个人简介
中国农业大学副教授、博士生导师，中国农业大学高层次人才，工学院产业创新研究中心副主任，北京市平谷区科学技术和工业信息化局总工程师，科技部驻外后备干部；北京市科技特派员，北京市平谷区柔性引进人才，中国农业机械学会终身会员、农副产品加工机械分会委员；毕业于爱尔兰国立都柏林大学，获博士学位；入选美国农业与生物工程师学会年度新人物 (New Faces of ASABE - Professionals)；中国农业大学高水平创新团队、现代农业产业技术体系北京市创新团队、农业农村部优秀创新团队、农业农村部国家农产品加工技术装备研发分中心、农业农村部全国名特优新农产品无损评价鉴定识别仪器设备技术北京中心主要成员，首批中国农业大学乡村产业振兴带头人培育“头雁”项目导师；长期从事农产品智能感知控制装备与机器人研究，以满足地球对丰富、营养和美味食物供应的需求；新加坡国家研究基金会(NRF)项目评审专家、山东省重点研发计划项目评审专家；国际期刊 Smart Cities 主编、Frontiers in Plant Science 副主编、Remote Sensing 顾问、Agriculture 编委、Bioseonsrs 首席客座编辑。
2023年，中国农业大学博士生导师、北京市平谷区科学技术和工业信息化局总工程师、科技部驻外后备干部；2022年，北京市中关村平谷园管委会总工程师、中国农业大学工学院产业创新研究中心副主任；2020年，中国农业大学高层次人才、一级副教授 (专业技术五级)、硕士生导师；2016至2020年，英国伯明翰大学、加州大学戴维斯分校、美国农业部农业研究局、美国明尼苏达大学工作；2016年，受邀参加欧美同学会组织的“百名海外名校博士创业中国行”活动；2015至2016年，丹麦哥本哈根大学、西班牙国立圣地亚哥大学访问学者。
荣誉及奖励
2023, 中国农业大学研究生自主创新研究基金重点项目指导老师
2022, 现代农业产业技术体系北京市创新团队奖
2021, 神农中华农业科技奖优秀创新团队奖
2021, 中国农业大学研究生自主创新研究基金项目指导教师
2020, 中国农业大学优秀人才
2020, 美国农业与生物工程师学会 (ASABE) 年度新人物奖
2018, 国际会议最佳论文奖
社会职务
2023，北京市科技特派员
2023，中国农业机械学会终身会员
2023，山东省重点研发计划（重大科技创新工程）项目评审专家
2023，教育部全国研究生教育评估监测专家库专家
2022，中国农业机械学会农副产品加工机械分会委员
2022，新加坡国家研究基金会(NRF) 卓越研究与科技企业园区(CREATE) 评审专家
2022，北京市平谷区科技特派员
2022，国际期刊 Smart Cities (ISSN 2624-6511) Section 主编
2022，国际期刊 Frontiers in Plant Science (ISSN 1664-462X) 副主编
2022，国际期刊 Frontiers in Food Science and Technology (ISSN 2674-1121) 副主编
2022，国际期刊 Frontiers in Nutrition (ISSN 2296-861X) 首席客座编辑
2022，国际期刊 Remote Sensing (ISSN 2072-4292) 首席客座编辑、顾问委员会委员
2022，国际期刊 Sensors (ISSN 1424-8220) 首席客座编辑、顾问委员会委员
2022，国际期刊 Biosensors (ISSN 2079-6374) 首席客座编辑
2021，国际期刊 Agriculture(ISSN 2077-0472) 首席客座编辑、编委会委员
2021，国际期刊 Agronomy (ISSN 2073-4395) 首席客座编辑、编委会委员
2021，国际期刊 Foods (ISSN 2304-8158) 客座编辑、顾问委员会委员
2021，国际期刊 Smart Cities (ISSN 2624-6511) 首席客座编辑、编委会委员
2018，国际期刊 Artificial Intelligence in Agriculture (ISSN 2589-7217) 编委会委员
2018，美国农业与生物工程师学会 (ASABE) 会员
2018，美国园艺科学学会 (ASHS) 会员
国际学术期刊同行通讯评审专家（包括 Nature Communications, Trends in Food Science and Technology, Critical Reviews in Food Science and Nutrition, Food Chemistry, Computers and Electronics in Agriculture, Remote Sensing, Sensors, Biosensors, Infrared Physics and Technology, IEEE Access, Foods, Food Additives and Contaminants, Innovative Food Science and Emerging Technologies, Postharvest Biology and Technology, Drying Technology 等）
研究领域
智慧农业与智能装备
技术方向：农产品智能感知控制机器人
田间作物智能识别看护
大田作物影像精准识别技术装备
作物信号传导及株间除草机器人
农产品品质智能检测控制
农产品智能识别定位分级机器人
新兴替代蛋白农品智能测控装置
近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
Quantitative Evaluation of Maize Emergence Using UAV Imagery and Deep Learning Remote Sensing 2023.04 China Agricultural University 第一
An Integrated Multi-Model Fusion System for Automatically Diagnosing the Severity of Wheat Fusarium Head Blight Agriculture 2023.07 China Agricultural University 通讯
A real-time smart sensing system for automatic localization and recognition of vegetable plants for weed control Frontiers in Plant Science 2023.03 China Agricultural University 通讯
Discrimination of Deoxynivalenol Levels of Barley Kernels Using Hyperspectral Imaging in Tandem with Optimized Convolutional Neural Network Sensors 2023.02 China Agricultural University 通讯
Convolutional Neural Networks in Computer Vision for Grain Crop Phenotyping: A Review Agronomy 2022.10 China Agricultural University 通讯
Automatic Tandem Dual BlendMask Networks for Severity Assessment of Wheat Fusarium Head Blight Agriculture 2022.09 China Agricultural University 通讯
SE‐YOLOv5x: An Optimized Model Based on Transfer Learning and Visual Attention Mechanism for Identifying and Localizing Weeds and Vegetables Agronomy 2022.08 China Agricultural University 通讯
