宋子盈，燕山大学人工智能学院讲师、硕士生导师，北京交通大学计算机科学与技术博士。研究方向为具身智能机器人和自动驾驶，包括世界模型、VLA、空间智能、3D目标检测、端到端自动驾驶规划、扩散模型/Flow Matching轨迹生成等。成果发表CCF-A或者中科院一区多篇，包括不限于：CVPR/ICCV/ECCV、IJCAINIPSICML/MM/IEEE TPAMI/TGRS/TCSVT/TITS/TNNLS等，Google Scholar引用约2000+次。具体成果请看谷歌学术：https://scholar.google.com/citations?user=tIjCAKEAAAAJ&hl=en

联系邮箱：22110110@bjtu.edu.cn   songziying@ysu.edu.cn songziying1997@gmail.com   

部分发表论文:

Ziying Song, et al. Don‘t Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving, CVPR2025 CCF-A 会议 （端到端自动驾驶）

Ziying Song, et al. Graphbev: Towards robust bev feature alignment for multi-modal 3d object detection, ECCV2024 CCF-B 

Ziying Song, et al. RoboFusion: A Robust Framework for Multi-Modal 3D Object Detection via SAM, IJCAI2024 CCF-A 会议

Ziying Song, et al. GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Obiect Detection, ICCV2023 CCF-A 会议

Ziying Song, et al. GraphAlign++: An Accurate Feature Alignment by Graph Matching for Multi-Modal 3D Object Detection, TCSVT2024 IEEE 汇刊 SCI-Q1 ESI高被引