一、個(gè)人基本信息

張鵬飛，博士/博士后，副研究員，碩士生導(dǎo)師，長(zhǎng)期從事人工智能、機(jī)器學(xué)習(xí)、信息融合、醫(yī)工交叉等相關(guān)領(lǐng)域科研教學(xué)工作。主持國(guó)家自然青年基金1項(xiàng)，國(guó)家資助博士后研究計(jì)劃（B檔）1項(xiàng)，中國(guó)博士后面上基金1項(xiàng)，四川省科技廳面上項(xiàng)目1項(xiàng)；主研和參與國(guó)家重點(diǎn)研發(fā)計(jì)劃、國(guó)家自然科學(xué)基金面上項(xiàng)目和四川省重點(diǎn)研發(fā)5項(xiàng)；是ACM會(huì)員，CCF會(huì)員，CAAI會(huì)員，中國(guó)人工智能協(xié)會(huì)機(jī)器學(xué)習(xí)專委會(huì)通信委員，中國(guó)中醫(yī)藥信息學(xué)會(huì)人工智能分會(huì)理事，中國(guó)人工智能學(xué)會(huì)粒計(jì)算與知識(shí)發(fā)現(xiàn)專委會(huì)委員，四川省計(jì)算機(jī)學(xué)會(huì)青少年信息科技專委會(huì)，以及擔(dān)任四川省城鄉(xiāng)數(shù)智中醫(yī)委員會(huì)副秘書(shū)長(zhǎng)。在IEEE TNNLS、 IEEE TFS、ACM TKDD、ACM TIST、Information Fusion、Information Sciences、Knowledge-Based Systems、Applied Soft Computing、Engineering Applications of Artificial Intelligence、International Journal of Approximate Reasoning等國(guó)內(nèi)期刊發(fā)表文章40余篇，其中1篇入選ESI高被引，谷歌引用1200余次，H指數(shù)20。擔(dān)任擔(dān)任Information Fusion、IEEE TFS、Pattern Recognition、Information Sciences、Advanced Engineering Informatics、International Journal of Approximate Reasoning、Artificial Intelligence Review等多個(gè)期刊審稿人。榮獲2022年度國(guó)家獎(jiǎng)學(xué)金、2023年度ACM Chengdu Chapter 優(yōu)秀博士論文獎(jiǎng)（提名獎(jiǎng)，全省僅1個(gè)）、2023年度西南交通大學(xué)優(yōu)秀博士論文（全校僅10篇）、2024度FLINS-ISKE國(guó)際會(huì)議最佳Poster獎(jiǎng)等榮譽(yù)等。

想要更多了解信息，請(qǐng)點(diǎn)擊我的個(gè)人主頁(yè)https://pengfei-zhang-55.github.io/。歡迎志同道合的同學(xué)報(bào)考我的研究生，同時(shí)歡迎本校想在學(xué)術(shù)上有所突破的本科生聯(lián)系我，聯(lián)系郵箱為zhangpengfei@cdutcm.edu.cn。

二、主持項(xiàng)目情況

國(guó)家自然科學(xué)基金, 青年基金, 62406044, 數(shù)據(jù)與知識(shí)雙驅(qū)動(dòng)的乳腺癌術(shù)后多源復(fù)雜數(shù)據(jù)智能表征與個(gè)性化推薦方法研究, 2025-2027, 30萬(wàn)元，主持

中國(guó)博士后科學(xué)基金會(huì)，國(guó)資計(jì)劃B檔，GZB20230092, 基于多模態(tài)數(shù)據(jù)融合與時(shí)空表征的中醫(yī)診斷模型研究，2024-2025，36萬(wàn)元，主持

中國(guó)博士后科學(xué)基金會(huì), 第74批面上資助, 2023M740383, 面向中醫(yī)四診數(shù)據(jù)的粒度融合方法研究, 2024-2025，8萬(wàn)元，主持

