Xuanci Zheng (郑玄词)

Xuanci Zheng (郑玄词)

PhD student & Research assistant at University of Cambridge

MPhil of Psychology
BE of Computer Science

Posts by Collection

portfolio

publications

Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System

Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020

A motor imagery-based BCI using zero-shot learning reduces calibration time and achieves 91.81% of traditional method accuracy.

Recommended citation: Duan, L., Li, J., Ji, H., Pang, Z., Zheng, X., Lu, R., Li, M., & Zhuang, J. (2020). Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(11), 2411–2419. https://doi.org/10.1109/tnsre.2020.3027004 https://doi.org/10.1109/TNSRE.2020.3027004

Task Transfer Learning for EEG Classification in Motor Imagery‐Based BCI System

Published in Computational and Mathematical Methods in Medicine, 2020

The motor-imagery brain-computer interface (MI-BCI) system improves by using command combinations and transfer learning to reduce calibration time and increase accuracy.

Recommended citation: Zheng, X., Li, J., Ji, H., Duan, L., Li, M., Pang, Z., Zhuang, J., Rongrong, L., & Tianhao, G. (2020). Task Transfer Learning for EEG Classification in Motor Imagery-Based BCI System. Computational and Mathematical Methods in Medicine, 2020, 1–11. https://doi.org/10.1155/2020/6056383 https://doi.org/10.1155/2020/6056383

Psychopy based Continuous Pain Monitoring Task

Published in Zenodo, 2024

This continuous pain rating task assesses pain intensity using the open-source software PsychoPy hosted on Pavlovia.

Recommended citation: Zheng, X., Rajwal, S., Ho, S. Y. S., Ashworth, C., Seymour, B., Shenker, N., & Mancini, F. (2024). Psychopy based Continuous Pain Monitoring Task (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.13754802 https://doi.org/10.5281/zenodo.13754802

Short-term variability of chronic musculoskeletal pain

Published in Frontiers in Pain Research, 2025

Short-term variability in chronic musculoskeletal pain is clinically significant, correlating with pain severity and providing insights for personalized pain management.

Recommended citation: Zheng, X., Rajwal, S., Ashworth, C., Ho, S. Y. S., Seymour, B., Shenker, N., & Mancini, F. (2025). Short-term variability of chronic musculoskeletal pain. Frontiers in Pain Research, 6. https://doi.org/10.3389/fpain.2025.1626589 https://doi.org/10.3389/fpain.2025.1626589

Word selection, concreteness and brain lateralization

Published in Brain and Language, 2025

fMRI evidence reveals distinct neural mechanisms for semantic selection and competition in Mandarin Chinese, dynamically modulated by word concreteness.

Recommended citation: Zhao, J., Zhao, Y., Zheng, X., Wang, X., Ning, Z., Chen, Y., Ji, H., Li, J., & Zhuang, J. (2025). Word selection, concreteness and brain lateralization. Brain and Language, 272, 105659–105659. https://doi.org/10.1016/j.bandl.2025.105659 https://doi.org/10.1016/j.bandl.2025.105659

Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study

Published in bioRxiv, 2026

An EEG-based BCI targeting speech-related neural rhythms shows potential for improving phonological processing and reading skills in developmental dyslexia.

Recommended citation: Zheng, X., Araújo, J., Busson, Q., & Goswami, U. (2026). Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study. https://doi.org/10.64898/2026.01.23.700941 https://doi.org/10.64898/2026.01.23.700941

Atypical cortical encoding of the low-frequency temporal dynamics of natural speech identifies children with Developmental Language Disorder

Published in bioRxiv, 2026

EEG analyses reveal atypical low-frequency neural dynamics during natural speech processing in children with Developmental Language Disorder (DLD).

Recommended citation: Zheng, X., Araújo, J., Keshavarzi, M., Feltham, G., Richards, S., Parvez, L., & Goswami, U. (2026). Atypical cortical encoding of the low-frequency temporal dynamics of natural speech identifies children with Developmental Language Disorder. https://doi.org/10.64898/2026.03.08.710292 https://doi.org/10.64898/2026.03.08.710292

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.