陈天石

副教授

教育背景

博士(香港中文大学)

工学硕士、工学学士(哈尔滨工业大学)

研究领域
系统辨识,机器学习,状态推理,数据科学,传感器融合,可扩展算法,非线性控制
电子邮件
tschen@cuhk.edu.cn
个人简介

陈天石在2001年以全系第一名的成绩从哈尔滨工业大学控制科学与工程系毕业获学士学位,在2005年从哈尔滨工业大学获得控制科学与控制工程硕士学位,在2008年12月从香港中文大学获得自动化与计算机辅助工程博士学位。从2009年4月至2015年12月,他在瑞典Linkoping 大学电气工程系工作,先任博士后(从2009年4月至2011年3月),后任助理教授(从2011年4月至2015年12月)。在2015年5月,他入选了国家第十一批“千人计划”青年人才(“青年千人计划”)。在2015年12月,他回国加入香港中文大学(深圳),任职副教授。

他主要从事系统辨识(数据驱动的建模和分析)、统计信号处理、机器学习、数据科学、非线性控制及其应用的研究工作。他在欧洲和中国参与了若干科研项目。目前,他主持一项由国家自然科学基金资助的面上项目(2018-2021),一项由深圳市科创委资助的学科布局项目(2017-2019),和一项由瑞典研究委员会资助的青年科学家基金(2015-2018,当年申请成功率为9.8%)。作为项目负责人,他目前获得的竞争性项目总经费为726万人民币和360万瑞典克朗。他在2011-2015年期间,作为主要合作者还参与了欧盟研究委员会资助的高级研究项目LEARN (Limitations, Estimation, Adaptivity, Reinforcement, Networks in System Identification, 250万欧元)。

他是Automatica(2017-至今)和System & Control Letters(2017-至今)的编委,他还是 IEEE控制系统协会会议编委会(CEB)的编委(2016-至今)。

学术著作

[1] Tianshi Chen* and Martin S. Andersen. “On Semiseparable Kernels and Efficient Implementation

of Regularized System Identification and Function Estimation”, Automatica, submitted on December 16, 2019, under review.

[2] Martin Lindfors, and Tianshi Chen*. “Regularized System Identification in the Presence

of Outliers: a Variational EM Approach”, Automatica, in press, 2020.  

[3] Teng Jiang, Dabo Xu, Tianshi Chen and Andong Sheng. “Parameter Estimation of Discrete-

Time Sinusoidal Signals: A Nonlinear Control Approach”, Automatica, vol. 108, 2020.  

[4] Lennart Ljung, Tianshi Chen, and Biqiang Mu. “A Shift in Paradigm for System Identification”,

International Journal of Control, vol. 93(2), pp. 173–180, 2020.

[5] Martin S. Andersen and Tianshi Chen. “Smoothing Splines and Rank Structured Matrices:

Revisiting the Spline Kernel”, SIAM Journal on Matrix Analysis and Applications, vol. 41(2),

pp. 389–412, 2020.

[6] Yuxin Zhao, Carsten Fritsche, Gustaf Hendeby, Feng Yin, Tianshi Chen and Fredrik

Gunnarsson. “Cramér-Rao Bounds for Filtering Based on Gaussian Process State-Space

Models”, IEEE Transactions on Signal Processing, vol. 67(23), pp. 5936–5951, 2019.

[7] Tianshi Chen*. “Continuous-time DC kernel — a stable generalized first-order spline kernel,” IEEE Transactions on Automatic Control, vol. 63. no. 12, pp. 4442–4447, 2018.

[8] Biqiang Mu, and Tianshi Chen*. “On input design for regularized LTI system identification: Powerconstrained inputs,” Automatica, vol. 97, pp. 327–338, 2018.

[9] Tianshi Chen and Gianluigi Pillonetto. “On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses,” Automatica, vol. 95, pp. 529–533, 2018.

[10] Biqiang Mu, Tianshi Chen* and Lennart Ljung. “On Asymptotic Properties of Hyperparameter Estimators for Kernel-based Regularization Methods,” Automatica, vol. 94, pp. 381–395, 2018.

[11] Tianshi Chen*. “On kernel design for regularized LTI system identification,” Automatica, vol. 90, pp. 109-122, 2018.

[12] Francesca P. Carli, Tianshi Chen*, and Lennart Ljung. “Maximum entropy kernels for system identification,” IEEE Transactions on Automatic Control, Vol. 62. pp. 1471–1477, 2017. 

[13] John Lataire and Tianshi Chen*. “Transfer function and transient estimation by Gaussian process regression in the frequency domain,” Automatica, Vol. 72. pp. 217–229, 2016.

[14] Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, and Lennart Ljung. “Regularized linear system identification using atomic, nuclear and kernel-based norms: the role of the stability constraint,” Automatica, Vol. 69. pp. 137–149, 2016.

[15] Tianshi Chen*, Tohid Ardeshiri, Francesca P. Carli, Alessandro Chiuso, Lennart Ljung, and Gianluigi Pillonetto. “Maximum entropy properties of discrete-time first-order stable spline kernel,” Automatica, Vol. 66. pp. 34–38, 2016.

[16] Tianshi Chen*, Martin Andersen, Lennart Ljung, Alessandro Chiuso, and Gianluigi Pillonetto, “System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques,” IEEE Transactions on Automatic Control, Vol.59, No. 11, pp. 2933–2945, 2014. (regular).

[17] Henrik Ohlsson, Tianshi Chen*, Sina Khoshfetrat Pakazad, Lennart Ljung, and Shankar Sastry, “Scalable Anomaly Detection in Large Homogenous Populations,” Automatica, Vol.50, No. 5, pp. 1459–1465, 2014.

[18] Gianluigi Pillonetto, Francesco Dinuzzo, Tianshi Chen, Giuseppe De Nicolao, and Lennart Ljung, “Kernel Methods in System Identification, Machine Learning and Function Estimation: A Survey,” Automatica, Vol.50, No. 3, pp.657–682, 2014.

[19] Tianshi Chen*, and Lennart Ljung, “Implementation of algorithms for tuning parameters in regularized least squares problems in system identification,” Automatica, no.8 pp. 1525–1535, 2013.

[20] Tianshi Chen*, Henrik Ohlsson, and Lennart Ljung, “On the estimation of transfer functions, Regularizations and Gaussian processes - revisited,” Automatica, no. 8, pp. 1525–1535, 2012.

[21] Tianshi Chen*, Thomas B. Schön, Henrik Ohlsson, and Lennart Ljung, “Decentralized particle filter with arbitrary state decomposition,” IEEE Transactions on Signal Processing, vol. 59, no. 2, pp. 465–478, 2011.

[22] Tianshi Chen*, “Comments on “state estimation for linear systems with state equality constraints” [Automatica 43 (2007) 1363-1368],” Automatica, vol. 46, pp. 1929–1932, 2010.

[23] Tianshi Chen and Jie Huang, “A small gain approach to global stabilization of nonlinear feedforward systems with input unmodeled dynamics,” Automatica, vol. 46, pp. 1028–1034, 2010.

[24] Tianshi Chen and Jie Huang, “Global robust output regulation by state feedback for strict feedforward

systems,” IEEE Transactions on Automatic Control, vol. 54, no. 9, pp. 2157–2163, 2009.

[25] Tianshi Chen and Jie Huang, “Disturbance attenuation of feedforward systems with dynamic

uncertainty,” IEEE Transactions on Automatic Control, vol. 53, no. 7, pp. 1711–1717, 2008.