目录
2023.10至今 华南农业大学动物科学学院，副教授
2017.11−2019.10 美国罗格斯大学，联合培养博士生，导师：朱浩 教授
广州大学2022年度学术新锐
华南农业大学动物科学学院2023年青年教师教学能力比赛“一等奖”
第十次全国毒理学大会优秀论文
E方知库年度论文特等奖
Carbon Research期刊2023年度优秀青年编委
[2] 国家自然科学基金青年项目：基于原子尺度深度学习的纳塑料及其复合污染物构效关系和毒性预测研究，2022/01−2024/12，30万，结题，主持。
[3] 华南农业大学高层次人才科研启动项目，60万元， 2023/10-2028/10，在研，主持。
[4] 2024年华南农业大学研究生教育创新计划项目（专业学位研究生实践教学资源建设与培养模式改革研究项目），0.8万元，结题，主持。
[5] 广州市科技计划基础与应用基础项目：基于端到端深度学习的纳塑料毒性预测研究，2021/04−2024/03，5万，结题，主持。
[6] 广州大学人才培育项目：大数据和纳米结构数字化驱动的深度学习预测纳塑料毒性研究，2021/03−2023/03，10万，结题，主持。
[2] Xiliang Yan, Tongtao Yue, David A. Winkler, Yongguang Yin, Hao Zhu, Bing Yan*. Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation. Chemical Reviews, 2023, 123, 13, 8575-8637. (中科院一区，IF: 72.087)
[3] Jiachen Yan, Xiliang Yan*, Song Hu, Hao Zhu, Bing Yan*. Comprehensive Interrogation on Acetylcholinesterase Inhibition by Ionic Liquids Using Machine Learning and Molecular Modeling. Environmental Science & Technology, 2021, 55, 21, 14720-14731. (中科院一区，IF: 11.357)
[4] Jiachen Yan#, Guohong Liu#, Hanle Chen, Song Hu, Xiaohong Wang, Bing Yan*, Xiliang Yan*. ILTox: A Curated Toxicity Database for Machine Learning and Design of Environmentally Friendly Ionic Liquids. Environmental Science & Technology Letters, 2023, 10, 11, 983-988. (中科院一区，IF: 11.558)
[5] Chen Jia#, Xiaofang Li#, Song Hu, Guohong Liu, Jiansong Fang*, Xiaoxia Zhou*, Xiliang Yan*, Bing Yan. Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines. Analytical Chemistry, 2025, 97, 1, 783-792. (中科院一区，IF: 6.8，Supplementary Cover)
[6] Song Hu, Guohong Liu, Jin Zhang, Jiachen Yan, Hongyu Zhou, Xiliang Yan*. Linking Electron Ionization Mass Spectra of Organic Chemicals to Toxicity Endpoints through Machine Learning and Experimentation. Journal of Hazardous Materials, 2022, 431, 128558. (中科院一区，IF: 14.224)
[7] Guohong Liu, Xiliang Yan*, Chengjun Li*, Song Hu, Jiachen Yan, Bing Yan*. Unraveling the joint toxicity of transition-metal dichalcogenides and per- and polyfluoroalkyl substances in aqueous mediums by experimentation, machine learning and molecular dynamics. Journal of Hazardous Materials, 2023, 443, 130303. (中科院一区，IF: 14.224)
[8] Ying He#, Guohong Liu#, Song Hu, Xiaohong Wang, Jianbo Jia, Hongyu Zhou*, Xiliang Yan*. Implementing Comprehensive Machine Learning Models of Multispecies Toxicity Assessment to Improve Chemical Regulation. Journal of Hazardous Materials, 2023, 458, 131942. (中科院一区，IF: 14.224)
[9] Xiliang Yan, Alexander Sedykh, Wenyi Wang, Xiaoli Zhao, Bing Yan*, Hao Zhu*. In Silico Profiling Nanoparticles: Predictive Nanomodeling Using Universal Nanodescriptors and Various Machine Learning Approaches. Nanoscale, 2019, 11, 17, 8352-8362. (中科院二区，IF: 8.307)
[10] Xiliang Yan, Jin Zhang, Daniel P. Russo, Hao Zhu*, Bing Yan*. Prediction of Nano−Bio Interactions through Convolutional Neural Network Analysis of Nanostructure Images. ACS Sustainable Chemistry and Engineering, 2020, 8, 51, 19096-19104. (中科院一区，IF: 9.224)
[11] Ying He, Guohong Liu, Chengjun Li*, Xiliang Yan*. Reaching the full potential of machine learning in mitigating environmental impacts of functional materials. Reviews of Environmental Contamination and Toxicology. 2022, 260, 1, 1-19. (中科院二区，IF: 7.9)
