About me

Hi there! I am Wenjie Du, an Associate Researcher at the School of Software Engineering/Suzhou Institute for Advanced Research, University of Science and Technology of China USTC, and a member of the USTC-DILab. I received my Ph.D. in the School of Software Engineering, USTC in 2024, supervised by Prof. Xike Xie and Prof. Yang Wang. Before starting my Ph.D. study, I received my Bachelor’s degree from Northeastern University (NEU) in 2018.

I have published about 20 high-level papers on research journals and conferences, including some top level international journals and conferences, such as Nature Water, Nature Communication, PNAS, JACS, ACL,IJCAI, IEEE TKDE, IEEE BIBM and so on. I am broadly interested in generalized AI for Science especially in the Environment, Chemistry and Materials science. You can find my CV here: Curriculum Vitae.

🌟招收对AI4Science、深度学习、LLM感兴趣且有较好数理基础的学生 [推免/工程实践/远程科研实习]，可通过邮箱（duwenjie@mail.ustc.edu.cn）联系我，请附上个人简历。

🌟中国科学技术大学数据智能实验室(DILab)诚招特任副研究员及博士后! 研究方向包括数据挖掘、机器学习、AI for Science。如您对团队研究方向感兴趣，欢迎您直接与团队负责人汪炀老师联系!

News

* (2025.03) Congratulations to Zhang Shuai for being named an outstanding graduate of the USTC！
* (2025.03) Congratulations to Li Jiahe for being named an outstanding graduate of the USTC！
* (2025.02) One paper on molecular interaction was accepted in ICLR 2025.
* (2025.02) One paper on molecular interaction was accepted in TCBB.
* (2024.11) Congratulations to Li Xuqiang for winning the National Scholarship！
* (2024.08) One paper on molecular property prediction was accepted in BIBM 2024.
* (2024.06) I received the “Outstanding Doctoral Dissertation Award” in USTC.
* (2024.06) My paper titled “Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique” is selected as the best paper (top 3/301).
* (2024.05) One paper on molecular interaction was accepted in ACL 2024.
* (2024.05) One paper on molecular interaction was accepted in IJCAI 2024.
* (2024.05) Successfully passed the "ghFund" review and was selected as "Outstanding" in Tianjin.
* (2024.05) Successfully defended the doctoral dissertation.

