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science and technology（中科院一区top）、Ocean Engineering（中科院一区top）、Journal of wind engineering and industrial aerodynamics（中科院一区top）、Applied Ocean Research等行业顶级期刊，其中一篇SCI论文被IAA（国际航空空间论文摘要）收录32行），一篇论文被Wind energy期刊认定为2024年度10篇高被引论文之一。获得授权发明专利8项，相关科研成果先后获得中国电力科学研究院科技进步奖两项。   所从事的民用研究工作已经应用于电网公司的输电线路抗风设计、光伏电池板的抗风设计等。   目前，与国家电网公司中国电力科学研究院、囯网电力工程研究院、中航工业第一飞机设计研究院、中国电建西北院等多家单位保持了良好的项目合作关系，且与西安交通大学、上海交通大学、西北工业大学、天津民航大学、西华大学等所高校的教师保持了良好的科研合作关系。目前，本团队研究方向持续，经费稳定，团队成员精神风貌昂扬向上，积极努力，不仅科研工作进展可控，而且毕业生均获得了良好的就业岗位，在各个领域做出了应有的贡献。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     1.作为培训专家参与了高层建筑风环境与噪声设计培训会。2.作为培训专家参与了河道污染与生态环境保护培训会。3.作为培训专家为中国电建西北院开展了高性能计算培训与软件自动化培训工作。4.作为培训专家为中航工业第一飞机设计研究院和中航工业特种飞机研究所开展了相关培训工作","陕西",false,"http:\u002F\u002Fjs.chd.edu.cn\u002Fjzgcxy\u002Fdhx\u002Flist.htm",true,[],[],{"id":402,"name":403,"orgName":404,"school":389,"gender":390,"title":405,"degree":392,"honor":10,"position":10,"researchDirection":406,"intro":407,"province":395,"completeness":95,"avatarAuthorized":396,"sourceUrl":408,"nameValid":398,"tags":409,"tagNames":410},"7694407a-a422-3ab5-b16b-a0e05863f78a","左琛","长安大学运输工程学院","讲师","1. 基于视觉基础模型的公路交通设施无人机巡检与智能图像识别方法研究伴随着飞控能力和计算平台的发展，无人机已经成为进行公路交通基础设施巡检的新兴工具。然而，无人机图像中扰动因素多、场景变化大，给后继的图像分析与智能识别方法带来巨大挑战。本课题组针对路面病害、标线标识、沿线设施、道路边坡等多种细分养护场景，以海量无人机航拍图像为数据基础，运用视觉基础模型、图像分割大模型、多模态数据处理等人工智能和计算机视觉前沿技术，探索各类异常结构的视觉响应特征，求解行业规范文本和巡检图像之间的相互对应关系，建立兼具计算效率和识别精度的智能图像分析方法，显著提高深度神经网络的训练速度、标注效率和泛化能力，为公路交通基础设施的状态检测和性能评估提供重要依据。1.1 基于基础模型的路面病害识别与搜索方法及时准确地发现裂缝、坑槽、修补等路面病害，是公路预防性养护和智慧化养护的重要内容。近年来，以卷积神经网络为核心的深度学习技术已经成为了分析巡检图像的主流方法。然而，当前技术多基于有监督学习框架，难以有效应对道路病害多样的形态特征，识别方法的泛化能力有限。本课题组基于无人机高分辨率图像，以视觉基础模型为核心技术手段，探索各类路面异常样例的高阶视觉特征，建立高性能路面病害识别方法。具体内容包括：(1)使用DINOv2、Web-SSL等视觉基础模型，充分利用自监督学习、Vision Transformer和海量无标注数据集，提取图像视觉特征；(2)运用距离度量、流形学习和无监督聚类技术，发现道路路面区域，移除不相关图像块；(3)使用XGBoost、TabPFN等有监督分类器，建立主动学习框架，促使计算机理解视觉特征与病害样本之间的对应关系，预测病害的发生位置、损坏类型和损坏程度；(4)基于典型病害样例库，运行近似近邻搜索方法，求解路面病害的类内多样性和场景变化性，实现异常结构的精细搜索与快速排查，探索道路病害的时空变化规律。1.2 图像分割大模型支持的交通标线缺损定位方法保障交通标线的可见性和清晰度，是道路设施养护的重要环节。基于深度神经网络的目标检测和语义分割方法是目前进行破损标线识别的主流技术手段。然而，神经网络的性能高度依赖人工标注的质量和规模，如何有效建立高质量数据集，提高神经网络的训练效率，减少人工标注工作量，成为了重要且紧迫的科研话题。本课题组引入图像分割大模型技术，依据标线颜色等先验信息，引导图像大模型理解交通设施养护场景，建立交通标线缺损快速检测和准确评估的技术方法。