People

TANG Fengzhen
TANG Fengzhen / Professor

Email:yuanxueqing@sia.cn
Research Areas:

Machine learning, Artificial Intelligence, Brain-inspired Computing, Brain-Computer Interfaces, Intelligent Robotics and Cyborgs, In-vivo and In-vitro Neural Signal Processing, Brain-inspired Navigation


Honor and Awards

[1] 2024 Natural Science Foundation of Liaoning province for Excellent Young Scholars, China

[2] 2024 Liaoning Revitalization Talents Program

[3] 2023 Shenyang Science and Technology Innovation Talent Program for Middle-aged and Young Scholars-Distinguished Young Scholars under 40 years old

[4] 2022 CAS Project for Young Scientists in Basic Research

[5] 2020 Liaoning’s Hundred-Thousand-Ten Thousand Talents Program

[6] 2020 Excellence Nomination Award for Outstanding Young Paper in the BCI Brain-Controlled Robot Competition – World Robot Competition

[7] 2018 CAS Hundred Talents Program

[8] 2011–2014 Li Siguang Scholarship

[9] 2007  Excellent student of Shenyang city

Publications

[1] Yinan Guo; Zirui Zhang; Fengzhen Tang* ; Feature selection with kernelized multi-class support vector machine, Pattern Recognition, 2021, 117: 107988 (IF:7.6)

[2] Fengzhen Tang*; Peter Tino ; Ordinal regression based on learning vector quantization, Neural Networks, 2017, 93: 76-88 (IF:6.3)

[3] Zirui Zhang; Yinan Guo; Fengzhen Tang* ; Dimension selection for EEG classification in the SPD Riemannian space based on PSO, Knowledge-Based Systems, 2023, 279: 110933 (IF:7.6)

[4] Fengzhen Tang*; Xiaocheng Zhang ; Robust Soft LVQ With LEML for SPD Matrices, IEEE Transactions on Emerging Topics in Computational Intelligence, 2025 9(4):2995-30092024 (IF:6.5)

[5] Fengzhen Tang; Lukas Adam*; Bailu Si ; Group Feature Selection with Multiclass Support Vector Machine,Neurocomputing, 2018, 317: 42-49 (IF:6.5)

[6] Fengzhen Tang*; Haifeng Feng; Peter Tino; Bailu Si; Daxiong Ji ; Probabilistic learning vector quantization on manifold of symmetric positive definite matrices, Neural Networks, 2021, 142: 105-118 (IF:6.3)

[7] Dongye Zhao; Fengzhen Tang*; Bailu Si; Xisheng Feng ; Learning joint space-time-frequency features for EEG decoding on small labeled data, Neural Networks, 2019, 114: 67-77 (IF:6.3)

[8] Zhihui Zhang; Hangpiao Zhao; Fengzhen Tang*; Yiping Li; Xisheng Feng ; A new dynamic shift mechanism based on cyclic group theory for continuous attractor neural networks, Nonlinear Dynamics, 2025,113:11027-11046 (IF:6.0)

[9] Bingjie Zhang, Xiaoling Gong, Jian Wang*, Fengzhen Tang*, Kai Zhang, Wei Wu. Nonstationary Fuzzy Neural Network Based on FCMnet Clustering and a Modified CG Method with Armijo-type Rule, Information Sciences, 608:313-338, 2022 (IF: 6.8)

[10] Chenchen Wu*, Ruming Zhang, Fengzhen Tang*,Pengyuan Zhao, Liang Li,Dingguo Zhang. Simulation-data-driven vibration optimization of deployable stepwise composite booms. Alexandria Engineering Journal 114 (2025) 440–452 (IF: 6.8)