芦维宁助理研究员

  • Email : luwn@tsinghua.edu.cn
  • 地址:清华大学FIT楼1-109
教育背景

2011年9月-2017年7月 清华大学 自动化系 博士研究生

2007年9月-2011年7月 复旦大学 物理学系 本科

工作履历

2020年4月-至今 清华大学信息国家研究中心 助理研究员

2017年7月-2020年4月 清华大学 航天航空学院 博士后

学术兼职

《飞控与探测》青年编委

研究领域

(1) 多源异构信息融合感知

(2)多智能体协同规划与决策

研究概况

面向环境复杂、信息缺失、状态未知等情况,增强无人群系统的快速感知认知、群智响应的实际作业能力。

奖励与荣誉

(1) 中国图像图形学会科技进步二等奖(2024年)

(2) 中国电子学会科技进步二等奖(2023年)

(3)自动化学会自然科学奖一等奖(2020年)

学术成果

[1] C. Li, W. Lu, Z. Ma, L. Meng and B. Liang, "Highly Efficient Observation Process Based on FFT Filtering for Robot Swarm Collaborative Navigation in Unknown Environments*," 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates, 2024, pp. 10267-10274

[2] Lu W, Tang Y, Liu Y, et al. CatLearning: highly accurate gene expression prediction from histone mark[J]. Briefings in Bioinformatics, 2024, 25(5): bbae373.

[3] Gao, Y., Lin, Q., Ye, S., Cheng, Y., Zhang, T., Liang, B., & Lu, W. (2024). Outlier detection in temporal and spatial sequences via correlation analysis based on graph neural networks. Displays, 84, 102775.

[4] Li, Y., Lu, W., Liu, Y., Meng, D., Wang, X., & Liang, B. (2023). Optimization Design Method of Tendon-Sheath Transmission Path Under Curvature Constraint. IEEE Transactions on Robotics.

[5] Dai, H., Lu, W., Li, X., Yang, J., Meng, D., Liu, Y., & Liang, B. (2022). Cooperative planning of multi-agent systems based on task-oriented knowledge fusion with graph neural networks. Frontiers of Information Technology & Electronic Engineering, 23(7), 1069-1076.

[6] Lu, W., Li, Y., Cheng, Y., Meng, D., Liang, B., & Zhou, P. (2018). Early fault detection approach with deep architectures. IEEE Transactions on instrumentation and measurement, 67(7), 1679-1689.

[7] Lu, W., Cheng, Y., Xiao, C., Chang, S., Huang, S., Liang, B., & Huang, T. (2017). Unsupervised sequential outlier detection with deep architectures. IEEE transactions on image processing, 26(9), 4321-4330.

[8] Lu, W., Liang, B., Cheng, Y., Meng, D., Yang, J., & Zhang, T. (2016). Deep model based domain adaptation for fault diagnosis. IEEE Transactions on Industrial Electronics, 64(3), 2296-2305.

[9] Zhai, S., Cheng, Y., Lu, W., & Zhang, Z. (2016, June). Deep structured energy based models for anomaly detection. In International conference on machine learning (pp. 1100-1109). PMLR.