具体内容包括：(1)基于图像分割大模型SAM,启动全局分析模式，自动划分无人机巡检图像，依据颜色信息确定道路路面区域，划定研究范围；(2)使用DINOv2基础模型，运用Hausdorff距离和余弦距离，量化无人机图像序列的相似性，获得代表性图像样例；(3)基于代表性图像，训练YOLO和DETR目标检查网络，准确定位减速标线、车道线、导向箭头和导流线破损；(4)启动图像分割大模型SAM，分析交通标线样例，预测标线初始状态。基于阈值分割方法，提取标线的现存可见区域。计算标线的缺失区域比例，定量评估标线健康状态。1.3 多模态学习赋能的交通沿线设施快速识别方法交通标志、交安设施、交通监控等沿线设施是交通系统的基本组成，定位和维护沿线设施是进行基础设施养护的基本要素。基于YOLO等目标检测网络，计算机能够实现无人机航拍图像的高效处理。然而，当前的有监督学习方法高度依赖人工标注数据集，能以有效应对光照条件、巡检场景和飞控参数的显著变化，识别方法的泛化能力有限。本课题组引入多模态分析技术，探索交通标志图像和行业规范文本之间的映射关系，在共享特征空间内实现多模态样例的准确对齐和配准，提高交通沿线设施的快速定位和精细分类。具体内容如下：(1)启动Grounding DINO、YOLO-World、YOLOE等开放词汇目标检测程序，合理设定关键字提示词，建立沿线设施样例数据集；(2)运用知识蒸馏技术，建立教师-学生结构，去除任务无关神经元，获得小尺寸高效率目标检测网络；(3)使用视觉基础模型分析无人机图像，使用文本编码器分析行业规范文本，运用线性映射层实现共享特征空间内的样本对齐，实现交通沿线设施的精细化分类。1.4 光学、红外与三维点云联合驱动的道路边坡隐患识别方法快速发现边坡落石、岩体开裂、植被侵入等异常案例，是维护道路边坡安全的重要因素。在无人机智能巡检框架内，如何有效整合光学图像、红外图像、三维点云等多模态数据采集手段，提高边坡异常结构的识别质量，成为了重要的研究话题。本课题组针对山区公路和沿海公路场景，有机结合设备、数据、技术和交通养护部门需求，以海量无人机图像为数据基础，运用深度神经网络、视觉基础模型、多模态数据处理等手段，建立高性能道路边坡智能巡检方法。具体内容如下：(1)启动EfficientNet、Vision Transformer、ConvNeXt、Mamba等多种前沿深度神经网络，探索各类神经网络的性能边界，实现边坡落石和岩体开裂的快速定位和分类；(2)针对水库边坡场景中的少样本学习难题，使用DINOv2视觉基础模型分析RGB、红外和点云图像，编程实现特征级融合和决策级融合框架，实现边坡落石和植被侵入的快速识别；(3)基于海量无标注图像，使用自监督学习和对比学习技术探索光学-红外-点云图像之间的匹配关系，促使计算机自主发掘边坡结构之间的内在关系和发展趋势，实现多模态数据对齐，获得与巡检场景相匹配的高质量图像编码器。2. 基于开放词汇目标检测和视觉基础模型的危化品车辆识别方法从海量交通监控视频中快速发现危化品车辆，是智慧交通系统的关键环节，是提高通行效率、保障交通安全、促进绿色发展的基本前提。近年来，深度学习和计算机视觉技术成为了实现交通感知的主流方法。然而，多样的视频采集设备、繁杂的交通通行场景和稀缺的危化品车辆样例，给深度神经网络的推广应用带来了巨大挑战。为了提高泛化能力并简化训练流程，本课题组将开放词汇目标检测和视觉基础模型引入到交通视频分析领域，充分利用通用视觉特征，建立高性能危化品车辆识别方法。具体内容包括：(1)启动YOLO-World目标检测程序，合理设置关键字提示词，快速提取交通监控视频中的车辆样例。为了消除冗余信息，使用ByteTrack和SAM2技术，完成车辆的轨迹跟踪；(2)使用DINOv2视觉基础模型，提取车辆样例的视觉特征，使用UMAP和谱聚类技术理解车辆样例之间的相似性关系；(3)使用k近邻搜索去除YOLO-World的噪声样例，使用XGBoost分类器预测车辆类型，有效应对夜间、降雨等复杂场景，建立具有高泛化能力和强鲁棒性的危化品车辆识别方法。3. 孔隙结构与物理属性联合约束的非均质数字岩心建模方法3.1 基于通用图像特征的非均质岩心表征方法3.2 基于机器学习技术的三维数字岩心快速建模方法3.3 贝叶斯证据学习驱动的地质模型空间不确定性量化方法4. 基于视觉基础模型的城市更新区域与建成环境识别方法对于具有复杂建成环境的老城区，采用人工智能技术可以提高更新规划的科学性，然而现有的目标识别方法高度依赖人工标注数据集，面临更新实践不足、分析精度受限和训练成本过高的局限。将视觉基础模型引入城市更新领域，探讨视觉基础模型支持的老城区更新规划方法：(1)通过等间隔采样构建图像块数据集，使用视觉基础模型提取高维视觉特征；(2)启动余弦距离、流形学习、高斯混合模型等机器学习技术，实现图像块数据集的智能分组；(3)对图像块进行空间转译，精准识别重点区域；结合多维要素综合评判，优化智能识别结果，指导后续更新规划实践。以陕西省榆林市清涧县老城区为例，探索该技术方法在城市更新规划实践中的应用，以期为老城区的城市更新提供新的思路","左琛，本科毕业于四川大学电子信息工程专业，博士毕业于西安交通大学信息与通信工程专业，美国斯坦福大学访问学者。现任长安大学运输工程学院讲师，数据与系统工程系副主任，数据与系统工程党支部宣传委员。申请人长期从事机器学习与计算机视觉相关研究工作，目前主持国家自然科学基金青年科学基金项目1项、陕西省自然科学基础研究计划一般项目(青年)1项、陕西省交通运输厅交通运输科研项目1项、山东省交通运输厅先行试验项目1项、中央高校基本科研业务费专项资金资助项目2项。作为技术负责人，参与国家自然科学基金面上项目2项、陕西省科学技术厅重点研发计划项目1项、陕西省交通运输厅重点项目2项、河北省交通厅科技项目1项。