教育经历
2013-2017，山东师范大学，学士
2017-2022，中国科学院-德国马普学会计算生物学伙伴研究所、中国科学院上海营养与健康研究所，博士         

工作经历

2022-2025，瑞士苏黎世联邦理工学院，博后
2025-至今，新加坡国立大学，助理教授

研究领域

食物信息与人工智能
可持续食物系统中的预测生命周期评价
食品合成生物学

荣誉奖项

2021年，中国科学院院长奖
2024年，国际食品科技联盟（IUFoST）青年科学家奖          
2024年，美国化学学会（ACS）欧文·西格尔全球流动奖

代表性论文

[1] Zhang, D.*; Liu, M.; Yu, Z.; Xu, H.; Pfister, S.; Menichetti, G.; Kou, X.; Zhu, J.; Fan, D.; Rao, P. Domain knowledge, just evaluation, and robust data standards are required to advance AI in food science. Trends in Food Science & Technology 2025. DOI: 10.1016/j.tifs.2025.105272.
[2] Tian, Y. #; Zhang, D.#; Xing, H.; Tang, M.; Zhao, C.; He, W.; Lin, H.; Yan, W.; Hu, Q. N.; Wu, A. Computational glycosyltransferases masked deoxynivalenol toxicity and halted FHB spread in wheat grains. Journal of Advanced Research 2025. DOI: 10.1016/j.jare.2025.08.045  
[3] Qiu, Y. #; Zhang, D. #; Long, M.; Zhou, Z.; Gao, C.; Ma, S.; Qin, J.; Chen, K.; Chen, C.; Zhao, Z.; et al. Coassembly of hybrid microscale biomatter for robust, water-processable, and sustainable bioplastics. Science Advances 2025, 11 (14), eadr1596. DOI: doi:10.1126/sciadv.adr1596.
[4] Jiao, X.; Zhu, J.; Ye, W.; Zou, H.; Yan, B.; Zhang, N.; Qiang, J.; Tao, Y.; Zhang, H.; Zhang, D.*; Fan, D. Artificial intelligence in smart seafood safety across the supply chains: Recent advances and future prospects. Trends in Food Science & Technology 2025, 163. DOI: 10.1016/j.tifs.2025.105161.4. 
[5] Zhang, D.*; Liu, D.; Jing, J.; Jia, B.; Tian, Y.; Le, Y.; Yu, Y.; Hu, Q.-N. Unveiling the chemical complexity of food-risk components: A comprehensive data resource guide in 2024. Trends in Food Science & Technology 2024, 148. DOI: 10.1016/j.tifs.2024.104513.
[6] Zhang, D.; Xing, H.; Liu, D.; Han, M.; Cai, P.; Lin, H.; Tian, Y.; Guo, Y.; Sun, B.; Le, Y.; et al. Discovery of toxin-degrading enzymes with positive unlabeled deep learning. ACS Catalysis 2024, 14, 3336-3348. DOI: 10.1021/acscatal.3c04461.
[7] Zhang, D.*; Wang, Z.; Oberschelp, C.; Bradford, E.; Hellweg, S. Enhanced deep-learning model for carbon footprints of chemicals. ACS Sustainable Chemistry & Engineering 2024, 12 (7), 2700-2708. DOI: 10.1021/acssuschemeng.3c07038.
[8] Xing, H.; Cai, P.; Liu, D.; Han, M.; Liu, J.; Le, Y.; Zhang, D.*; Hu, Q.-N. High-throughput prediction of enzyme promiscuity based on substrate–product pairs. Briefings in Bioinformatics 2024, 25 (2). DOI: 10.1093/bib/bbae089.
[9] Zhang, D.*; Jia, C.; Sun, D.; Gao, C.; Fu, D.; Cai, P.; Hu, Q. N. Data-driven prediction of molecular biotransformations in food fermentation. Journal of Agricultural and Food Chemistry 2023, 71 (22), 8488-8496. DOI: 10.1021/acs.jafc.3c01172 
[10] Kou, X.; Shi, P.; Gao, C.; Ma, P.; Xing, H.; Ke, Q.; Zhang, D.* Data-driven elucidation of flavor chemistry. Journal of Agricultural and Food Chemistry 2023, 71 (18), 6789-6802. DOI: 10.1021/acs.jafc.3c00909.

学术兼职 

兼任新国大人工智能研究所、新加坡毒理学网络委员会、欧洲食品安全局利益相关者小组等机构成员，npj Science of Food副主编，Journal of Food Science、Discovery Food等期刊编委，The Innovation Informatics青年编委，Future Foods客座编辑

NUS网址

https://www.fst.nus.edu.sg/our_people/faculty-members/zhang-dachuan/