Jiahong Li

Jiahong Li

Associate Professor@BUU

Jiahong Li

Hello! I am an Associate Professor at the School of Robotics, Beijing Union University, Beijing, China (since Mar. 2025). My research focuses on state-of-the-art multi-agent cooperative estimation, optimization, and control methods applied to autonomous agents and sensor networks.

Previously, I was a Postdoctoral Associate in the Artificial Intelligence Lab at Vrije Universiteit Brussel (2021-2022), working with Prof. Ann Nowé to explore and develop safe and explainable (Multi-agent) reinforcement learning (RL). Prior to that, I served as a Lecturer at Beijing Union University from 2017 to 2025.

I received my Ph.D. degree in Control Science and Engineering under the supervision of Prof. Jie Chen in 2017, and my B.Eng. degree in Electrical Engineering and Automation in 2011, both from the Beijing Institute of Technology, Beijing, China. During my Ph.D., I was a visiting scholar at Loughborough University, UK (2014-2015), working with Prof. Shuang-Hua Yang.

My research interests mainly focus on:

  • Multi-agent cooperative robust adaptive estimation, inference, and optimization under unknown system or measurement statistics.
  • Risk-sensitive multi-agent robust control and RL under uncertainties.
  • Cooperative indoor localization and target tracking under uncertainties (e.g., IMU/UWB sensor fusion, connected vehicles).
  • Intelligent optimization and decision-making for complex systems.

News

  • 01/2025: Two papers accepted at 2025 China Automation Congress (CAC) and CVCI2025.
  • 04/2021: Paper “Distributed Noise Covariance Matrices Estimation in Sensor Networks” was nominated for the 2020 Roberto Tempo IEEE Best CDC Paper Award.
  • 03/2019: My doctoral thesis received the Excellent Doctoral Dissertation Award from the Chinese Decision and Control Society.
  • ALS-IRLS: Outlier-Robust Autocovariance Estimation
    An efficient iteratively reweighted least squares (IRLS) framework for noise covariance estimation in Kalman filters, significantly improving robustness against measurement outliers.
    [Project Page] [Code] [arXiv]

Selected Publications

Full publications: [Google Scholar], [DBLP], [ResearchGate].

  • Jiahong Li, Xinkai Xu, Zhuoying Jiang, Beiyan Jiang. Adaptive Kalman Filter for Real-Time Visual Object Tracking Based on Autocovariance Least Square Estimation. Applied Sciences. 2024, 14(3):1045.
  • Jiahong Li, Fang Deng, Jie Chen. A Fast Distributed Variational Bayesian Filtering for Multi-sensor LTV system with Non-Gaussian Noise. IEEE Transactions on Cybernetics. 2018, 49(7): 2431-2443.
  • Jie Chen, Jiahong Li, Shuanghua Yang, Fang Deng. Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Cooperative Sensor Networks. IEEE Transactions on Cybernetics. 2016, 47(11): 3892-3905.
  • Jiahong Li, Xianghu Yue, Jie Chen, Fang Deng. A Novel Robust Trilateration Method applied to Ultra-Wide Bandwidth Location Systems. Sensors. 2017, 17(4): 795.
  • Jiahong Li, Nan Ma, Fang Deng. Distributed Noise Covariance Matrices Estimation in Sensor Networks. The 59th IEEE Conference on Decision and Control (CDC 2020). 2020: 1158-1163.