以第一作者和通信作者身份，累计发表学术论文10余篇，包括《IEEE Transaction on Geoscience and Remote Sensing》《Water Resources Research》《Remote Sensing》等，参加国内外高水平学术会议并做专题报告6次，已授权发明专利2项。 \n                                \n                                \n                                    \n                                         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液滴微流控 技术，以系统仪器为抓手，生物医学应用为导向，开展了一系列创新性的研究工作，相关工作以第一作者发表在 Nature Biomedical Engineering 、 Science Advances 等国际顶尖期刊上。；什么是液滴微流控？；液滴微流控作为近二十年来飞速发展的一项技术，旨在微尺度流道中将宏观液体分割成尺寸均一的微米级液滴，并在其中进行精细的生化反应及细胞操纵。；液滴微流控的特点是什么？；一方面，每个液滴都可以作为独立的反应单元，实现单细胞级别的精准操控与分析；另一方面，液滴的数量通常在数十万到数百万之间，可以支撑高通量的生物检测分析。；液滴微流控有什么用？；液滴微流控可以显著提升检测灵敏度和分析效率，不仅有力支撑了先进前沿的生命科学研究，也是开发新一代高端生物检测分析仪器的重要技术基础，在疾病诊断、药物研发等领域都有着广泛的应用。","【产业方向】高端装备","https:\u002F\u002Fgr.xjtu.edu.cn\u002Fnanlang\u002Fzh_CN\u002Findex.htm",[445,446,449,452,455],{"code":426,"name":427},{"code":447,"name":448},"GB-74","专业技术服务业",{"code":450,"name":451},"SEI-02","高端装备制造产业",{"code":453,"name":454},"CH-20","高端装备",{"code":456,"name":457},"CH-28","交通",[427,448,451,454,457],{"id":460,"name":461,"orgName":462,"school":439,"gender":10,"title":391,"degree":10,"honor":10,"position":10,"researchDirection":463,"intro":442,"province":395,"completeness":288,"avatarAuthorized":396,"sourceUrl":464,"nameValid":398,"tags":465,"tagNames":509},"bcdc275e-d27a-4991-8a5c-05c0f3e7a0ee","罗钰","西安交通大学机械工程学院","1.微纳制造 \u002F增材制造（3D打印技术）及其高端装备开发；；2.光电子器件与柔性电子传感系统设计（软、硬件结合）及制造 ；；3.基于新型光电、生物传感器的智能算法及人机交互系统开发。；传统 传统喷墨打印或挤出式打印采用外驱动力“推”动挤压墨液，难以满足粘度高于50cps或特征尺寸小于10μm的高精度打印需求。电流体3D打印技术通过电场力“拉”动和控制液滴成型，产生的墨滴尺寸远小于喷嘴内径，打印精度可达亚微米级别,具备按需点喷、近场直写、静电纺丝、静电雾化四种工作模式，可在各类型平面或曲面基材（如金属基材、玻璃、硅片、聚合物膜、陶瓷、纸基等）上实现高分辨率点阵、二维图案、薄膜和任意三维结构的低成本、大面积制造，可打印材料兼容导电墨水、高分子材料、UV固化材料等（1cp-50000cps）。在微电子、锂电池、生物医疗、微纳传感领域有较好应用前景。 团队自主开发的电流体3D打印设备及配套控制软件（包含运动控制、视觉定位、矢量图打印、机器视觉-打印参数闭环控制等功能） 已在传感器制造、芯片封装等领域实现产业化应用。；云端鼻息-可穿戴呼吸监测仪；柔性电路的3D打印；已取得成果： 与宁德时代、深圳海目星、上海金力泰等上市公司开展技术对接 。；已取得成果： 采用激光诱导石墨烯技术制备的可穿戴柔性葡萄糖传感器工作发表在 Advanced Materials Technologies(影响因子 7.8)Electrochimica Acta（影响因子6.9）等期刊。2023年，该方向获批国家自然科学基金面上项目。；F、少层\u002F多层石墨烯薄膜大面积喷印制备 （可应用于场效应晶体管、电磁屏蔽、金属工件或薄膜的防潮防腐等领域。）；已取得成果： 正在承担国家自然科学基金项目全喷墨打印的高灵敏度COVID-19双检测FET传感器，150万元。自主开发了FET便携式测试系统、检测试剂盒及对应的APP程序，目前正在做产业化开发。