BIMSA > Jiayi Kang
Assistant Professor Jiayi Kang

Group: Statistics, Probability and Data Science

Office: A12-108

Email: kangjiayi@bimsa.cn

Research Field: Control, Filtering, Machine Learing

Research Interest

  • Control: Numerical method for linear and nonlinear control problem, Feedback control for dynamical system, Manifold-based control problem
  • Filtering and Sampling: Particle method and Optimal transportation structure for filtering problems, Filtering on Manifold, Varitional inference, Sampling method based on Wasserstein geometry
  • Machine Learning and Deep Learning: Approximation capability and representability for neural networks, Adversarial attacks and Robustness, Control-based Neural networks, Physics-informed Neural networks, Online learning and sequence inference.
  • Numerical methods for PDE and SPDE Analysis for Galerkin method, Numerical scheme for SPDE and PDE.
  • Bioinformatics: Classification of the genome and protein, Protein Structure.

Education Experience

  • 2019 - 2024      Tsinghua University      Mathematics      Ph.D      (Supervisor: Stephen Shing-Toung Yau)
  • 2015 - 2019      Sichuan University      Mathematics and Applied Mathematics      Bachelor

Work Experience

  • 2024 -      BIMSA      Assistant Professor

Publication

  • [1] Jiayi Kang, Xiuqiong Chen, and Stephen S.-T. Yau, Explicit Convergence analyses of PDE-based filtering algorithms, accepted by SIAM Journal on Control and Optimaization (2025)
  • [2] Yuzhong Hu, Jiayi Kang, Lei Ma, and Xiaoming Zhang, A novel implementation of Yau-Yau filter for time-variant nonlinear problems, accepted by Data Analytics and Topology (2025)
  • [3] Xiuqiong Chen*, Jiayi Kang* and Stephen S.-T. Yau, Continuous Discrete Optimal Transportation Particle Filter, Asian Journal of Mathematics (2025)
  • [4] Luyao Zhang, Tong Guo, Jiayi Kang, Ning Liu, Wangrun Xia, Yao Mao, A Distributed Diffusion Bound Optimal Filter for Nonlinear Systems, accepted by 44th Chinese Control Conference (2025)
  • [5] Jiayi Kang, Xiaopei Jiao, and Stephen S.-T. Yau, Estimation of the Linear System via Optimal Transportation and Its Application for Missing Data Observations, IEEE Transactions on Automatic Control (2025)
  • [6] Y Tao, J Kang, SST Yau, The Stochastic Stability Analysis for Outlier Robustness of Kalman-type Filtering Framework Based on Correntropy-Induced Cost, IEEE Transactions on Automatic Control (2024)
  • [7] Jiayi Kang, Andrew Salmon and Stephen S.-T. Yau, Nonexistence of finite-dimensional estimation algebras on closed smooth manifolds, arXiv preprint arXiv:2410.08689 (2024)
  • [8] Xiuqiong Chen, Jiayi Kang and Stephen S.-T. Yau, Time-varying feedback particle filter, Automatica, 167, 111740 (2024)
  • [9] Jiayi Kang, Xiaopei Jiao and Stephen S-T. Yau, Finite Dimensional Estimation Algebra For Time-varying Filtering System and Optimal Transport Particle Filter: A Tangent Flow Point of View, IEEE Transactions on Aerospace and Electronic Systems(2023)
  • [10] Stephen S-T. Yau, Yangtianze Tao, and Jiayi Kang, Maximum Correntropy Ensemble Kalman Filter, accepted by proceedings of the 2023 62nd IEEE Conference on Decision and Control(2023)
  • [11] Y Tao, J Kang, SST Yau, Neural projection filter: Learning unknown dynamics driven by noisy observations, IEEE Transactions on Neural Networks and Learning Systems (2023)
  • [12] Stephen S-T. Yau, Jiayi Kang and Andrew Salmon, Log-concave posterior densities arising in continuous filtering and a maximum a posteriori algorithm, SIAM Journal on Control and Optimization, 64(2023), 4, 2407-2424
  • [13] Kang, Jiayi, Xiuqiong Chen, Yangtianze Tao, and Stephen Shing-Toung Yau, Optimal transportation particle filter for linear filtering systems with correlated noises, IEEE Transactions on Aerospace and Electronic Systems, 58(6), 5190-5203 (2022)
  • [14] Xiuqiong Chen*, Jiayi Kang*, Mina Teicher, and Stephen S.-T. Yau, A New Linear Regression Kalman Filter with Symmetric Samples, Symmetry, 13(11), 2139 (2021)
  • [15] Xiaopei Jiao*, Shaojun Pei*, Zeju Sun, Jiayi Kang and Stephen S.-T. Yau, Determination of the nucleotide or amino acid composition of genome or protein sequences by using natural vector method and convex hull principle, Fundamental Research, 1(5), 559-564 (2021)
  • [16] STY Stephen, X Chen, X Jiao, J Kang, Z Sun, Y Tao, Principles of Nonlinear Filtering Theory,

 

Update Time: 2025-08-13 17:00:09