Zheng Ma was born in 1984. He received the B.S. degree in electronic engineering from Dalian University of Technology in 2006 and received the Ph.D. degree in biomedical engineering from Dalian University of Technology in 2016. From 2016 to 2019, he was a postdoctoral fellow in the Laboratory for Human Machine Control, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. From 2019 to 2025, he served as an assistant investigator in the Institute of Brain Cognition and Brain Diseases (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Since 2026, he served as an associate investigator in the Shenzhen Neher Neural Plasticity Laboratory. 

Visual brain-computer interfaces, EEG/Neural signal processing, Machine learning.

1.    Xinnian Wang, Zheng Ma, Yifan Luo, Yechao Han, Chuanzan Zhan, Yulin Ouyang, and Yang Zhan*. Distinct neural dynamics in the ventral hippocampus and medialprefrontal cortex during social information processing, PNAS, 2025, 122(15): e2516279122
2.    Zihao Chen#, Yechao Han#, Zheng Ma, Xinnian Wang, Surui Xu, Yong Tang, Alexei L. Vyssotski, Bailu Si, Yang Zhan*. A prefrontal-thalamic circuit encodes social information for social recognition, Nature Communications, 2024, 15: 1-15
3.    Zheng Ma#, Zexin Xie#, Tianshuang Qiu, Jun Cheng*. Driving event-related potential-based speller by localized posterior activities: An offline study. Mathematical Biosciences and Engineering. 2020, 17(1): 789-801. DOI: 10.3934/mbe.2020041.（SCI）
4.    Zheng Ma, Jun Cheng*, Dapeng Tao. Online Learning Using Projections onto Shrinkage Closed Balls for Adaptive Brain-Computer Interface. Pattern Recognition. 2020, 97: 107017. DOI: 10.1016/j.patcog.2019.107017.（SCI）
5.    Zheng Ma* and Tianshuang Qiu. Performance improvement of ERP‑based brain–computer interface via varied geometric patterns. Medical & Biological Engineering & Computing. 2017, 55(12): 2245-2256. DOI: 10.1007/s11517-017-1671-5 (SCI)

He has led a project, "Study on Visual Pattern Stimulus-based BCI Intrinsic Component Enhancement and Recognition" (Grant No.: 61906183), funded by the National Natural Science Foundation of China, from 2020 to 2022.