葡京直营集团

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师资力量

机电工程系

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个人概况

姓名:冯耀泽

硕/博导:硕导

性别:男

办公地点:工程楼B518

职称:副教授

电子邮箱:Yaoze.feng@mail.hzau.edu.cn

冯耀泽,男,1984年生,爱尔兰都柏林大学博士毕业,硕士生导师,机电系副主任。长期致力于农产品和食品的快速无损检测技术研究。主持和参与国家自然科学基金青年基金、湖北省自然科学基金重点项目、国家重点研发计划子课题等多项项目,发表学术论文20余篇,2篇为ESI高被引论文。主编(第二)中文教材1部,参编英文教材/专著两部。
英文概况
Dr.Yaoze Feng joined College of Engineering, HZAU in 2014 as associate professor after obtaining his PhD degree in University College Dublin. He is interested in intelligent detection and control technologies and particularly in applying various rapid and nondestructive sensing technologies (NIR MIR and Raman spectroscopy, hyperspectral imaging, computer vision etc.) in determining the quality and safety of food and agricultural products. He has secured and participated in research projects from National Natural Science Foundation of China, Hubei Natural Science Foundation Key programs. He has published more than 20 research papers where 2 are ESI highly cited. He has also edited one textbook and chaptered another two books.
教育经历
2004年9月-2008年6月 葡京集团 机械设计制造及其自动化 学士/本科
2008年9月-2010年9月 葡京集团 农业电气化与自动化 硕士研究生
2010年9月-2014年9月 University College Dublin,Biosystems Engineering 博士/研究生
工作经历
2014年9月- 葡京集团 葡京直营集团机电工程系 副教授
主讲课程
《Modern Measurement Technology》,《电工技术A》,《模拟电子技术》等
教研教改
研究领域
智能化检测与控制技术;快速无损传感检测方法
主要学术兼职
湖北-武汉无损检测学会理事
中国农业工程学会高级会员
科研成果
[1]Yao-Ze Feng*, Hai-Tao Zhao, Gui-Feng Jia, Chijioke Ojukwu, and He-Qun Tan, 'Establishment of Validated Models for Non-Invasive Prediction of Rectal Temperature of Sows Using Infrared Thermography and Chemometrics', International journal of biometeorology, 63 (2019), 1405-15 (IF=2.377)
[2]Hai-Tao Zhao, Yao-Ze Feng*, Wei Chen, Gui-Feng Jia,Application of invasive weed optimization and least square support vector machine for prediction of beef adulteration with spoiled beef based on visible near-infrared (Vis-NIR) hyperspectral imaging,Meat Science, 151,2019, 75-81, (IF=3.486)
[3]Yao-Ze Feng*, Wei Yu, Wei Chen, Kuan-Kuan Peng, Gui-Feng Jia,Invasive weed optimization for optimizing one-agar-for-all classification of bacterial colonies based on hyperspectral imaging,Sensors and Actuators B: Chemical,269, 2018, 264-270 (IF=6.393)
[4]Ke-Xin Mu, Yao-Ze Feng*, Wei Chen, Wei Yu, Near infrared spectroscopy for classification of bacterial pathogen strains based on spectral transforms and machine learning,Chemometrics and Intelligent Laboratory Systems, 179,2018, 46-53(IF=2.786)
[5]Chen, W., Yao-Ze Feng*, Jia, G. et al. Application of Artificial Fish Swarm Algorithm for Synchronous Selection of Wavelengths and Spectral Pretreatment Methods in Spectrometric Analysis of Beef Adulteration. Food Anal. Methods 11, 2229–2236 (2018) (IF=2.413)
[6]Yao-Ze Feng, Gerard Downey, Da-Wen Sun, Des Walsh and Jun-Li Xu. Towards improvement in classification of Escherichia coli, Listeria innocua and their strains in isolated systems based on chemometric analysis of visible and near-infrared spectroscopic data. Journal of Food Engineering, 2015, 149:87-96 (SCI,IF=3.625)
[7]Yao-Ze Feng, Gamal ElMasry, Da-Wen Sun, Amalia Scannell, Des Walsh and Noha Morcy. Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets. Food Chemistry, 2013, 138(2-3): 1829-1836 (SCI,IF=5.399, ESI高被引文章)
[8]Yao-Ze Feng and Da-Wen Sun. Determination of total viable count (TVC) in chicken breast fillets by near-infrared hyperspectral imaging and spectroscopic transforms, Talanta, 2013, 105: 244-249 (SCI,IF=4.916)
[9]Yao-Ze Feng and Da-Wen Sun. Near-infrared hyperspectral imaging in tandem with partial least squares regression and genetic algorithm for non-destructive determination and visualization of Pseudomonas loads in chicken fillets, Talanta, 2013, 109: 74-83 (SCI,IF=4.916)
[10]Yao-Ze Feng and Da-Wen Sun. Application of hyperspectral imaging in food safety inspection and control: a review. Critical reviews in food science and nutrition, 2012, 52(11): 1039-1058 (SCI,IF=6.704, ESI高被引文章)
科研项目
1.国家自然科学基金,基于水光谱组学的细菌分类检测机理与新方法,2018-2020,25万元 主持
2.湖北省自然科学基金重点项目,多种光学信息融合的牛肉掺假无损检测方法研究,2015-2017,10万元 主持
主要奖励
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