Line-drawing portrait of Jianqiang Ding

I am a doctoral researcher in the Nonlinear Systems and Control group at Aalto University, advised by Prof. Shankar Deka and funded by the Intelligent Work Machines (IWM) doctoral program. My research lies at the intersection of control theory and formal methods, and aims to make autonomous systems trustworthy in safety-critical settings by designing control policies that are not only effective but also come with formal guarantees of safety, stability, and robustness.

More concretely, my work focuses on formal verification and provable controller synthesis for nonlinear dynamical systems, in particular for systems operating in uncertain environments, with applications to safety-critical cyber-physical systems such as robots and autonomous vehicles.

Publications [Google Scholar]

* Equal contribution. † Corresponding author.

  1. Data-driven Reachability Verification with Probabilistic Guarantees under Koopman Spectral Uncertainty Jianqiang Ding, Shankar A. Deka [IFAC WC 2026] The 23rd IFAC World Congress [pdf] [code]
  2. PyBDR: Design and Usage of a Toolkit for Set-Boundary Based Reachability Analysis Taoran Wu*, Jianqiang Ding*†, Zhen Liang, Shankar A. Deka, Bai Xue [SCP 2026] Science of Computer Programming, vol. 253, art. 103498 [doi] [code]
    About PyBDR

    PyBDR is an open-source Python toolbox for reachability analysis of dynamical systems, built on the set-boundary method. Instead of propagating the whole initial set, it propagates only a thin set enclosing its boundary. This reduces the wrapping effect, so the reachable sets stay tight for large initial sets and long time horizons, and non-convex initial sets are handled directly.

    • Systems: linear, nonlinear and neural ODEs.
    • Set representations: intervals, zonotopes and polytopes.
    • Usage: installs with pip on Linux, macOS and Windows without system libraries; example notebooks for every algorithm, including a Colab demo; interactive 3D plots.
    pip install "pybdr @ git+https://github.com/ASAG-ISCAS/PyBDR"

    [GitHub] [latest release] [documentation] [Colab demo]

    Reachable sets of the Lotka-Volterra model: the set obtained by propagating the whole initial set (orange) is much larger than the one obtained by propagating only its boundary (blue).
    Lotka–Volterra model ẋ = 1.5x − xy, ẏ = −3y + xy initial set [2.5, 3.5]², time t ∈ [0, 2.2] whole initial set propagated boundary only (PyBDR)
  3. Provable Reach-avoid Controllers Synthesis for Deterministic Discrete-time Systems Based on Convex Computations of Controlled Reach-avoid Sets Jianqiang Ding, Taoran Wu, Yuping Qian, Lijun Zhang, Shankar A. Deka, Bai Xue [Book Chapter] Design and Verification of Cyber-Physical Systems (Fränzle Festschrift), LNCS vol. 16060, pp. 223–243, 2026 [doi] [pdf]
  4. Reach-Avoid Model Predictive Control with Guaranteed Recursive Feasibility via Input Constrained Backstepping Jianqiang Ding, Nishant Jayesh Bhave, Shankar A. Deka Preprint, arXiv:2604.03407, 2026.   [pdf] [code]
  5. Backstepping Reach-avoid Controller Synthesis for Multi-input Multi-output Systems with Mixed Relative Degrees Jianqiang Ding, Dingran Yuan, Shankar A. Deka [CDC 2025] The 64th IEEE Conference on Decision and Control [pdf] [doi] [code]
  6. Time-to-reach Bounds for Verification of Dynamical Systems using the Koopman Spectrum Jianqiang Ding, Shankar A. Deka Preprint, arXiv:2411.05554, 2024.   [pdf]
  7. PyBDR: Set-boundary based Reachability Analysis Toolkit in Python Jianqiang Ding*†, Taoran Wu*, Zhen Liang, Bai Xue [FM 2024] 26th International Symposium on Formal Methods [pdf] [code]
  8. Inner-approximate Reachability Computation via Zonotopic Boundary Analysis Dejin Ren, Zhen Liang, Chenyu Wu, Jianqiang Ding, Taoran Wu, Bai Xue [CAV 2024] 36th International Conference on Computer Aided Verification [pdf]
  9. Discernible Image Mosaic with Edge-aware Adaptive Tiles Pengfei Xu, Jianqiang Ding, Hao Zhang, Hui Huang [CVM 2019] Computational Visual Media, vol. 5 [doi]