马广智，2025年9月加入南京信息工程大学计算机学院、网络空间安全学院。2025年博士毕业于悉尼科技大学（UTS）澳大利亚人工智能研究所（AAII），近年来主要从事迁移学习，领域适应与可信赖机器学习相关研究，近五年发表SCI中科院一区学术论文若干篇，收录在IEEE TFS、IEEE TNNLS、IEEE TCYB等，担任IEEE TFS、IEEE TNNLS、NeurIPS、KDD、AAAI等CCF-A/B类顶级期刊会议审稿人。

近五年成果：

[1]  G Ma, J Lu, G Zhang, Multiview classification through learning from interval-valued data, IEEE Transactions on Neural Networks and Learning Systems, 2024, Volume: 36 Issue: 5.

[2]  G Ma, F Liu, G Zhang, J Lu, Learning from imprecise observations: An estimation error bound based on fuzzy random variables, 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8.

[3]  G Ma, J Lu, F Liu, Z Fang, G Zhang, Multiclass Classification With Fuzzy-Feature Observations: Theory and Algorithms, IEEE Transactions on Cybernetics, 2022, Volume: 54 Issue: 2.

[4]  G Ma, J Lu, F Liu, Z Fang, G Zhang, Domain Adaptation with Interval-valued Observations: Theory and Algorithms, IEEE Transactions on Fuzzy Systems, 2024, Volume: 32 Issue: 5.

[5] G Ma, J Lu, G Zhang, Multi-source Domain Adaptation with Interval-Valued Target Data via Fuzzy Neural Networks, IEEE Transactions on Fuzzy Systems, 2024, Volume: 32 Issue: 5.

[6] G Ma, J Lu, G Zhang, Interval-Valued Observations-Based Multi-Source Domain Adaptation Using Fuzzy Neural Networks, 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[7] J Lu, G Ma, G Zhang, Fuzzy machine learning: A comprehensive framework and systematic review, IEEE Transactions on Fuzzy Systems, 2024, Volume: 32 Issue: 7.