个人信息

罗迪新，长聘副教授，研究员，博士生导师。于上海交通大学获得学士和博士学位，博士在读期间于美国佐治亚理工学院访学。先后任加拿大多伦多大学和美国杜克大学博士后、研究员。主要研究方向为机器学习与人工智能，尤其是可控视频内容编辑与多模态学习。已发表领域顶级国际会议及期刊论文40余篇，其中以第一作者或通讯作者发表CCF-A类论文20余篇（包括TPAMI、TKDE、CVPR、ACM-Multimedia、IJCAI、AAAI、ICML、NeurIPS等），授权国家发明专利9项，主持国家自然科学基金项目、北京市自然科学基金面上项目、人工智能教育部重点实验室开放课题等。长期担任ICML、NeurIPS、WebConf、AAAI、ACM Multimedia等多个国际顶级会议程序委员，及TPAMI、TKDE、TNNLS等顶级期刊审稿人。

招生计划：招收硕士生和博士生，同时欢迎优秀的本科生加入实验室。

个人主页：https://dixinluo.github.io/

科研方向

机器学习、人工智能

代表性学术成果

本页面不常更新，最新科研进展和成果请见：

个人主页：https://dixinluo.github.io/

Google Scholar：https://scholar.google.com/citations?user=yhyPrGIAAAAJ

【近期主要论文】

**JOURNAL**

1. Dixin Luo, H. Xu*, and L. Carin. “Differentiable Hierarchical Optimal Transport for Robust Multi-View Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 45.6 (2022): 7293-7307.

2. H. Xu, J. Liu, Dixin Luo*, and L. Carin. “Representing graphs via Gromov-Wasserstein factorization.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 45.1 (2022): 999-1016.

**CONFERENCE**

1. S. Zhu, Y. Wang, H. Xu, and Dixin Luo*. “Weakly-supervised movie trailer generation driven by multi-modal semantic consistency.” In 34th International Joint Conference on Artificial Intelligence (IJCAI), pp. 10234-10242. 2025.

2. H. Cheng, and Dixin Luo*. “Inferring Directed Acyclic Graphs from Event Sequences via Learning Gromov-Wasserstein-Regularized Hawkes Processes.” In Companion Proceedings of the ACM on Web Conference, pp. 911-914. 2025.

3. M. Cheng, Dixin Luo, and H. Xu. “WatE: A Wasserstein t-distributed Embedding Method for Information-enriched Graph Visualization.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 39, no. 15, pp. 16010-16018. 2025.

4. Y. Wang, J. Teng, J. Cao, Y. Li, C. Ma, H. Xu, and Dixin Luo*. “Efficient video face enhancement with enhanced spatial-temporal consistency.” In Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), pp. 2183-2193. 2025.

5. Y. Wang, S. Zhu, H. Xu, and Dixin Luo*. “An Inverse Partial Optimal Transport Framework for Music-guided Trailer Generation.” In Proceedings of the 32nd ACM International Conference on Multimedia (ACM MM), pp. 9739-9748. 2024.

6. S. Zhu, and Dixin Luo*. ”Enhancing Multi-modal Contrastive Learning via Optimal Transport-Based Consistent Modality Alignment.” In Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 157-171. 2024.

7. H. Liu, Dixin Luo, and H. Xu. “Inferring Iterated Function Systems Approximately from Fractal Images.” In 33rd International Joint Conference on Artificial Intelligence (IJCAI), pp. 7699-7707. 2024.

8. J. Liang, H. Liu, H. Xu, and Dixin Luo*. “Generalizable Face Landmarking Guided by Conditional Face Warping.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2425-2435. 2024.

9. A. Yue, Dixin Luo, and H. Xu. “A Plug-and-Play Quaternion Message-Passing Module for Molecular Conformation Representation.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 38, no. 15, pp. 16633-16641. 2024.

10. Y. Wang, H. Xu, and Dixin Luo*. “Self-supervised Video Summarization Guided by Semantic Inverse Optimal Transport.” In Proceedings of the 31st ACM International Conference on Multimedia (ACM MM), pp. 6611-6622. 2023.

11. Dixin Luo, T. Yu, and H. Xu*. “Group sparse optimal transport for sparse process flexibility design.” In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI), pp. 6121-6129. 2023.

12. Dixin Luo†, H. Cheng†, Q. Li, and H. Xu*. “Coupled point process-based sequence modeling for privacy-preserving network alignment.” In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI), pp. 6112-6120. 2023.

13. Y. Xiang, Dixin Luo, and H. Xu*. “Privacy-preserved evolutionary graph modeling via Gromov-Wasserstein autoregression.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 37, no. 12, pp. 14566-14574. 2023.

14. Dixin Luo, Y. Wang, A. Yue, and H. Xu*. “Weakly-supervised temporal action alignment driven by unbalanced spectral fused Gromov-Wasserstein distance.” In Proceedings of the 30th ACM International Conference on Multimedia (ACM MM), pp. 728-739. 2022.

承担科研情况

所获奖励

2024年本科生毕设校级重点项目指导教师。

2025年2篇校级优秀硕士论文指导教师。

第十七届北京理工大学教育教学成果奖（研究生类）。

指导学生以第一作者发表CCF-A类论文多篇。

社会兼职

中国计算机学会会员、中国电子学会会员、中国人工智能学会会员。

AAAI 2026 Tutorial“最优传输理论与应用”主办人和主讲人。

WWW 2025 Workshop“最优传输驱动的结构化数据建模与生成”联合主席。

IJCAI 2024 Computer Vision分论坛主席。

The Workshop on Data-driven Knowledge Mobilization, CASCON 2016，联合主席。

备注

欢迎有意来读研、读博、打算在本科阶段接触科研的同学邮件联系。