四川省科技廳，面上項(xiàng)目，2024NSFSC0721，中醫(yī)診斷數(shù)據(jù)智能化處理與多粒度融合模型研究，2024-2025，20萬(wàn)元，主持

國(guó)家科學(xué)技術(shù)部，重點(diǎn)研發(fā)計(jì)劃課題，2019YFB2101802，城市知識(shí)庫(kù)構(gòu)建及語(yǔ)義協(xié)同挖掘，2019-2022，322萬(wàn)元，主研

三、部分論文

[1] Pengfei Zhang, Tianrui Li, Guoqiang Wang, Chuan Luo, Hongmei Chen, Junbo Zhang, Dexian Wang, Zeng Yu. Multi-source information fusion based on rough set theory: A review. Information Fusion, 2021, 68: 85-117. (高被引論文,中科院1區(qū)Top, IF=14.7)

[2] Pengfei Zhang, Tianrui Li, Guoqiang Wang, Dexian Wang, Pei Lai, Fan Zhang. A multi-source information fusion model for outlier detection. Information Fusion, 2023, 93: 192-208. (中科院1區(qū)Top, IF=14.7)

[3] Pengfei Zhang, Tianrui Li, Zhong Yuan, Chuan Luo, Guoqiang Wang, Jia Liu, Shengdong Du. A data-level fusion model for unsupervised attribute selection in multi-source homogeneous data. Information Fusion, 2022, 80: 87-103. (中科院1區(qū)Top, IF=14.7)

[4] Pengfei Zhang, Dexian Wang, Zheng Yu, Yujie Zhang, Tao Jiang, Tianrui Li, A multi-scale information fusion-based multiple correlations for unsupervised attribute selection. Information Fusion,106(2024) 102276. (排名第1, 中科 院1 區(qū)Top, IF=14.7)

[5] Pengfei Zhang, Tianrui Li, Zhong Yuan, Zhixuan Deng, Guoqiang Wang, Dexian Wang, Fan Zhang. A possibilistic information fusion-based unsupervised feature selection method using information quality measures. IEEE Transactions on Fuzzy Systems, 2023, 31(9): 2975-2988. (排名第1, 中科院1區(qū)Top, IF=10.7)

[6] Pengfei Zhang, Tianrui Li, Zhong Yuan, Chuan Luo, Keyu Liu, Xiaoling Yang. Heterogeneous Feature Selection Based on Neighborhood Combination Entropy. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(3): 3514-3527. (排名第1, 中科院1 區(qū)Top, IF=10.2)

[7] Qinli Zhang, Pengfei Zhang*, Tianrui Li, Information fusion for large-scale multi-source data based on the Dempster-Shafer evidence theory. Information Fusion, 115(2025) 102754.(通訊作者,中科院1區(qū)Top, IF=14.7)

[8] Jia Liu, Nijing Yang, Yanli Lee, Wei Huang, Yajun Du, Tianrui Li, Pengfei Zhang*, FedDAF: Federated Deep Attention Fusion for Dangerous Driving Behavior Detection. Information Fusion, 2024, 112: 102584.(通訊作者,中科院1區(qū)Top, IF=14.7)

[9] Dexian Wang, Pengfei Zhang*, Ping Deng, Qiaofeng Wu, Wei Chen, Tao Jiang, Wei Huang, Tianrui Li, An autoencoder-like deep NMF representation learning algorithm for clustering. Knowledge-Based Systems, 2024. (通訊作者,中科院1區(qū)Top, IF=7.2)

[10]  Yongming Luo, Jingjing Hu, Gangqiang Zhang, Pengfei Zhang*, Ying Xie, Zhaomin Kuang,Xingji Zeng, Shushi Li, A dissolved oxygen levels prediction method based on single-hidden layer feedforward neural network using neighborhood information metric. Applied Soft Computing, 2024.(通訊作者,中科院1區(qū)Top, IF=7.2)