实现了晶圆级少层石墨烯薄膜的低成本、大规模制备，将具备良好半导体性能石墨烯薄膜的成本降低至现有技术的1\u002F20.","https:\u002F\u002Fgr.xjtu.edu.cn\u002Fyuluo825\u002Fzh_CN\u002Findex.htm",[466,469,472,475,478,481,484,485,488,491,492,495,496,497,500,503,506],{"code":467,"name":468},"GB-28","化学纤维制造业",{"code":470,"name":471},"GB-30","非金属矿物制品业",{"code":473,"name":474},"GB-38","电气机械和器材制造业",{"code":476,"name":477},"GB-40","仪器仪表制造业",{"code":479,"name":480},"GB-65","软件和信息技术服务业",{"code":482,"name":483},"GB-67","资本市场服务",{"code":447,"name":448},{"code":486,"name":487},"GB-84","卫生",{"code":489,"name":490},"SEI-01","新一代信息技术产业",{"code":450,"name":451},{"code":493,"name":494},"CH-08","集成电路",{"code":453,"name":454},{"code":456,"name":457},{"code":498,"name":499},"CH-30","制造",{"code":501,"name":502},"CH-32","消费电子",{"code":504,"name":505},"CH-33","人工智能",{"code":507,"name":508},"FU-01","未来制造",[468,471,474,477,480,483,448,487,490,451,494,454,457,499,502,505,508],{"id":511,"name":512,"orgName":462,"school":439,"gender":10,"title":513,"degree":10,"honor":10,"position":10,"researchDirection":514,"intro":442,"province":395,"completeness":288,"avatarAuthorized":396,"sourceUrl":515,"nameValid":398,"tags":516,"tagNames":538},"6699d356-6a50-4e41-bf0e-7016136ba495","刘阳鹏","副研究员","超精密加工技术与装备、精密测量技术与仪器、生物制造与仪器、微纳机械电子系统与微纳米测试技术、微纳制造与先进传感技术等，在复杂零件精密测量与分析领域有扎实的研究基础与技术积累。本人先后参与了 973子课题“复杂曲面加工及装配精度的检测原理”、863重点课题“复杂与大型齿轮测量系统”、国家科技重大专项“工业机器人关节减速器生产线”、“高档数控机床与基础制造装备”科技重大专项项目“1500大尺寸超精密非球面车磨复合加工机床及应用工艺”等项目的研究工作,参与建设国内机床龙头企业陕西秦川机床股份公司智能产线建设，参与陕西法士特齿轮股份公司黑灯工厂建设，且参与的项目“复杂零件高端测量装备自适应精密检测技术及系列产品开发”获得2018高等学校科学研究优秀成果奖科学技术进步二等奖。近年来在中外期刊发表科技论文十余篇，其中6篇SCI收录、8篇EI收录，获得授权发明专利16项，申请软件著作权16项，出版专著一部。","https:\u002F\u002Fgr.xjtu.edu.cn\u002Fyangpeng.liu\u002Fzh_CN\u002Findex.htm",[517,520,521,522,523,526,527,528,531,534,535,536,537],{"code":518,"name":519},"GB-34","通用设备制造业",{"code":479,"name":480},{"code":426,"name":427},{"code":447,"name":448},{"code":524,"name":525},"GB-86","新闻和出版业",{"code":489,"name":490},{"code":450,"name":451},{"code":529,"name":530},"SEI-04","生物产业",{"code":532,"name":533},"CH-02","生物制造",{"code":453,"name":454},{"code":456,"name":457},{"code":498,"name":499},{"code":507,"name":508},[519,480,427,448,525,490,451,530,533,454,457,499,508],{"id":540,"name":541,"orgName":462,"school":439,"gender":10,"title":513,"degree":10,"honor":10,"position":10,"researchDirection":542,"intro":442,"province":395,"completeness":543,"avatarAuthorized":396,"sourceUrl":544,"nameValid":398,"tags":545,"tagNames":566},"2c3399da-a0e6-4b42-9eb0-d83e07492e01","张迪","科研项目： 