Two-Stage Convolutional Neural Networks for Diagnosing the Severity of Alternaria Leaf Blotch Disease of the Apple Tree Remote Sensing 2022.05 China Agricultural University 通讯
Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review Biosensors 2022.01 China Agricultural University 通讯
Development of a Three-Dimensional Plant Localization Technique for Automatic Differentiation of Soybean from Intra-Row Weeds Agriculture 2022.01 China Agricultural University 第一/通讯
Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality Foods 2021.09 China Agricultural University 第一
Rapid Softness Prediction and Microbial Spoilage Visualization of Whole Tomatoes by Using Hyper/Multispectral Imaging Challenges 2021.08 China Agricultural University 第一/通讯
Hyperspectral imaging and improved feature variable selection for automated determination of deoxynivalenol in various genetic lines of barley kernels for resistance screening Food Chemistry 2021.05 China Agricultural University 第一
Automatic Evaluation of Wheat Resistance to Fusarium Head Blight Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision Remote Sensing 2021.02 China Agricultural University 第一
Systemic Crop Signaling for Automatic Recognition of Transplanted Lettuce and Tomato under Different Levels of Sunlight for Early Season Weed Control Challenges 2020.12 China Agricultural University 第一/通讯
Crop plant signaling for real-time plant identification in smart farm: A systematic review and new concept in artificial intelligence for automated weed control Artificial Intelligence in Agriculture 2020.12 China Agricultural University 第一/通讯
Advanced Machine Learning in Point Spectroscopy, RGB- and Hyperspectral-Imaging for Automatic Discriminations of Crops and Weeds: A Review Smart Cities 2020.09 China Agricultural University 第一/通讯
Fluorescent compound helps intelligent weeders in celery fields California Agriculture 2020.06 University of California, Davis 第一/通讯
Development of a systemic crop signalling system for automated real-time plant care in vegetable crops Biosystems Engineering 2020.05 University of California, Davis 第一/通讯
Non-destructive evaluation of photostability of crop signaling compounds and dose effects on celery vigor for precision plant identification using computer vision Computers and Electronics in Agriculture 2020.01 University of California, Davis 第一/通讯
Chemometric determination of time series moisture in both potato and sweet potato tubers during hot air and microwave drying using near/mid-infrared (NIR/MIR) hyperspectral techniques Drying Technology 2020.01 University College Dublin, National University of Ireland 第一
Fluorescence imaging for rapid monitoring of translocation behaviour of systemic markers in snap beans for automated crop/weed discrimination Biosystems Engineering 2019.10 University of California, Davis 第一/通讯
Automated Identification of Systemic Fluorescent Markers in Vegetable Seedling Leaves for Weed and Crop Differentiation HortScience 2019.07 University of California, Davis 第一/通讯
Rapid Determination of Starch Content of Potato and Sweet Potato by Using NIR Hyperspectral Imaging HortScience 2019.07 University of California, Davis 第一/通讯
Mid-infrared (MIR) Spectroscopy for Quality Analysis of Liquid Foods Food Engineering Reviews 2019.05 University College Dublin, National University of Ireland 第一
