姓名：黄栋

职位：工学博士、讲师

教师简介：

1、学习工作经历：

2013.9-2017.6，福州大学，数学与计算机科学学院计算机科学与技术专业， 工学学士

2017.9-2020.6，福州大学，数学与计算机科学学院计算机技术专业，工学硕士

2021.4-2024.3，日本筑波大学，情报理工学院计算机科学专业，工学博士

2024.8-今，福建农林大学未来技术学院任教

2、主讲课程

本科生课程：《计算机视觉与模式识别》，《人机交互》

硕士生课程：《人工智能导论》

3、研究方向和领域：

机器学习、生物信息、脑机交互、计算机视觉、联邦学习、隐私保护等。

4、发表论文：

[1] Dong Huang, Xiucai Ye*, Tetsuya Sakurai. Multi-party Collaborative Drug Discovery via Federated Learning[J]. Computers in Biology and Medicine，2024:108181. (IF: 7.7，JCR一区)

[2] Dong Huang, Xiucai Ye*, Ying Zhang, and Tetsuya Sakurai. Collaborative analysis for drug discovery by federated learning on non-IID data [J]. Methods, 2023, 219: 1-7.（IF: 4.8，JCR一区）

[3] Dong Huang, Xiucai Ye*, Tetsuya Sakurai. Knowledge distillation-based privacy-preserving data analysis[C]//Proceedings of the Conference on Research in Adaptive and Convergent Systems. 2022: 15-20.

[4] Tianyi Shi, Xiucai Ye*, Dong Huang*, Tetsuya Sakurai. Cancer subtype identification by multi-omics clustering based on interpretable feature and latent subspace learning. Methods, 2024, 231: 144-153. (IF:4.8, JCR一区)

[5] Tianyi Shi, Xiucai Ye*, Dong Huang*, Tetsuya Sakurai. Selecting interpretable features for cancer subtyping on multi-omics data. IEEE International Conference on Bioinformatics and Biomedicine 2024 (IEEE BIBM 2024). (CCF B会议)

[6] Yuzhen Niu, Dong Huang, Yiqing Shi, and Xiao Ke*. Siamese-Network-Based Learning to Rank for No-Reference 2D and 3D Image Quality Assessment, IEEE Access, vol. 7, 2019. (JCR一区)

[7] Peikun Chen, Yuzhen Niu*, Dong Huang. No-reference image quality assessment based on multi- scale convolutional neural networks[C]//Intelligent Computing: Proceedings of the 2019 Computing Conference, Volume 2. Springer International Publishing, 2019: 1202-1216.（EI）

5、联系方式：

    电子邮箱：huangdong@fafu.edu.cn