Mindspeech: Continuous imagined speech decoding using high-density fNIRS and prompt tuning for advanced human-AI interaction
S. Zhang, et al.
arXiv preprint arXiv:2408.05362 (2024)
Publications
Selected publications from my research in computational neuroscience, machine learning, and brain-computer interfaces. For a complete list, see my Google Scholar profile.
MindGPT: Advancing Human-AI Interaction with Non-Invasive fNIRS-Based Imagined Speech Decoding
S. Zhang, et al.
arXiv preprint arXiv:2408.05361 (2024)
Computational and neural mechanisms of statistical pain learning
F. Mancini, S. Zhang, and B. Seymour
Nature Communications, vol. 13, no. 1 (2022)
Pain Control by Co-adaptive Learning in a Brain-Machine Interface
S. Zhang et al.
Current Biology, vol. 30, no. 20, pp. 3935-3944 (2020)
Encoding and Decoding of Pain Relief in the Human Brain
S. Zhang
PhD Thesis, University of Cambridge (2019)
The control of tonic pain by active relief learning
S. Zhang et al.
eLife, vol. 7, p. e31949 (2018)
Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection
L. R. Harries et al. (S. Zhang co-author)
NeurIPS Workshop on Machine Learning for Health (ML4H) (2018)
Dissociable Learning Processes Underlie Human Pain Conditioning
S. Zhang, H. Mano, G. Ganesh, T. Robbins, and B. Seymour
Current Biology, vol. 26, no. 1, pp. 52–58 (2016)
Technology for chronic pain
S. Zhang and B. Seymour
Current Biology, vol. 24, no. 18, pp. R930–R935 (2014)
An automatic classifier of pain scores in chronic pain patients from local field potentials recordings
S. Zhang, A. Green, and P. P. Smith
IEEE/EMBS Conference on Neural Engineering (NER) (2013)