吕秋杰，男，1993年生，博士，副研究员，硕士生导师。2024年6月毕业于中山大学智能工程学院，获得计算机科学与技术博士学位。CCF TCCC执行委员。长期从事小样本学习、联邦学习、医学图像分析、生物信息等研究工作。在IEEE Transactions on Neural Networks and Learning Systems、Signal Transduction and Targeted Therapy、Chemical Science、Neural Networks、Expert Systems with Applications等领域重要学术期刊发表论文20余篇，并受邀担任IEEE TNNLS、KBS、NN、ESWA、PR等期刊审稿人。
研究经历：
2024.06–至今，郑州大学，人工智能
2023.01–2024.01，新加坡国立大学，医学图像分析
代表性论文：
1.Qiujie Lv, Guanxing Chen, Ziduo Yang, et al. Meta-MolNet: A cross domain benchmark for few examples drug discovery[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024. (中科院一区Top)
2.Qiujie Lv, Guanxing Chen, Ziduo Yang, et al. Meta learning with graph attention networks for low-data drug discovery[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, 35(8): 11218-11230. (中科院一区Top)
3.Qiujie Lv, Guanxing Chen, Haohuai He, et al. TCMBank: bridges between the largest herbal medicines, chemical ingredients, target proteins, and associated diseases with intelligence text mining[J]. Chemical Science, 2023, 14(39): 10684-10701. (中科院一区Top)
4.Qiujie Lv, Guanxing Chen, Haohuai He, et al. TCMBank-the largest TCM database provides deep learning-based Chinese-Western medicine exclusion prediction[J]. Signal Transduction and Targeted Therapy, 2023, 8(1): 127. (中科院一区Top)
5.Qiujie Lv, Jun Zhou, Ziduo Yang, et al. 3D graph neural network with few-shot learning for predicting drug–drug interactions in scaffold-based cold start scenario[J]. Neural Networks, 2023, 165: 94-105.(中科院一区Top)
6.Qiujie Lv, Guanxing Chen, Lu Zhao, et al. Mol2Context-vec: learning molecular representation from context awareness for drug discovery[J]. Briefings in Bioinformatics, 2021, 22(6): bbab317. (中科院二区Top)
7.Qiujie Lv, Chen Hsin-Yi, Zhong Weibin, et al. A multi-task group Bi-LSTM networks application on electrocardiogram classification[J]. IEEE Journal of Translational Engineering in Health and Medicine, 2019, 8: 1-11. (中科院三区)
获奖情况：
2024年 IEEE 超智能技术委员会(Hyper-Intelligence Technical Committee，HITC) 杰出博士论文奖
2024年 博士研究生“国家奖学金”；
招生信息：
最新动态见：https://scholar.google.com/citations?user=Gu-qh44AAAAJ
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欢迎对人工智能、深度学习、医学图像分析、生物信息等方向感兴趣的优秀学子报考研究生！
联系方式：lvqiujie@zzu.edu.cn，15515589793（微信）
