中国科学院数学与系统科学研究院

系统科学研究所

中国科学院系统控制重点实验室

北京中关村东路55号

电子信箱：zhfang@amss.ac.cn

个人主页：zhoufang92.github.io

教育经历：

2014.09-2019.06 浙江大学 运筹学与控制论 博士学位

2010.09-2014.06 浙江大学 信息与计算科学 学士学位

工作经历：

2025.01-至今  中国科学院数学与系统科学研究院  副研究员

2019.11-2024.06 苏黎世联邦理工学院（ETH Zurich） 博士后

研究领域：

1. 系统与合成生物学

2. 计算生物学

3. 系统辨识与控制

学术荣誉及科研奖励：

陈景润未来之星（2025）

浙江省优秀毕业生（2019）

博士生国家奖学金（2017）

期刊论文：

[1]. Z. Fang, A. Gupta, S. Kumar, M. Khammash, Advanced methods for gene network identification and noise decomposition from single-cell data, Nature Communications, vol. 15, article number 4911, 2024.

[2]. Z. Fang, C. Gao, D. Dochain, Stochastic weak passivity for weakly stabilizing stochastic systems with nonvanishing noise, Systems & Control Letters, vol. 180, pp. 105606, 2023.

[3]. Z. Fang, A. Gupta, M. Khammash, Convergence of regularized particle filters for stochastic reaction networks, SIAM Journal on Numerical Analysis, vol. 61, pp. 399-430, 2023. 

[4]. X. Zhang , Z. Fang, C. Gao, D. Dochain, On the relation between ω-limit set and boundaries of mass-action chemical reaction networks, Automatica 149 : 110828, 2023.

[5]. S. Chen, Z. Fang, S. Lu, C. Gao, Efficacy of regularized multi-task learning based on SVM models, IEEE transactions on Cybernetics, 2022.

[6]. Z. Fang, A. Gupta, M. Khammash, Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximations, Journal of Computational Physics, vol. 467, pp. 111441, 2022.

[7]. Y. Lu, Z. Fang, C. Gao, D. Dochain, Noise-to-state Exponentially Stabilizing (state, input)-disturbed CSTRs with Non-vanishing noise, Automatica, vol. 142, pp. 110387, 2022.

[8]. Z. Fang, A. van der Schaft, C. Gao, A graphic formulation of non-isothermal chemical reaction systems and the analysis of detailed balanced networks, SIAM Journal on Applied Dynamical Systems, 19 (4), 2594-2627, 2020.

[9]. Z. Fang, C. Gao, Time-domain Boundedness of Noise-to-State Exponentially Stable Systems, ESAIM: Control, Optimisation and Calculus of Variations, vol. 26, no. 105, 2020.

[10]. Z. Fang, B. Jayawardhana, A. van der Schaft, C. Gao, Adaptation mechanisms in phosphorylation cycles by allosteric binding and gene autoregulation, IEEE Transactions on Automatic Control, vol. 65, no. 8, pp. 3457–3470, 2020.

[11]. Z. Fang, C. Gao, Lyapunov function partial differential equations for chemical reaction networks: some special cases, SIAM Journal on Applied Dynamical Systems, 18 (2), 1163-1199, 2019.

[12]. M. Ke, Z. Fang, C. Gao, Complex balancing reconstructed to the asymptotic stability of mass-action chemical reaction networks with conservation laws, SIAM Journal on Applied Mathematics, 79 (1), 55-74, 2019.

[13]. Z. Fang, C. Gao, Stabilization of input-disturbed stochastic port-Hamiltonian systems via passivity, IEEE Transactions on Automatic Control, vol. 62, no. 8, pp. 4159–4166, 2017. 

会议论文：

[1]. Z. Fang, A. Gupta, M. Khammash, Effective filtering approach for joint parameter-state estimation in SDEs via Rao-Blackwellization and modularization, IEEE 63th Conference on Decision and Control (CDC), to appear, 2024.

[2]. Z. Fang, A. Gupta, M. Khammash, Stochastic filters based on hybrid approximations of multiscale stochastic reaction networks, IEEE 59th Conference on Decision and Control (CDC), pp. 4616- 4621, 2020.

[3]. Z. Fang, E. Ydstie, C. Gao, Thermodynamic Potentials from Stationary Probabilities, the 3rd IFAC Workshop on Thermodynamic Foundations for Mathematical Systems Theory, 2019. 

[4]. Z. Fang, B. Jayawardhana, A. van der Schaft, C. Gao, Integral regulation mechanism in phosphorylation cycles, IEEE 56th Conference on Decision and Control (CDC), pp. 5322-5327, 2017.