Artificial Intelligence Algorithms Group

方向负责人：周扬帆

中国科学院苏州纳米技术与纳米仿生研究所
博士
助理研究员
江苏省卓越博士后
中国科学院特别研究助理
智能算法方向负责人
邮箱：yfzhou2020@sinano.ac.cn
地址：江苏省苏州市工业园区若水路398号
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负责人简介

  2023年博士毕业于中国科学技术大学，入选2023年江苏省卓越博士后计划。曾获得国家奖学金、中国光谷奖学金、中科大优秀毕业生等荣誉，主要从事智能无人系统中基于深度学习的视觉算法、定位算法、集群协同算法及优化算法方面的研究。

  科研成果方面，目前以第一或通讯作者身份在IEEE TNNLS、IEEE TITS、IEEE TIM、IEEE TETCI、EAAI、ICRA等高水平期刊和会议发表论文12篇，参与合作发表论文7篇，申请发明专利6项。

  科研项目方面，担任KJW项目子课题负责人2项；主持中国科学院特别研究助理项目、广东省基础与应用基础研究基金联合基金项目等；参与KJW、国家重点研发计划、中科院率先引才行动、国家自然科学基金面上等项目。

方向成员

博士生

魏文晖 、 乔麟（联培）

硕士生

李志（联培）、 王森（联培）、 李祺（联培）、 周子恒（硕博连读）

实习生

于晨彬（本科）

研究内容

  1. Autonomous localization algorithms for intelligent unmanned systems；
  2. Fast Motion Planning Algorithms for Intelligent Unmanned Systems；
  3. Multi-object Detection Algorithms for UAVs；
  4. Swarm Cooperative Control Algorithms for Uavs;
  5. Optimization Algorithms for Deep Learning.

已发表论文

  1. 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.
  2. 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, DOI: 10.1109/TNNLS.2022.3143554.
  3. 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, 72:1-13, 2023.08.01, doi: 10.1109/TIM.2023.3300446.
  4. 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, 7(2): 565-577, 2023.4, DOI: 10.1109/TETCI.2022.3171797.
  5. 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, 121: 105968, 2023.5, DOI: 10.1016/j.engappai.2023.105968.
  6. Jinfeng Gao, Fengyuan Wu, Cheng Cheng, Chengbai Wu, Yangfan Zhou*. A Markov random field based method for removing invalid unwrapping phase points in 3D reconstruction. IET Image Process, 2023, ISSN: 1751-9659.
  7. Yangfan Zhou, Kaizhu Huang, Cheng Cheng, Xuguang Wang, and Xin Liu. LightAdam: Towards a Fast and Accurate Adaptive Momentum Online Algorithm[J]. Cognitive Computation, 14:764-779, 2022.1.11, DOI: 10.1007/s12559-021-09985-9.
  8. Yangfan Zhou, Mingchuan Zhang, Junlong Zhu, et al. A Randomized Block-Coordinate Adam online learning optimization algorithm[J]. Neural Computing & Application, 32: 12671–12684, 2020.01.18. DOI: 10.1007/s00521-020-04718-9.
  9. Mingchuan Zhang, Yangfan Zhou, Quanbo Ge, Rruijuan Zheng and Qingtao Wu, Decentralized Randomized Block-Coordinate Frank–Wolfe Algorithms for Submodular Maximization Over Networks[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(8): 5081-5091, 2022.08. DOI: 10.1109/TSMC.2021.3112691.
  10. Mingchuan Zhang, Yangfan Zhou, Wei Quan, Junlong Zhu, Rruijuan Zheng and Qingtao Wu, Online Learning for IoT Optimization: A Frank–Wolfe Adam-Based Algorithm[J]. IEEE Internet of Things Journal, 7(9): 8228-8237, 2020.09. DOI: 10.1109/JIOT.2020.2984011.
  11. Yangfan Zhou, Mingchuan Zhang, Junlong Zhu, et al. A Randomized Block-Coordinate Adam online learning optimization algorithm[J]. Neural Computing & Application, 32: 12671–12684, 2020.01.18. DOI: 10.1007/s00521-020-04718-9.