连 ********** 究， JKW 重点项目子课题， 200 万， 2023\u002F01-2025\u002F03 ( 主持 ) ； 预应力下三维编织复合材料低速冲击力学行为及构效关系研究，国家自然科学基金（青年科学基金项目）， 30 万， 2025-01-01 至 2027-12-31 ( 主持 ) ; 离散冲击载荷下复合材料结构损伤及剩余强度评估技术 ( 主持 ) ，航空科学基金， 17 万， 2022\u002F03-2025\u002F02 ； 三维编织陶瓷基复合材料热力耦合损伤机理及结构强度多尺度仿真技术研究 ( 主持 ) ，航天液体动力全国重点实验室基金， 40 万， 2023\u002F06-2025\u002F06 ； 三维编织复合材料多点 \u002F 多次低速冲击损伤机理研究 ( 主持 ) ，博士后科学基金， 8 万， 2021\u002F09-2023\u002F09 ； 中低应变率下三维编织复合材料力学性能表征及多尺度分析 ( 主持 ) ，陕西省自然科学基金， 5 万 2023\u002F03- 2025\u002F03 ； 三 ********** 究 ( 主持 ) ，西安航天动力研究所， 32 万， 2022\u002F04-2023\u002F03 ； 超大尺寸复材机翼整体壁板高性能精确成型方法研究 ( 主研 ) ，科技部重点研发计划， 400 万， 2021\u002F12-2026\u002F11 ； 三维编织陶瓷复合材料喷管制造工艺及其性能与寿命预测仿真技术研究 ( 主研 ) ，装发基础研究项目， 138 万， 2021\u002F01-2022\u002F12 ； 航空航天先进复合材料构件成型关键技术 ( 主研 ) ，陕西省科学技术厅， 200 万， 2022\u002F07-2023\u002F12 ； 复合材料机身机构高能大面积冲击材料试验与分析技术 ( 主研 ) ，中国飞机强度研究所， 80 万， 2021\u002F01-2022\u002F12 。 学术成果： Zhang Di , Zhou Jin, Wang Jizhen, Zhang Wenxin, Guan Zhongwei. A comparative study on failure mechanisms of open-hole and filled-hole composite laminates: Experiment and numerical simulation. Thin-walled structures. 2024;198: 111730. ( SCI 1 区， Top ) Zhang Di , Zhang Chun, Qi Jiangwei, Zhou Jin, Zheng Xitao, Liu Haibao. Experimental and numerical studies on filled-hole compression of FRP laminates considering different countersunk hole configurations. Construction and Building Materials. 2024; 417: 135305. ( SCI 1 区， Top ) Zhang Di , Zhang Wenxin, Zhou Jin, Zheng Xitao, Wang Jizhen, Liu Haibao. Numerical investigation of the low-velocity impact damage resistance and tolerance of composite laminates with preloads. Aerospace Science and Technology. 2023;142: 108650. ( SCI 1 区， Top ) Zhang Di , Zheng Xitao, Wang Zhibang, Wu Tianchi, Sohail Ahmed. Effects of braiding architectures on damage resistance and damage tolerance behaviors of 3D braided composites. Composite Structures. 2020; 232: 111565. ( SCI 1 区， Top ) Zhang Di , Zheng Xitao, Wu Tianchi. Damage characteristics of open-hole laminated composites subjected to longitudinal loads. Composite Structures. 2019; 230: 111474. ( SCI 1 区， Top ) Zhang Di , Zheng Xitao, Zhou Jin, Zhang Wenxuan. Bridging the low-velocity impact energy versus impact damage and residual compression strength for composite laminates. Journal of Reinforced Plastics and Composites. 