Selected Papers

Spatiotemporal Pattern of Greenhouse Gas Emissions in China’s Wastewater Sector and Pathways towards Carbon Neutrality. Nature Water ,2023. (Nature 子刊)
Wenjie Du, JiaYuan Lu, YiRong Hu, Juanxiu Xiao, Jie Wu, Cheng Yang, Baocheng Huang, Shuo Cui, Yang Wang, Wenwei Li.PDF
Spectroscopy-Guided Deep Learning Predicts Solid-Liquid Surface Adsorbate Properties in Unseen Solvents. Journal of the American Chemical Society , 2023. (JACS, 化学领域顶刊NO.1, 中科院一区, IF = 15. 419)
Wenjie Du, Fenfen Ma, Jiahui Zhang, Baicheng Zhang, Xiaoting Yang, Wu Di, Yang Wang, and Jun Jiang.PDF
Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning. Proceedings of the National Academy of Sciences ,2022. (PNAS, 美国科学院院刊, 中科院一区, IF = 11.1)
Baicheng Zhang, Xiaolong Zhang, Wenjie Du, Zhaokun Song, Guozhen Zhang, Guoqing Zhang, Yang Wang, Xin Chen, Jun Jiang, and Yi Luo,.PDF
Deciphering Urban Traffic Impacts on Air Quality by Deep Learning and Emission Inventory. Journal of Environmental Sciences ,2023. (ESI 高被引论文)
Wenjie Du, Lianliang Chen, Haoran Wang, Ziyang Shan, Zhengyang Zhou, Wenwei Li, Yang Wang.PDF
Fusing 2D and 3D Molecular Graphs as Unambiguous Molecular Descriptors for Conformational and Chiral Stereoisomers. Briefings in Bioinformatics ,2023. (JCR Q1, IF= 13.994)
Wenjie Du, Xiaoting Yang, Di Wu, FenFen Ma, Baicheng Zhang, Chaochao Bao, Yaoyuan Huo, Xin Chen, Yang Wang.PDF
MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction. IJCAI ,2023. (CCF A)
Wenjie Du, Shuai Zhang, Ziyuan Zhao, Jun Xia, Junfeng Fang, Yang Wang.PDF
Inverse design of chiral functional films by a robotic AI-guided system. Nature Communications ,2023. (Nature 子刊)
Yifan Xie, Shuo Feng, Linxiao Deng, Aoran Cai, Liyu Gan, Zifan Jiang, Peng Yang, Guilin Ye, Zaiqing Liu, Li Wen, Qing Zhu, Wanjun Zhang, Zhanpeng Zhang, Jiahe Li, Zeyu Feng, Chutian Zhang, Wenjie Du, Lixin Xu, Jun Jiang, Xin Chen & Gang Zou.PDF
Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique. Frontiers of Environmental Science & Engineering ,2023. (JCR Q1)
Yirong Hu, Wenjie Du, Cheng Yang, Yang Wang, Tianyin Huang, Xiaoyi Xu & Wenwei Li.PDF
On regularization for explaining graph neural networks: An information theory perspective. Frontiers of Environmental Science & Engineering ,2024. (TKDE)
Junfeng Fang; Guibin Zhang; Kun Wang; Wenjie Du; Yifan Duan; Yuankai Wu.PDF
SMG-BERT: integrating stereoscopic information and chemical representation for molecular property prediction. Frontiers in Molecular Biosciences ,2023. (JCR Q2)
Jiahui Zhang, Wenjie Du, Xiaoting Yang, Di Wu, Jiahe Li, Kun Wang, Yang Wang.PDF
Flexmol: A flexible toolkit for benchmarking molecular relational learning. NeurIPS ,2024. (CCF A)
Sizhe Liu, Jun Xia, Lecheng Zhang, Yuchen Liu, Yue Liu, Wenjie Du, Zhangyang Gao, Bozhen Hu, Cheng Tan, hongxin xiang, Stan Z. Li.PDF
Text-guided small molecule generation via diffusion model. iScience ,2024. (JCR Q1)
Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, Xiang Wang.PDF
IIB-DDI: Invariant Information Bottle Theory for Out-of-Distribution Drug-Drug Interaction Prediction. IEEE Transactions on Computational Biology and Bioinformatics ,2025. (JCR Q1)
Shuai Zhang, Jiahui Zhang, Xuqiang Li, Di Wu, Sihan Wang, Limin Li, Wenjie Du, Yang Wang.PDF
NovoBench: Benchmarking Deep Learning-based\emph {De Novo} Sequencing Methods in Proteomics. NeurIPS ,2024. (CCF A)
Jingbo Zhou, Shaorong Chen, Jun Xia, Sizhe Liu, Tianze Ling, Wenjie Du, Yue Liu, Jianwei Yin, Stan Z. Li.PDF
EMoNet: An environment causal learning for molecule OOD generalization. BIBM ,2024. (CCF B)
Limin Li, Kuo Yang, Wenjie Du, Zhongchao Yi, Zhengyang Zhou, Yang Wang.PDF
MolCLW: Molecular Contrastive Learning With Learnable Weighted Substructures. BIBM ,2024. (CCF B)
Jiahe Li, Wenjie Du, Yang Wang.PDF
Improving efficiency in rationale discovery for Out-of-Distribution molecular representations. BIBM ,2023. (CCF B)
Jiahui Zhang, Wenjie Du, Di Wu, Jiahe Li, Shuai Zhang, Yang Wang.PDF