09,2012–06,2016 重庆大学 计算机科学与技术 博士 09,2006–06,2009 西南大学 计算机软件与理论 硕士 09,2002–06,2006 西南大学 计算机科学与技术 本科

[0]2019年度西南大学教育教学改革研究项目（重点）——大数据环境下实验报告质量监测预警机制研究(2019JY046)（2020-2021） [1]Research on Key Technologies of Deep Learning in Spark Cluster——Taking Large-scale 3D Model Retrieval as an Example(2019-2021)097 [2]CY170217重庆市2017年度中小学创新人才工程项目（雏鹰计划项目）——智能协同清扫机器人（2017-2018） [3]XDJK2015C110 3D Retrieval Based on Manifold Ranking(2015-2017) supported by"the Fundamental Research Funds for the Central Universities" XDJK2015C110 [4]Teach Reform of SWU----Computing Essentials Course Lab Teaching With Lego Mindstorms(2016-2017) [5]XDJK2012C066 Research on 3D CAD Retrieval in Agriculture Mechinal Design(2012-2014) supported by"the Fundamental Research Funds for the Central Universities" XDJK2012C066

Main research on:PR,3D retrieval,published 11 papers include(2 indexed by SCI,5 indexed by EI, and one on 3DOR) Publications [1]Qiang Chen, Yinong Chen, et al. Traffic Light and Moving Object Detection for Guide-Dog Robot[C].ACAIT2019,July 5-7,2019,Chongqing,China. [2]Qiang C, CHEN Y, Peng T, et al. Indoor Simultaneous Localization and Mapping for Lego Ev3[C]. 2018 International Conference on Computer, Communication and Network Technology (CCNT2018), June 29-30, 2018 in Wuzhen, China. [3]Qiang C, CHEN Y, Ran C, et al. Autonomous Car Simulating Based on Lego Ev3 and Android App[C]. 2018 International Conference on Computer, Communication and Network Technology (CCNT2018), June 29-30, 2018 in Wuzhen, China. [4]Qiang Chen, Bin Fang, Yinong Chen, Yan Tang. An adaptive feature combination method based on ranking order for 3D model retrieval[J].( International Journal of Computational Science and Engineering,2017,EI JA20200408066503 ) [5]Chen Q, Fang B*, Yu Y M, et al. 3D CAD model retrieval based on the combination of features [J]. Multimedia Tools and Application, 2015, 74(13): 4907-4925.(SCI WOS:000357130400022) [6]Li B, Lu Y, Li C, Godil A, Schreck T, Aono M, Burtscher M, Chen Q, Chowdhury N K, Fang B,et al. A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries[J], Computer Vision and Image Understanding, 2015, 131: 1-27.(ESI WOS:000349588900002) [7]Li B, Lu Y, Li C, Godil A,Schreck T, Aono M, Burtscher M, Chen Q , Chowdhury N K, Fang B,Furuya T,Johan H,Kosaka R,Koyanagi H,Ohbuchi R,Tatsuma A. SHREC14 Track: Large Scale Comprehensive 3D Shape Retrieval[C]. Eurographics Workshop on 3D Object Retrieval, 2014: 131-140.