2021;40(9-10):378-390. ( SCI ) Zhang Di , Zheng Xitao, Zhou Jin, Song Xinyi, Jia Pu, Liu Haibao, Liu Xiaochuan. Effect of Braiding Architectures on the Mechanical and Failure Behavior of 3D Braided Composites: Experimental Investigation. Polymers. 2022;14(9): 1916. ( SCI ) Song Xinyi, Zhang Di , Zhou Jin, Chen Xuefeng, Zhang Shenghao, Bai Longteng, Yang Xiaohui, Du Feiping, Guan Zhongwei, Zheng Xitao, Wesley J. Cantwell. Hierarchical multi-scale analysis of the effect of varying fiber bundle geometric properties on the mechanical properties of 3D braided composites. Composite Structures. 2023;322: 117375. ( SCI 1 区， Top ) Zhang Wenxin, Zhang Di , Zhou Jin, Qi Jiangwei, Zhao Wen, Yang Shuming, John P. Dear, Liu Haibao. Damage mechanisms of composite laminates under impact loading including the effect of pre-load. Thin-walled structures. 2023;191: 111068. ( SCI 1 区， Top ) Song Xinyi, Zhou Jin, Zhang Di , Zhang Shenghao, Li Pei, Bai Longteng, Yang Xiaohui, Du Feiping, Chen Xuefeng, Guan Zhongwei, Cantwell Wesley J. Trans-scale analysis of 3D braided composites with voids based on micro-CT imaging and unsupervised machine learning. Composites Science and Technology. 2024; 249: 110494. ( SCI 1 区， Top ) Liu Haibao, Zhou Jin, Zhang Di , Li Shipeng, Giannopoulos Ioannis. Effects of contact friction and ply blocking on the crush behaviour of thin-walled composite structures: a numerical study. Thin-Walled Structures, 2023; 182: 110214. ( SCI 1 区， Top ) 《先进复合材料飞机结构设计与应用》第四章：强度设计，航空工业出版社， 2019. ( 专著 ) 《航空航天复合材料》第十五章：含冲击损伤复合材料的静强度及疲劳性能，科学出版社， 2024. ( 专著 )",67,"https:\u002F\u002Fgr.xjtu.edu.cn\u002F0020200422\u002Fzh_CN\u002Findex.htm",[546,547,550,553,556,557,558,559,560,563,564,565],{"code":470,"name":471},{"code":548,"name":549},"GB-37","铁路、船舶、航空航天和其他运输设备制造业",{"code":551,"name":552},"GB-44","电力、热力生产和供应业",{"code":554,"name":555},"GB-56","航空运输业",{"code":482,"name":483},{"code":426,"name":427},{"code":524,"name":525},{"code":450,"name":451},{"code":561,"name":562},"CH-09","航空航天",{"code":453,"name":454},{"code":456,"name":457},{"code":498,"name":499},[471,549,552,555,483,427,525,451,562,454,457,499],{"id":568,"name":569,"orgName":570,"school":571,"gender":10,"title":440,"degree":10,"honor":10,"position":10,"researchDirection":572,"intro":417,"province":573,"completeness":543,"avatarAuthorized":396,"sourceUrl":574,"nameValid":398,"tags":575,"tagNames":581},"d7862fa7-d2f2-403f-a771-baede5ec0218","王雅雷","粉末冶金研究院","中南大学","高性能碳 \u002F碳 复合材料及大尺寸异形构件研制；高性能碳 \u002F 陶复合材料；超高温耐烧蚀陶瓷涂层；特种高纯陶瓷粉体等，主持和承担国家自然科学基金项目等各类横向项目 30 多项","湖南","http:\u002F\u002Ffaculty.csu.edu.cn\u002Fwangyalei\u002Fzh_CN\u002Findex.htm",[576,577,578,579,580],{"code":470,"name":471},{"code":482,"name":483},{"code":426,"name":427},{"code":429,"name":430},{"code":432,"name":433},[471,483,427,430,433],{"id":583,"name":584,"orgName":585,"school":439,"gender":10,"title":415,"degree":10,"honor":10,"position":10,"researchDirection":586,"intro":587,"province":395,"completeness":543,"avatarAuthorized":396,"sourceUrl":588,"nameValid":398,"tags":589,"tagNames":601},"69d16215-dff8-4ac1-b1ee-13a10059e770","王鹤峰","西安交通大学物理学院","量子算法，量子计算与量子信息理论 。 随着电子线路的尺寸越来越小，量子效应开始显现，如何在这种情况下进行计算？ 在经典计算机上模拟量子体系的复杂度随体系的大小呈指数增长，如何高效的模拟量子体系？量子计算机是由量子体系构建而成，量子信息的存储，传输，处理和读出都必须服从量子力学原理。量子计算把待求解问题映射到量子体系中，利用量子力学原理求解这些问题。我们研究的核心问题是：哪些问题在经典计算机上难以求解，而在量子计算机上可以高效解决？设计高效的量子算法解决这些问题。 我们已经发展了一些量子算法：量子态的 制备 ；量子开放体系动力学的量子模拟； 求解薛定谔方程、 本征值问题、离散数学问题、数据拟合问题、优化问题 等。 近期发表的部分文章： 1. Quantum algorithm for PageRank computation through multistep quantum resonant transitions, Chuqing Wang, Hefeng Wang and Hua Xiang, Journal of Computational and Applied Mathematics , 491 , 118059 (2027). 2. Saving resources through repeat-until-success positive-operator-valued-measure measurements in quantum computation, Hefeng Wang, Sixia Yu and Hua Xiang, Physical Review A , 114 , 032408 (2026). 3. Quantum optimization algorithm based on multistep quantum computation, Hefeng Wang and Hua Xiang, New J. Phys ., 26 , 073031 (2024). 4. Efficient quantum algorithm for solving structured problems via multistep quantum computation, Hefeng Wang, Sixia Yu and Hua Xiang, Physical Review Research , 5, L012004 (2023). 5. Quantum Multi-Round Resonant Transition Algorithm, Fan Yang, Xinyu Chen, Dafa Zhao, Shijie Wei, Jingwei Wen, Hefeng Wang, Tao Xin and Guilu Long, Entropy , 25 , 61 (2023). 6. Quantum algorithm for preparing the ground state of a physical system through multi-step quantum resonant transitions， Hefeng Wang and Sixia Yu, Quantum Information Processing ， 20 ，40 (2021) 7. Quantum algorithm for total least squares data fitting, Hefeng Wang and Hua Xiang, Physics Letters A , 383 ，2235-2240 （2019）. 