朱强，男，1984年9月生，博士。2008年6月毕业于华中农业大学信息管理专业，获学士学位；2014年12月毕业于华中科技大学计算机应用技术专业，获硕士学位；2020年6月毕业于华中师范大学管理科学与工程专业，获博士学位。
邮箱：qzhu@wtu.edu.cn
1.主要研究方向
自然语言处理、生物信息学。
2.教学、科研项目
湖北省教育厅指导项目，“基于异构网络融合和图嵌入的病毒-宿主交互预测”，2021.1—2021.12，主持；
国家自然科学基金面上项目—基于多组学数据的微生物高阶相互作用预测关键 技术研究，2019.1—2022.12, 参与
武汉纺织大学，教研项目，“新工科”背景下课程教学改革研究与实践—以“自然语言处理”课程为例，2022.3-2024.2，主持；
横向项目，“化工药品爆旺平滞生命周期预测系统”，2021年，经费5万，参与；
3.论文与专利
[1] Q. Zhu, Dai Q, Wang B, et al. VHINFGM: Virus-Host Interaction prediction via Network Fusion and Graph Mining. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021: 2977-2984.
[2] Q. Zhu, B. Li, T. He, G. Li, and X. Jiang, "Robust biomarker discovery for microbiome-wide association studies.," Methods, vol. 173, pp. 44–51, 2020.
[3] Q. Zhu, B. Huo, H. Sun, B. Li, and X. Jiang, "Application of Deep Learning in Microbiome," Journal of Artificial Intelligence for Medical Sciences, vol. 1, no. 1–2, pp. 23–29, 2020.
[4] Q. Zhu, X. Jiang, M. Pan, and T. He, "Graph Embedding Deep Learning Guides Microbial Biomarkers’ Identification.," Frontiers in Genetics, vol. 10, p. 1182, 2019.
[5] Q. Zhu, X. Jiang, X. Hu, and T. He, "An Ensemble Feature Selection Method Based on Deep Forest for Microbiome-Wide Association Studies," BIBM, 2018, pp. 248–253.
[6] Q. Zhu, M. Pan, X. Jiang, X. Hu, and T. He, "The Phylogenetic Tree based Deep Forest for Metagenomic Data Classification," BIBM, 2018, pp. 279–282.
[7] M. Pan, Y. Zhang, Q. Zhu, B. Sun, T. He, and X. Jiang, "An adaptive term proximity based rocchio's model for clinical decision support retrieval.," BMC Medical Informatics and Decision Making, vol. 19, no. 9, pp. 1-11, 2019.
[8] Q. Zhu, C. Han, Q. Zhu, T. He, and X. Jiang, "Integrating Deep Textual Features to Probability Matrix Factorization for Metabolite-disease Association Prediction," BIBM, 2019, pp. 628-633.