周扬帆

个人简历/Personal resume

  2023年获得中国科学技术大学博士学位，2025年起任中国科学院苏州纳米所副研究员。入选2023年中国科学院特别研究助理资助计划和江苏省卓越博士后计划，主持国家部委级项目子课题、江苏省青年基金、广东省青年基金、苏州市基础研究等纵向课题7项。 长期致力于机器人自主定位导航、目标检测跟踪、深度学习低成本优化等技术研究，近年来在IEEE Trans. Robotics、ISPRS P&RS‌、IEEE Trans. Neural Networks Learn. Syst.、IEEE Trans. Intell. Transp. Syst.、ICRA等高水平期刊和会议上发表论文24篇。

研究方向/Research direction

  1. 无人机机载端自主定位导航技术

  2. 动态场景下弱小目标检测跟踪技术

  3. 深度模型轻量化与低成本训练技术

招生信息/Enrollment information

  电子科学与技术、计算机科学与技术、人工智能、自动化与控制等相关专业

论文专著/The monograph

  1. Yangfan Zhou, Wenhui Wei*, Renshu Li, Xin Liu, Jiadong Li*. A continual evolving Visual-Inertial Odometry for drones in flight [J], ISPRS Journal of Photogrammetry and Remote Sensing, 2026, 236: 49-64.

  2. Wenhui Wei, Xin Liu, Jiadong Li*, Yangfan Zhou*. Self-RIO: Robust Self-Supervised Odometry Across Diverse Weather and Terrain by Fusing Radar and Inertial Signals[J], IEEE Transactions on Intelligent Transportation Systems, 2026.4, 1-15.

  3. Wenhui Wei, Yangfan Zhou*, Yimin Hu, Zhi Li, Sen Wang, Xin Liu, and Jiadong Li. BotVIO: A Lightweight Transformer-Based Visual-Inertial Odometry for Robotics, IEEE Transactions on Robotics, 2025, 41: 3760-3778.

  4. Wenhui Wei, Yang Ping, Jiadong Li, Xin Liu, and Yangfan Zhou*. Fine-MVO: Toward Fine-Grained Feature Enhancement for Self-Supervised Monocular Visual Odometry in Dynamic Environments[J], IEEE Transactions on Intelligent Transportation Systems, 2024, 25(10): 13947-13960.

  5. Wenhui Wei, Jiantao Li, Kaizhu Huang, Jiadong Li, Xin Liu, and Yangfan Zhou*. Lite-SVO: Towards A Lightweight Self-Supervised Semantic Visual Odometry Exploiting Multi-Feature Sharing Architecture[C], IEEE International Conference on Robotics and Automation (ICRA), 2024.

  6. Wenhui Wei, Kaizhu Huang, Xin Liu*, and Yangfan Zhou*. GSL-VO: A Geometric-Semantic Information Enhanced Lightweight Visual Odometry in Dynamic Environments[J]. IEEE Transactions on Instrumentation and Measurement, 2023.08.01, 72: 1-13.

  7. Yangfan Zhou, Kaizhu Huang, Cheng Cheng, Xuguang Wang, Amir Hussain, and Xin Liu. FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity[J], IEEE Transactions on Neural Networks and Learning Systems, 2023.9, 34(9): 6515-6529.

  8. Yangfan Zhou, Kaizhu Huang, Cheng Cheng, Xuguang Wang, Amir Hussain, and Xin Liu. Towards Faster Training Algorithms Exploiting Bandit Sampling from Convex to Strongly Convex Conditions[J], IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.4, 7(2): 565-577.

  9. Yangfan Zhou, Kaizhu Huang, Jiang Li, Cheng Cheng, Xuguang Wang, Amir Hussian, and Xin Liu. Randomized Block-Coordinate Adaptive Algorithms for Nonconvex Optimization Problems[J], Engineering Applications of Artificial Intelligence, 2023.5, 121: 105968.

  10. Yangfan Zhou, Kaizhu Huang, Cheng Cheng, Xuguang Wang, and Xin Liu. LightAdam: Towards a Fast and Accurate Adaptive Momentum Online Algorithm[J], Cognitive Computation, 2022.3, 14: 764-779.