杨明奇（Yang Mingqi）

● 助理教授（Assistant Professor）

● 办公室：B10南座

● 邮箱：yangmq@scut.edu.cn

工学博士，华南理工大学电子商务系助理教授。

       主要从事图机器学习、AI for Science、算法公平性、商务智能等方向的研究。成果发表在International Conference on Machine Learning (ICML)、The Association for the Advancement of Artificial Intelligence (AAAI)、The Web Conference (WWW)、IEEE Transactions on Knowledge and Data Engineering (TKDE)等机器学习和人工智能领域顶级会议和期刊。

机器学习，图数据挖掘，数据科学与商务智能

       Machine Learning, Graph Mining, Data Science and Business Intelligence

2019.09~2023.06 大连理工大学 博士

2022.10~2023.04 新加坡国立大学 博士联培

2015.09~2018.06 吉林大学 硕士

2011.09~2015.06 山东师范大学 学士

2019.09~2023.06 Dalian University of Technology, PhD

2022.10~2023.04 National University of Singapore, Visiting PhD

2015.09~2018.06 Jilin Technology, MSc.

       2011.09~2015.06 Shandong Normal University, BSc

2025.01~ 华南理工大学 电子商务系 助理教授

2023.08~2024.08 新加坡国立大学 计算机学院 博士后

2018.07~2019.03 小米 人工智能与云平台 研发

2025.01~ South China University of Technology, Department of Electronic Business, Assistant Professor

2023.08~2024.08 National University of Singapore, School of Computing, Postdoc

       2018.07~2019.03 Xiaomi, AI & Cloud, Software Engineer

[1] Runze Wang, Mingqi Yang, Yanming Shen. Bridging Molecular Graphs and Large Language Models. The Association for the Advancement of Artificial Intelligence (AAAI) 2025 (CCF A)

[2] Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi. Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering. International Conference on Machine Learning (ICML) 2023 (CCF A)

[3] Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, Baocai Yin. A New Perspective on the Effects of Spectrum in Graph Neural Networks. International Conference on Machine Learning (ICML) 2022 (CCF A)

[4] Mingqi Yang, Renjian Wang, Yanming Shen, Heng Qi, Baocai Yin. Breaking the Expression Bottleneck of Graph Neural Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022 (CCF A)

[5] Mingqi Yang, Yanming Shen, Heng Qi, Baocai Yin. Soft-mask: Adaptive Substructure Extractions for Graph Neural Networks. The Web Conference (WWW) 2021 (CCF A)

[6] Mingqi Yang, Renjian Wang, Yanming Shen, Heng Qi, Baocai Yin. On the Design of Powerful Aggregations in Graph Neural Networks. KDD Deep Learning on Graphs (DLG) Workshop 2021

[7] 杨明奇, 李占山, 张家晨. 一种基于时间戳的简单表缩减算法. 软件学报, 2019, 30(11): 3355-3363.

[8] Zhe Li, Mingqi Yang, Zhanshan Li. A new variable-oriented propagation scheme for constraint satisfaction problem. International Conference on Knowledge Science, Engineering and Management (KSEM) 2018

      [9] 杨明奇, 李占山, 李哲. 优化求解约束满足问题的MDDc和STR3算法. 软件学报, 2017, 28(12): 3156-3166.