[12] Jiahui Wang, Gaoxing Su*, Xiliang Yan*, Wei Zhang, Jianbo Jia, Bing Yan*. Predicting cytotoxicity of binary pollutants towards a human cell panel in environmental water by experimentation and deep learning methods. Chemosphere, 2022, 287, 132324. (中科院二区，IF: 8.943)
[13] Xiliang Yan, Jianfen Fan*, Yi Yu, Jian Xu, Mingming Zhang. Transport Behavior of a Single Ca2+, K+, and Na+ in a Water-Filled Transmembrane Cyclic Peptide Nanotube. Journal of Chemical Information and Modeling, 2015, 55, 5, 998-1011. (中科院二区，IF: 6.162)
[14] Yinju Qin, Xiaohong Wang*, Xiliang Yan*, Di Zhu, Jia Wang, Siying Chen, Shuo Wang, Yang Wen, Chrostopher J. Martyniuk, Yuanhui Zhao*. Developmental Toxicity of Fenbuconazole in Zebrafish: Effects on Mitochondrial Respiration and Locomotor Behavior. Toxicology, 2022, 470, 153137. (中科院三区，IF: 4.571)
[15] Yuanchao Li, Jing Sun*, Cuijuan Jiang, Xiliang Yan*. DFT perspective of gas sensing properties of metal oxide nanocages toward trimethylamine: Effects of humidity, temperature and electric field. Materials Today Sustainability, 2024, 25, 100668. (中科院三区，IF: 7.8)
[16] Yuanchao Li, Cuijuan Jiang, Xiliang Yan*. MnN4 embedded zeolite-templated carbon for methylamine and trimethylamine sensing: Insights from DFT study. Journal of Molecular Liquids, 2024, 397, 124090. (中科院二区，IF: 6)
[17] Yuanchao Li, Xiliang Yan*. Effect of Different Strategies for Modifying Graphene on the Adsorption and Gas Sensing of Trimethylamine: Insights from DFT Study. International Journal of Hydrogen Energy 2024, 61, 1330-1339. (中科院二区，IF: 7.2)
[18] Ying He, Fang Liu, Weicui Min, Guohong Liu, Yinbao Wu, Yan Wang, Xiliang Yan*, Bing Yan. De novo Design of Biocompatible Nanomaterials Using Quasi-SMILES and Recurrent Neural Networks. ACS Applied Materials & Interfaces, 2024, 16, 48, 66367–66376. (中科院二区，IF: 8.3)
[19] Xiaofang Li, Hanle Chen, Jiachen Yan, Guohong Liu, Chengjun Li, Xiaoxia Zhou, Yan Wang, Yinbao Wu, Bing Yan, Xiliang Yan*. Balancing the Functionality and Biocompatibility of Materials with a Deep-Learning-Based Inverse Design Framework. Environment & Health 2024, 2, 12, 875–885. (中国科技期刊卓越行动计划”高起点新刊，Supplementary Cover)
[20] 胡松, 刘国红, 何英, 颜嘉晨, 陈寒乐, 闫希亮*, 闫兵. 基于端到端深度学习的有机光伏材料光电转化效率预测[J] . 环境工程, 2022, 40 (6), 188-193. (核心期刊)
[2] 周小霞，何帅，闫兵，闫希亮. 一种用于定量分析环境水体中纳塑料的方法. 2022-11-11. ZL202110288797.X
[3] 刘国红，闫希亮，李成俊，颜嘉晨，胡松，闫兵. 一种基于实验和计算的二维纳米复合物毒性评价方法. 2024-05-10. 中国. ZL202211358675.4
[4] 闫希亮，胡松，刘国红，颜嘉晨，周宏钰，周小霞，闫兵. 一种基于谱图分析的有机物生物毒性预测方法及系统. 申请号：202111270668.4
[4] 闫希亮，闵维翠，刘国红，陈寒乐，何英，闫兵. 一种基于Quasi-SMILES 和循环神经网络的纳米颗粒反向设计方法. 申请号：202211236491.0
[5] 闫希亮，何英，刘国红，闵维翠，陈寒乐，闫兵. 一种用于筛选金属有机框架吸附甲苯的机器学习方法. 申请号：202310113928.X
[6] 颜嘉晨，闫希亮，刘国红，胡松，闫兵，何思源. 一种离子液体对乙酰胆碱酯酶的毒性预测方法及系统. 申请号：202211092681.X
[8] 闫希亮，闵维翠，刘国红，陈寒乐，何英，闫兵. 一种基于机器学习和虚拟筛选的抗菌纳米颗粒设计方法. 申请号：202310176054.2
[9] 闫希亮，陈寒乐，刘国红，闵维翠，何英，闫兵. 一种基于可解释机器学习的纳塑料细胞毒性预测方法. 申请号：202310202095.4
[10] 闫希亮，贾琛，刘国红，王燕，吴银宝，张菁，闫兵. 一种基于机器学习辅助的金属氧化物纳米酶快速筛选方法. 申请号：202410398240.5
[11] 闫希亮，张菁，刘国红，王燕，吴银宝，贾琛，闫兵. 一种基于多模态数据的跨材料纳米生物效应预测方法. 申请号：202410444764.3
[12] 王燕，闫希亮，陈颖欣. 一种基于机器学习的微塑料影响抗性基因传播评估方法及装置. 申请号：202410799264.1
[13] 王燕，闫希亮，李世凯. 一种基于机器学习的植物抗生素抗性基因传播评估方法及装置. 申请号：202410922646.9
