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Dan Zhang

Tenured Associate Professor

Department of Psychological and Cognitive Sciences, Tsinghua University

dzhang (at) tsinghua.edu.cn

职称 Tenured Associate Professor 单位 Department of Psychological and Cognitive Sciences, Tsinghua University
邮箱 dzhang (at) tsinghua.edu.cn 个人主页
研究领域 Affective Brain-Computer Interface、Physiological computing for psychological assessment
Education background

2001.09 — 2002.07 Academic Talent Program, Physics, Tsinghua University

2001.08 — 2005.07 Bachelor of Engineering, Automation, Tsinghua University

2006.09 — 2011.01 Tsinghua-Hamburg Joint Ph.D. program ‘CINACS’

2005.09 — 2011.01 Ph.D., Biomedical Engineering, Tsinghua University

Experience

2011.01 — 2013.04 Postdoc, School of Medicine, Tsinghua University

2013.05 — 2016.12 Assistant professor, Department of Psychology, Tsinghua University

2016.12 — 2024.04 Associate professor, Department of Psychology, Tsinghua University

2024.04 — Present Associate professor, Department of Psychological and Cognitive Sciences, Tsinghua University

Research Interests

My research integrates EEG, near-infrared spectroscopy, and wearable sensors to pioneer affective brain-computer interfaces and computational methods for affective neurophysiology, enabling intelligent assessment in mental health, learning science, and human-computer interaction.

I currently served as the Associate Editor-in-Chief for IEEE Transactions on Affective Computing, the Co-Editor-in-Chief for Brain Science Advances, and editorial board members for Journal of Neuroscience Methods、Cognitive Neurodynamics、Frontiers in Neuroscience, etc.

I was selected for the Stanford University World’s Top 2% Scientists List 2025.

Publications (selected)

Ding, Y.#*, Sun, B.#, Tang, Y., Zhang, D.* (2025). Unveiling the Neural Signature of Group Cohesion in Music Co-Audition. Annals of the New York Academy of Sciences, 1554: 203–215. (IF = 4.8, JCR Q1)

Shen, X.#, Gan, R.#, Wang, K., Yang, S., Zhang, Q., Liu, Q., Zhang, D.*, Song, S.* (2025). Dynamic-Attention-based EEG State Transition Modeling for Emotion Recognition. IEEE Transactions on Affective Computing, 16(4): 3552 - 3568. (IF = 9.6, JCR Q1)

Chen, J.#, Hassan, R.#, Sun, S., Mo, Y.*, Zhang, D.* (2025). Evaluating the Impact of Lightboard Videos on College Students' Performance in a Mathematical Optimization Course. IEEE Transactions on Learning Technologies, 18: 428-437. (IF = 4.9, JCR Q1)

Li, M.#, Su, Y.#, Huang, H., Cheng, J., Hu, X., Zhang, X., Wang, H., Qin, Y., Wang, X., Lindquist, K., Liu, Z.*, Zhang, D.* (2024) Language-specific representation of emotion-concept knowledge causally supports emotion inference. iScience, 111401. (IF = 4.1, JCR Q1, Cover Article)

Shui, X.#, Lin, R.#, Luo, Z.#, Lin, B., Mao, X., Li, H., Liu, R.*, Zhang, D. * (2024). Bodily Electrodermal Representations for Affective Computing. IEEE Transactions on Affective Computing, 15(3): 1018-1025. (SCI IF = 9.6, JCR Q1)

He, W., Luo, H., Zhang, D.*, Zhang, Y.* (2024). Students' Subjective Feelings during Classroom Learning. Learning and Instruction, 91, 101891. (IF = 4.7, JCR Q1)

Tang, L.#, Yuan, P.#, Zhang, D.* (2024). Emotional experience during human-computer interaction: a survey. International Journal of Human-Computer Interaction, 40(8): 1845-1855. (SCI IF = 3.4, JCR Q1)

Shen, X.#, Liu, X.#, Hu, X., Zhang, D.*, Song, S.* (2023). Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition. IEEE Transactions on Affective Computing, 14(3): 2496-2511. (SCI IF = 11.2, JCR Q1, ESI highly cited paper)

Chen, J.#, Wang, X.#, Huang, C., Hu, X., Shen, X., Zhang, D.* (2023). A large finer-grained affective computing EEG dataset. Scientific Data, 10:740, DOI: 10.1038/s41597-023-02650-w. (IF = 9.8, JCR Q1)

Chen, J.#, Xiao, Y.#, Xu, B., Zhang, D.* (2023). The Developmental Trajectory of Task-related Frontal EEG Theta/Beta Ratio in Childhood. Developmental Cognitive Neuroscience, 60, 101233. (SCI IF = 4.7, JCR Q1)

Chen, J., Qian, P., Gao, X., Li, B., Zhang, Y.*, Zhang, D.* (2023). Inter-brain coupling reflects disciplinary differences in real-world classroom learning. npj Science of Learning, DOI: 10.1038/s41539-023-00162-1. (SCI IF = 4.2, JCR Q1)

Hu, X., Wang, F., Zhang, D.* (2022). Similar brains blend emotion in similar ways: Neural representations of individual difference in emotion profiles. NeuroImage, 118819 (SCI IF = 5.7, JCR Q1, Cover Article)

Li, W., Wu, C., Hu, X., Chen, J., Fu, S., Wang, F.*, Zhang, D.* (2022). Quantitative Personality Predictions from a Brief EEG Recording. IEEE Transactions on Affective Computing, 13(3): 1514-1527. (SCI IF = 11.2, JCR Q1)

Ding, Y.#, Hu, X.#, Xia, Z., Liu, Y.-J., Zhang, D.* (2021). Inter-brain EEG Feature Extraction and Analysis for Continuous Implicit Emotion Tagging during Video Watching. IEEE Transactions on Affective Computing, 12(1): 92-102. (SCI IF = 13.990, JCR Q1)

Hu, X.#, Chen, J.#, Wang, F., Zhang, D.* (2019). Ten Challenges for EEG-based Affective Computing. Brain Science Advances, 5(1): 1–20. (Editor's Top Picks 2019-2020)

Hu, X., Yu, J., Song, M., Yu, C., Wang, F., Sun, P., Wang, D.*, Zhang, D.* (2017). EEG Correlates of Ten Positive Emotions. Frontiers in Human Neuroscience, 11(796), 2765. (SCI IF = 3.209, JCR Q1)

Zhang, D.#, Song, H.#, Xu, R., Zhou, W., Ling, Z., Hong, B.* (2013). Toward a minimally invasive brain-computer interface using a single subdural channel: a visual speller study. NeuroImage, 71, 30–41. (SCI IF = 6.252, JCR Q1)

Please see my ResearchGate page for more information.

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