Potato hierarchical clustering and doneness degree determination by near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy Journal of Food Measurement and Characterization 2019.04 University College Dublin, National University of Ireland 第一
Chemometrics in tandem with near infrared (NIR) hyperspectral imaging and Fourier transform mid infrared (FT-MIR) microspectroscopy for variety identification and cooking loss determination of sweet potato Biosystems Engineering 2019.04 University College Dublin, National University of Ireland 第一/通讯
Fingerprinting study of tuber ultimate compressive strength at different microwave drying times using mid-infrared imaging spectroscopy Drying Technology 2019.01 University College Dublin, National University of Ireland 第一
Evaluation of spectral imaging for inspection of adulterants in terms of common wheat flour, cassava flour and corn flour in organic Avatar wheat (Triticum spp.) flour Food Engineering 2018.05 University College Dublin, National University of Ireland 第一
Fourier transform mid-infrared-attenuated total reflectance (FTMIR-ATR) microspectroscopy for determining textural property of microwave baked tuber Food Engineering 2018.02 University College Dublin, National University of Ireland 第一
Multispectral Imaging for Plant Food Quality Analysis and Visualization Comprehensive Reviews in Food Science and Food Safety 2018.01 University College Dublin, National University of Ireland 第一
Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review Comprehensive Reviews in Food Science and Food Safety 2018.01 University College Dublin, National University of Ireland 第一
Non-destructive and rapid evaluation of staple foods quality by using spectroscopic techniques: a review Critical Reviews in Food Science and Nutrition 2017.10 University College Dublin, National University of Ireland 第一
Chemical imaging for measuring the time series variations of tuber dry matter and starch concentration Computers and Electronics in Agriculture 2017.08 University College Dublin, National University of Ireland 第一
Variation analysis in spectral indices of volatile chlorpyrifos and non-volatile imidacloprid in jujube (Ziziphus jujuba Mill.) using near-infrared hyperspectral imaging (NIR-HSI) and gas chromatograph-mass spectrometry (GC–MS) Computers and Electronics in Agriculture 2017.06 University College Dublin, National University of Ireland 第一
Comparative assessment of feature-wavelength eligibility for measurement of water binding capacity and specific gravity of tuber using diverse spectral indices stemmed from hyperspectral images Computers and Electronics in Agriculture 2016.11 University College Dublin, National University of Ireland 第一
Multivariate analysis of hyper/multi-spectra for determining volatile compounds and visualizing cooking degree during low-temperature baking of tubers Computers and Electronics in Agriculture 2016.09 University College Dublin, National University of Ireland 第一
Facilitated wavelength selection and model development for rapid determination of the purity of organic spelt (Triticum spelta L.) flour using spectral imaging Talanta 2016.08 University College Dublin, National University of Ireland 第一
Potential of hyperspectral imaging for visual authentication of sliced organic potatoes from potato and sweet potato tubers and rapid grading of the tubers according to moisture proportion Computers and Electronics in Agriculture 2016.07 University College Dublin, National University of Ireland 第一
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