HU Bin

Academic Title: Tenured Professor

Research Interests: Brain-inspired Computing, Spiking Neural Network Modeling and Analysis, Functional Brain Networks, Mental Health (Depression, Autism) Management Application

Biography

Bin Hu is a Professor and Doctoral Supervisor at the School of Future Technology, South China University of Technology, and also a Researcher at the Guangdong Provincial Artificial Intelligence and Digital Economy Laboratory (Guangzhou). His research focuses on brain-inspired spiking neural network modeling and its applications in depression. In the past five years, she has published over 20 first/corresponding author papers in IEEE Transactions, obtained 9 patents, and authored one Springer monograph. She has presided over projects including the National Natural Science Foundation Excellent Young Scientists Fund and General Program. She has received honors such as the Intel China Rising Star Fellow Award and the South China University of Technology Elite Scholar Award.

Education

2011 - 2015: Ph.D. in Control Science and Engineering, Huazhong University of Science and Technology

Work Experience

2023 - Present: Professor/Doctoral Supervisor, School of Future Technology, South China University of Technology

2023 - Present: Researcher, Scientific Research Department, Guangdong Provincial Artificial Intelligence and Digital Economy Laboratory (Guangzhou)

Research Projects

1.National Natural Science Foundation of China, Excellent Young Scientists Fund: "Modeling, Analysis and Control of Hybrid Spiking Neural Networks", Jan 2024 - Dec 2026, PI

2.Pazhou Laboratory Project: "Brain-inspired Neural Network Methods for Depression Diagnosis and Intervention", Jan 2023 - Dec 2027, PI

3.National Natural Science Foundation of China, Key Program: "Autonomous Collaboration and Game Theory of Hybrid Intelligent Unmanned Systems", 2023 - 2027, Second-in-charge

Selected Publications

Publications:

[1] B. Hu, H. Zeng, Z. Guan, Multimodal time-series recognition with spatiotemporal dynamic graph spike neural networks. IEEE TII 2025, pp. 1-12.

[2] B. Hu, Z. Guan, et al. Energy-efficient hybrid impulsive model for joint classification and segmentation on CT images. IEEE TAI 2025, 6(5): 1401-1413.

[3]B. Hu, Z. Guan, et al. Neuroscience and network dynamics towards brain-inspired intelligence. IEEE TCYB 2022, 52(10): 10214-10227.

[4] B. Hu, X. Yu, Z. Guan, et al. Hybrid neural adaptive control for practical tracking of Markovian switching networks. IEEE TNNLS 2021, 32(5): 2157-2168.

[5] B. Hu, Z. Guan, et al. Multistability of delayed hybrid impulsive neural networks with application to associative memories. IEEE TNNLS 2019, 30(5): 1537-1551.

Patents:

[1] Invention Patent, "An Audio Feature Extraction Method Based on Brain Neural Model," South China University of Technology, CN202510912582.9

[2] Invention Patent, "Multimodal Depression Risk Assessment Method, Device, System, Medium and Training Method," South China University of Technology, CN202410604088.1

[3] Invention Patent, "Multi-task Hybrid Neural Network-driven CT Image Processing Method and Brain-inspired Diagnostic System," Guangdong Provincial Artificial Intelligence and Digital Economy Laboratory (Guangzhou) & South China University of Technology, CN202311626792.9