获奖情况:
(1)2025年度国家级青年人才
(2)2023年北京航空航天大学教学成果一等奖(排名第一)
(3)2025 年北京市科学技术协会首都前沿学术成果奖
(4)2025年中国环境科学学会新污染物治理青年创新奖
(5)2025年中国生态学学会环境污染与生态保护优秀青年学者
发明专利:
(1)王颖,吴丰昌,穆云松,冯承莲,刘跃丹,过渡金属保护人体健康水质基准的非致癌EDs预测方法,ZL201710617090.2
(2)王颖,郭飞,武暕,张琛,白英臣,王国静,吴丰昌,突发环境事件应急处置限值的非参数核密度确定方法,ZL201710083062.7
(3)王颖,徐秋童,范文宏,李晓敏,有机污染物影响下的水生生态系统种群数量的预测方法,ZL202011125825.8
(4)王颖,周运驰,张浩文,范文宏,纳米材料生物毒性数据库及分析预测软件,软件著作权,2025SR0549156
(5)王颖,董瑾初,周运驰,范文宏,小数据机器学习毒性预测与分析平台(SDML Tox),软件著作权,2026SR0628562
代表性论文:
[1] Yunchi Zhou, Ying Wang*, et al. Integrating Functional Genomic Descriptors into Explainable Machine-Learning Models for Cross-Aquatic Species Prediction of Metal-Containing Nanomaterials Ecotoxicity. Environ. Sci. Technol. Lett., 2026, 13, 1114−1121(内封面论文).
[2] Yinghao Cheng, Ying Wang*, et al. Predicting the site-specific toxicity of metals to fishes using a new machine learning-based approach. Environ. Sci. Technol., 2025, 59(29), 1488-14891.
[3] Ying Wang, Jinchu Dong, et al. Addressing the Data Scarcity Problem in Ecotoxicology via Small Data Machine Learning Methods. Environ. Sci. Technol., 2025, 59(12), 5867–5871.
[4] Yunchi Zhou, Ying Wang*, et al. Application of Machine Learning in Nanotoxicology: A Critical Review and Perspective, Environ. Sci. Technol., 2024, 58(34), 14973−14993(内封面论文).
[5] Yunchi Zhou, Ying Wang*, et al. Using Machine Learning to Predict Adverse Effects of Metallic Nanomaterials to Various Aquatic Organisms. Environ. Sci. Technol., 2023, 57(46), 17786−17795(内封面论文).