorder. Frontiers in Neuroscience. 2022.08.（JCR:Q2,IF: 5.152）\n[12] Feng Zhao, Yan Lu, Xinning Li, Lina Wang, Yingjie Song, Deming Fan, Caiming Zhang, Xiaobo Chen. Multiple Imputation Method of Missing Credit Risk Assessment Data Based on Generative Adversarial Networks. Applied Soft Computing. 2022.07.（JCR:Q1, IF: 8.263）\n[13] Feng Zhao, Xinning Li, Yating Gao, Ying Li, Zhiquan Feng, Caiming Zhang. Multi-layer features ablation of BERT model and its application in stock trend prediction. Expert Systems with Applications. 2022.06.（JCR:Q1,IF: 8.665）\n[14] Feng Zhao,Na Li, Hongxin Pan, Xiaobo Chen, Yuan Li, Haicheng Zhang, Ning Mao, Dapeng Cheng.Multi-view feature enhancement based on self-attention mechanism graph convolutional network for autism spectrum disorder diagnosis. Frontiers in Human Neuroscience. 2022.07.（JCR:Q2,IF: 3.473）\n[15]Feng Zhao, Xiangfei Zhang, Kim-Han Thung, Ning Mao, Seong-Whan Lee, Dinggang Shen. Constructing Multi-view High-order Functional Connectivity Networks for Diagnosis of Autism Spectrum Disorder.IEEE Transactions on Biomedical Engineering, 2022.（JCR：Q1, IF: 4.538）\n[16] Feng Zhao; Zhongwei Han; Dapeng Cheng; Ning Mao; Xiaobo Chen; Yuan Li; Deming Fan; Peiqiang Liu; Hierarchical Synchronization Estimation of Low- and High-Order Functional Connectivity Based on Sub-Network Division for the Diagnosis of Autism Spectrum Disorder, Frontiers in Neuroscience, 2022. （JCR：Q2, IF: 4.667）\n[17] Xie Q, Zhang X, Rekik I, Chen X, Mao N, Shen D, Zhao Feng*. Constructing high-order functional connectivity network based on central moment features for diagnosis of autism spectrum disorder. PeerJ, 2021.（JCR：Q2, IF: 2.984）\n[18]Feng Zhao, Yating Gao, Xinning Li, Zhiyong An, Shiyu Ge, Caiming Zhang. A similarity measurement for time series and it"