殷荣，博士，副教授。长期从事信息内容安全、大语言模型、图神经网络、机器学习理论等方向研究，发表顶级会议和期刊论文近30篇，其中 CCF-A/中科院一区论文近20篇，涵盖 NeurIPS、ICML、AAAI、IJCAI、IEEE TIP、IEEE TKDE、IEEE TNNLS、IEEE TMM 和 Information Fusion 等。主持/参与国家级或省部级重点项目20余项，包括国家自然科学基金委青年/面上基金、国家重点研发计划、中科院特别研究助理项目等。曾入选中国科学院特别研究助理、中国科学院信息工程研究所优秀引进人才，担任10余个CCF-A类国际会议的程序委员，比如：ICML、NeurIPS、ICLR、ACL、JMLR，担任国际期刊 MDPI Mathematics（JCR-Q1）和Cybersecurity（JCR-Q1，CCF-T1）客座编辑、信息安全学报（CCF-T2）青年编委，担任 CCF 人工智能与模式识别专委会委员、中国指挥与控制学会情报与智能认知专委会委员。 部分国际会议/期刊论文： (1) Rong Yin, Ruyue Liu, Xiaoshuai Hao, Xingrui Zhou, Yong Liu, Can Ma, Weiping Wang. Multi-Modal Molecular Representation Learning via Structure Awareness. In IEEE Transactions on Image Processing, 2025, 34: 3225-3238. (TIP 2025) (CCF-A，中科院一区，影响因子：13.7). (2) Ruyue Liu, Rong Yin*（通讯作者), Xiangzhen Bo, Xiaoshuai Hao, Yong Liu, Jinwen Zhong, Can Ma, Weiping Wang. SSTAG: Structure-Aware Self-Supervised Learning Method for Text-Attributed Graphs. In Proceedings of Advances in Neural Information Processing Systems, 2025. (NeurIPS 2025) (CCF-A). (3) Ruyue Liu, Rong Yin*（通讯作者), Yong Liu, Xiaoshuai Hao, Haichao Shi, Can Ma, Weiping Wang. AS-GCL: Asymmetric Spectral Augmentation on Graph Contrastive Learning. In IEEE Transaction on Multimedia, 2025. (TMM 2025)(中科院一区，影响因子：9.7). (4) Xiaoshuai Hao, Yunfeng Diao*, Mengchuan Wei, Yifan Yang, Peng Hao, Rong Yin*（通讯作者), et al. MapFusion: A novel BEV feature fusion network for multi-modal map construction. In Information Fusion, 2025. (IF 2025)(中科院一区，影响因子：14.8). (5) Xiaoshuai Hao, Lingyu Liu, Yunfeng Diao, Rong Yin, Pengwei Wang, Jing Zhang, Lingdong Kong, Shu Zhao. SafeMap: Robust HD Map Construction from Incomplete Observations. In Proceedings of the 42th International Conference on Machine Learning. (ICML 2025) (CCF-A). (6) Xiaoshuai Hao, Guanqun Liu, Yuting Zhao, Yuheng Ji, Mengchuan Wei, Haimei Zhao, Lingdong Kong, Rong Yin*（通讯作者), Yu Liu*. MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception. In IEEE International Conference on Multimedia & Expo. (ICME 2025) (CCF-B). (7) Xuning Zhang, Jian Li, Rong Yin, Weiping Wang. FedNK-RF: Federated Kernel Learning with Heterogeneous Data and Optimal Rates. In IEEE Transactions on Neural Networks and Learning Systems, 2025. (TNNLS 2025) (中科院一区，影响因子：8.9). (8) Xiaoshuai Hao, Yunfeng Diao, Rong Yin, et al. DADA++: Dual Alignment Domain Adaptation for Unsupervised Video-Text Retrieval. ACM Transactions on Multimedia Computing, Communications, and Applications, 2025. (TOMM 2025) (CCF-B) (9) Xiaoshuai Hao, Lingyu Liu, Yuting Zhao, yuheng ji, Luanyuan Dai, Peng Hao, dingzhe li, Shuai Cheng, Rong Yin. What Really Matters for Robust Multi-Sensor HD Map Construction? In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. (IROS 2025) (CORE-A). (10) Zhihui Zhang, Zirui Wang, Rong Yin, Wei Zhou, Long Chen, Ruiyu Liang, Hanning Yuan, Xiaoshuai Hao. Dual Prompt Clustering: Aligning and Adapting Multi-Views via Prompt Learning. Neurocomputing. (NC 2025) (中科院二区，影响因子：6.5). (11) Xunyu Zhu , Jian Li, Rong Yin, Can Ma, Weiping Wang. Improving Mathematical Reasoning Abilities of Small Language Models via Key-Point-Driven Distillation. In Proceedings of International Joint Conference on Neural Networks. (IJCNN 2025) (CORE-A). (12) Xunyu Zhu , Jian Li, Rong Yin, Can Ma, Weiping Wang. Improving Mathematical Reasoning Capabilities of Small Language Models via Feedback-Driven Distillation. In Proceedings of International Joint Conference on Neural Networks. (IJCNN 2025) (CORE-A). (13) Ruyue Liu, Rong Yin*（通讯作者), Yong Liu, Weiping Wang. ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network. In Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024, 38(12): 13990-13998. (AAAI 2024) (CCF-A). (14) Ruyue Liu, Rong Yin*（通讯作者), Yong Liu, Weiping Wang. Unbiased and Augmentation-Free Self-Supervised Graph Representation Learning. In Pattern Recognition, 2024. (PR 2024) (中科院一区，影响因子：8). (15) Jinhui Pang, Changqing Lin, Xiaoshuai Hao, Rong Yin, et al. FTF-ER: Feature-Topology Fusion-Based Experience Replay Method for Continual Graph Learning. In Proceedings of the ACM Multimedia, 2024: 8336-8344. (MM 2024) (CCF-A). (16) Xiaoshuai Hao, Ruikai Li, Hui Zhang, Dingzhe Li, Rong Yin, et al. MapDistill: Boosting Efficient Camera-based HD Map Construction via Camera-LiDAR Fusion Model Distillation. In Proceedings of European Conference on Computer Vision, 2024: 166-183. (ECCV 2024) (CCF-B). (17) Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Scalable Kernel k-Means with Randomized Sketching: From Theory to Algorithm. In IEEE Transactions on Knowledge and Data Engineering, 2023, 35(9): 9210-9224. (TKDE 2023) (CCF-A，中科院一区，影响因子：9.235). (18) Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Randomized Sketches for Clustering: Fast and Optimal Kernel k-Means. In Proceedings of Advances in Neural Information Processing Systems, 2022, 35: 6424-6436. (NeurIPS 2022) (CCF-A). (19) Rong Yin, Yong Liu, Dan Meng. Distributed Randomized Sketching Kernel Learning. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, 2022, 36(8): 8883-8891. (AAAI 2022) (CCF-A). (20) Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Distributed Nystrom Kernel Learning with Communications. In Proceedings of the 28th International Conference on Machine Learning, PMLR, 2021: 12019-12028. (ICML 2021) (CCF-A). (21) Rong Yin, Yong Liu, Lijing Lu, Weiping Wang, Dan Meng. Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm. In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020, 34(04): 6696-6703. (AAAI 2020) (CCF-A). (22) Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Sketch Kernel Ridge Regression using Circulant Matrix: Algorithm and Theory. In IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(9): 3512-3524. (TNNLS 2020) (中科院一区，影响因子：11.683). (23) Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Extremely sparse Johnson-Lindenstrauss transform: From theory to algorithm. In Proceedings of IEEE International Conference on Data Mining, 2020: 1376-1381. (ICDM 2020) (CCF-B). (24) Jian Li, Yong Liu, Rong Yin, Weiping Wang. Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019: 2880-2886. (IJCAI 2019) (CCF-A). (25) Jian Li, Yong Liu, Rong Yin, Weiping Wang. Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019: 2887-2893. (IJCAI 2019) (CCF-A). (26) Jian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang. Multi-class learning: From theory to algorithm. In Proceedings of Advances in Neural Information Processing Systems, 2018. (NeurIPS 2018) (CCF-A). (27) Lijing Lu, Rong Yin, Yong Liu, Weiping Wang. Hashing Based Prediction for Large-Scale Kernel Machine. In Proceedings of the International Conference on Computational Science, 2020: 496-509. (ICCS 2020)(CORE-A). |
