赵鹤飞
博士，高级工程师，本科和硕士毕业于江南大学食品学院，2021年博士毕业于美国内布拉斯加大学林肯分校（University of Nebraska-Lincoln）食品科学系，2023年在美国加州大学戴维斯分校 UC Davis（University of California, Davis）食品科学系完成博士后研究，期间完成美国农业部（USDA）联合加州食品和农业部（CFDA）资助的2020年橄榄油产业废弃物特种作物专项基金项目（20-0001- 033-SF），发表SCI论文共28篇，他引539次，H index 12；发表中文核心或EI文章10篇。
研究方向
1.膜分离纯化数学模型和技术
2.机器学习驱动拉曼光谱原位检测
3.食品生产制造过程中不良风味的抑制和去除
参编专著
1.Zhao, H.; Xu, C. Machine Learning-Driven Raman Spectroscopy Techniques for Rapid Detection of Chemical Compounds and Contaminants in Foods. Raman Spectroscopy in the Food Industry. CRC Press, 2024; pp. 77-106.https://doi.org/10.1201/9781003359975-3?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle
2.Zhao, H.; Xu, C. Natural Phenolic Compounds as Anti-obesity and Anti-cardiovascular Disease Agent. Dietary Phytochemicals; Springer, 2021; pp. 205-221. https://doi.org/10.1007/978-3-030-72999-8_11
3.赵黎明;赵鹤飞.第一章‘膜分离技术基本原理及数学模型分析’:p1-90; 第八章‘膜分离技术在酶制剂生产中的应用’: p269-298.‘膜分离技术在食品发酵工业中的应用’，共423页, ISBN 978-7-5064-7432-0,中国纺织出版社,北京,2011
学术荣誉
参加美国国际食品技术学会IFT年会，美国油脂化学家学会AOCS年会的口头演讲/海报演讲共14次；科研亮点被食品科技、光谱学等英文国际媒体报道9次。机器学习驱动拉曼光谱检测的研究获得2021年美国油脂化学家学会AOCS分析化学奖；2019年江南大学北美校友会博⼠生研究论文竞赛一等奖；2013年上海市科学技术奖三等奖。
学术兼职
美国国际食品技术学会IFT-ΦΤΣ终身会员，美国油脂化学家学会AOCS会员，江南⼤学北美校友会终身会员，并曾经担任校友会北美西部地区副主席；担任Food Chemistry, Journal of Agricultural and Food Chemistry (JAFC), Food Control, Trends in Food Science & Technology,PLOS One, Food Science and Human Wellness, Journal of Functional Foods, Food Science &Nutrition, Foods, Frontiers in Nutrition, Journal of Food Biochemistry, Nutrients, Journal of Food Quality, Journal of the American Oil Chemists' Society (AOCS), Molecules, RSC Advances,International Journal of Biological Macromolecules 等国际知名期刊审稿⼈，并受邀加⼊Royal Society of Chemistry (RSC)英国皇家化学学会期刊审稿专家库。
科研亮点和国际新闻媒体报道
1.北美光谱学会新闻采访报道Research Highlight of “Investigating Food Purity Using Raman Spectroscopy Combined with Machine Learning”, by Cindy Delonas. Spectroscopy Magazine, February 2022. https://www.spectroscopyonline.com/view/investigating-food-purity-using-raman-spectroscopy-combined-with-machine-learning
2.美国油脂化学家学会会刊专题报道文章Zhao, H., et al. Machine learning-driven Raman spectroscopy for rapidly detecting type, adulteration, and oxidation of edible oils. American Oil Chemists’ Society (AOCS) INFORM Magazine (Feature Article), 2020, 31(4), 12–15. Retrieved from https://doi.org/10.21748/inform.04.2020.12.
3.指导美国加州大学戴维斯分校UC Davis本科生实验室科研实习，所指导的学生Yongju Cho (韩国裔)获得IFT北加州分会海报演讲竞赛一等奖，并被UC Davis官方新闻网站报道。https://news.bftv.ucdavis.edu/food-science-and-technology/ncift-1st-place-win-undergrad-yongju-cho
代表性学术成果
1.H. Zhao, Y. Kim, R.J. Avena-Bustillos, N. Nitin, S.C. Wang, Characterization of California olive pomace fractions and their in vitro antioxidant and antimicrobial activities, LWT. 180 (2023) 114677. https://doi.org/https://doi.org/10.1016/j.lwt.2023.114677. (美国农业部联合加州食品和农业部项目20-0001- 033-SF， JCR和中科院1区Top期刊，2024 IF 6.0)
2.H. Zhao, A. Han, J.J. Nduwamungu, N. Nishijima, Y. Oda, A. Handa, Y. Zhang, K. Majumder, C. Xu, Improving textural properties of gluten-free veggie sausage with egg white proteins, Food Bioeng. 1(2022)319-330. https://doi.org/https://doi.org/10.1002/fbe2.12028. (Kewpie Corporation project，日本丘比集团项目)
3.H. Zhao, R.J. Avena-Bustillos, S.C. Wang, Extraction, Purification and In Vitro Antioxidant Activity Evaluation of Phenolic Compounds in California Olive Pomace, Foods. 11 (2022) 174. https://doi.org/10.3390/foods11020174. (美国农业部联合加州食品和农业部项目 20-0001- 033-SF，中科院2区期刊，2024 IF 4.7)
4.H. Zhao, Y. Zhan, Z. Xu, J. John Nduwamungu, Y. Zhou, R. Powers, C. Xu, The application of machine-learning and Raman spectroscopy for the rapid detection of edible oils type and adulteration, Food Chem. 373 (2022) 131471.
https://doi.org/https://doi.org/10.1016/j.foodchem.2021.131471. (美国国家自然科学基金 NSF 资助项目， JCR和中科院1区Top期刊，2024 IF 8.5，Google Scholar 谷歌学术高被引文章、97次引用)
5.H. Zhao, X. Xie, P. Read, B. Loseke, S. Gamet, W. Li, C. Xu, Biofortification with selenium and lithium improves nutraceutical properties of major winery grapes in the Midwestern United States, Int. J. Food Sci. Technol. 56 (2021) 825–837.
https://doi.org/https://doi.org/10.1111/ijfs.14726.
6.H. Zhao, C. Shen, Z. Wu, Z. Zhang, C. Xu, Comparison of wheat, soybean, rice, and pea protein properties for effective applications in food products, J. Food Biochem. 44 (2020) e13157. https://doi.org/10.1111/jfbc.13157. (中科院2区期刊，2024 IF 3.5 ，Google Scholar谷歌学术高被引文章、182次引用)
7.H. Zhao1, X. Hua1, R. Yang, L. Zhao, W. Zhao, Z. Zhang, Diafiltration process on xylo‐oligosaccharides syrup using nanofiltration and its modelling, Int. J. Food Sci. Technol. (2012). https://doi.org/10.1111/j.1365-2621.2011.02803.x. (十二五国家重点研发项目)
8.X. Hua1, H. Zhao1, R. Yang, W. Zhang, W. Zhao, Coupled model of extended Nernst–Planck equation and film theory in nanofiltration for xylo-oligosaccharide syrup, J. Food Eng. (2010). https://doi.org/10.1016/j.jfoodeng.2010.04.013. (十二五国家重点研发项目)