个人简介

雷名龙，副教授，硕士生导师，计算机学院、北京人工智能研究院教师。2019年毕业于中国科学院大学，获工学博士学位。承担国家自然科学基金、北京市自然科学基金等多项纵向课题，在国内外人工智能与数据挖掘著名期刊与会议上发表论文30余篇。

研究方向

面向图数据的机器学习方法与应用，涵盖微观化学分子至宏观社交网络等各个尺度图结构的建模、分析、预测。关注图深度学习的表达能力、泛化能力、鲁棒性、轻量化等方面的研究。典型应用包括智能交通系统、智能气象系统、计算社会学、计算生物学、AI for Science等。

学术兼职

学术期刊审稿人：IEEE TKDE、TNNLS、TCYB、TITS，TRC，PR，NN，KBS等。

科研项目

[1]北京市自然科学基金面上项目，基于轻量级时空图神经网络的交通预测方法研究

[2]国家自然科学基金专项项目，基于多任务图学习的社交网络异常用户检测方法研究

[3]北京市朝阳区博士后工作经费资助，基于高阶图卷积神经网络的脑疾病预测方法研究

主要论文论著

[1]Jing He, Junzhong Ji, and Minglong Lei*. Spatio-temporal transformer network with physical knowledge distillation for weather forecasting. In 33th Conference on Information and Knowledge Management (CIKM), 819–828, 2024.

[2]Junzhong Ji, Jing He, Minglong Lei*, Muhua Wang, and Wei Tang. Spatio-temporal transformer network for weather forecasting. IEEE Transactions on Big Data, 2024.

[3]Ruibin Zeng†, Minglong Lei†, Lingfeng Niu†, and Lan Cheng. A unified pre-training and adaptation framework for combinatorial optimization on graphs. Science China Mathematics, 67, 1439–1456, 2024.

[4]Chengxi Song, Lingfeng Niu, and Minglong Lei*. Two-level adversarial attacks for graph neural networks. Information Sciences, 654:119877, 2024.

[5]Junzhong Ji, Fan Yu, Minglong Lei*. Self-Supervised Spatiotemporal Graph Neural Networks with Self-Distillation for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 24(2), 1580-1593, 2023.

[6]Junzhong Ji, Hao Jia, Yating Ren, Minglong Lei*. Supervised Contrastive Learning with Structure Inference for Graph Classification. IEEE Transactions on Network Science and Engineering, 10(3):1684–1695, 2023.

[7]Minglong Lei, Pei Quan, Rongrong Ma, Yong Shi, Lingfeng Niu*. DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation. IEEE Transactions on Cybernetics, 52(2), 912-924, 2022.

[8]Junzhong Ji, Yating Ren, Minglong Lei*. FC-HAT: Hypergraph Attention Network for Functional Brain Network Classification. Information Sciences, 608, 1301-1316, 2022.

[9]Junzhong Ji, Ye Liang, Minglong Lei*. Deep attributed graph clustering with self-separation regularization and parameter-free cluster estimation. Neural Networks, 142, 522-533, 2021.

[10]Jiabin Liu, Biao Li*, Minglong Lei*, Yong Shi. Self-supervised knowledge distillation for complementary label learning. Neural Networks, 155, 318-327, 2022.

[11]Hong Yang, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, Peng Zhang. Discrete embedding for latent networks. In 29th International Conference on International Joint Conferences on Artificial Intelligence (IJCAI), 1223-1229, 2020.