8. Quantum Simulation of Resonant Transitions for Solving the Eigenproblem of an Effective Water Hamiltonian, Zhaokai Li, Xiaomei Liu, Hefeng Wang†, Sahel Ashhab, Jiangyu Cui, Hongwei Chen, Xinhua Peng‡, and Jiangfeng Du, Physical Review Letters , 122 , 090504 (2019). 9. A quantum eigensolver for symmetric tridiagonalmatrices，Hefeng Wang and Hua Xiang, Quantum Information Processing ， 18 ，93 (2019) 10. Quantum algorithm for preparing the ground state of a system via resonance transition, Hefeng Wang, Scientific Reports ， 7 ，16342 (2017) 11. Quantum algorithm for obtaining the eigenstates of a physical system, Hefeng Wang, Phys. Rev. A 93 , 052334 (2016) 12. Determining Ramsey numbers on a quantum computer, Hefeng Wang, Phys. Rev. A 93 , 032301 (2016) 13. Ultrafast adiabatic quantum algorithm for the NP-complete exact cover problem, Hefeng Wang & Lian-Ao Wu, Scientific Reports ， 6 ，22307 (2016) 14. A quantum algorithm for obtaining the energy spectrum of a physical system without guessing its eigenstates, Hefeng Wang, Phys. Chem. Chem. Phys ., 2014, 16 (30), 16241-16245 15. A quantum algorithm for solving some discrete mathematical problems by probing their energy spectra, Hefeng Wang, Heng Fan, Fuli Li, Physical Review A 89 , 012306 (2014) 16. Quantum algorithm for obtaining the energy spectrum of a physical system, Hefeng Wang, S. Ashhab, Franco Nori, Phys. Rev. A 85, 062304 (2012) 17. Quantum algorithm for simulating the dynamics of an open quantum system, Hefeng Wang, S. Ashhab, Franco Nori, Phys. Rev. A , 83 , 062317 (2011) 18. Robust and scalable optical one-way quantum computation, Hefeng Wang, Chui-Ping Yang, Franco Nori, Phys. Rev. A 81 , 052332 (2010) 19. Measurement-based quantum phase estimation algorithm for finding eigenvalues of non-unitary matrices, Hefeng Wang, Lian-Ao Wu, Yu-xi Liu, Franco Nori, Phys. Rev. A , 82 , 062303 (2010) 20. Efficient quantum algorithm for preparing molecular-system-like states on a quantum computer, Hefeng Wang, S. Ashhab, Franco Nori, Phys. Rev. A 79 , 042335 (2009) 21. Quantum Algorithm for Obtaining the Energy Spectrum of Molecular Systems, Hefeng Wang, Sabre Kais, Alán Aspuru-Guzik, Mark R. Hoffmann, Phys. Chem. Chem. 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