Associate Professor | Peking University | China
Assoc. Prof. Dr. Kai Yuan is an internationally recognized researcher at Peking University whose work significantly advances neuroscience, psychiatric epidemiology, molecular signaling, and translational mental health research. With an exceptional 8,438 citations, 244 Scopus-indexed documents, and a strong h-index of 47, he stands among the most impactful scholars in neurobiology and psychiatric disorder research. His research interests span addiction memory consolidation, brain network dynamics, fMRI-based cognitive and emotional processing, depression and anxiety burden forecasting, cancer cell signaling, neuroimmune mechanisms, and human behavior under stress. Dr. Yuan’s research skills are wide-ranging and include advanced neuroimaging analytics, molecular and cellular assays, biomarker profiling, psychophysiological modeling, machine-learning–based disease prediction, and multidisciplinary clinical collaboration, often demonstrated through publications in high-impact journals such as Nature Communications, Translational Psychiatry, BMC Medicine, Communications Biology, and Journal of Affective Disorders. Although Scopus Preview does not list formal award entries, Dr. Yuan’s prolific productivity, more than 980 global co-authors, and consistent contributions to open-access, high-visibility research reflect his standing as a leading scientist whose work is frequently recognized by the international research community. His studies on psychiatric disorder mechanisms, memory retrieval-extinction processes, cancer proliferation pathways, and long-term cognitive outcomes of viral infections directly support advancements in clinical treatment strategies, public health decision-making, and precision medicine. In conclusion, Dr. Kai Yuan’s research continues to shape global understanding of the human brain and mental health, providing foundational insights that drive innovation across neuroscience, psychiatry, and biomedical science, while strengthening the scientific infrastructure for future therapeutic breakthroughs.
Profiles: Scopus | ORCID | Google Scholar
Featured Publications
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Yu, Y. F., Jia, T. Y., Lin, X., Bao, Y. P., Chang, S. H., Sun, J., Gao, T., Shi, J., Ai, S. Z., & Yuan, K.* (2025). Unveiling causal relationship between white matter tracts and psychiatric disorders. Communications Biology, 8(1), 1221.
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Xu, A., Yuan, K.#, Xue, S., Lu, W., Wu, X., Liu, W., Xue, Q., Liu, L., Hu, J., Guo, L., Zhang, Y., Hu, X., Chun Wong, G. T., Lu, L., & Huang, C. (2025). Laminin–dystroglycan mediated ferroptosis in hemorrhagic shock and reperfusion-induced cognitive impairment through AMPK/Nrf2. Free Radical Biology and Medicine, 230, 1–16.
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Chen, X., Li, Z., Han, Y., Yang, L., Han, Q., Cao, L., Guan, X., Liu, S., Meng, S., Liu, X., Lu, L., Zhang, Z., & Yuan, K.* (2025). A coordinated and enhanced brain network supports the persistence of long-term cocaine memory. Translational Psychiatry, 15(1), 444.
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Liu, X.#, Yuan, K.#, Lu, T., Lin, X., Zheng, W., Xue, Y., Shi, J., Lu, L., & Han, Y. (2023). Preventing incubation of drug craving to treat drug relapse: From bench to bedside. Molecular Psychiatry, 28(4), 1415–1429.
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Yue, J. L.#, Yuan, K.#, Bao, Y. P., Meng, S. Q., Shi, L., Fang, Q., Guo, X. J., Cao, L., Sun, Y. K., Lu, T. S., Zeng, N., Yan, W., Han, Y., Sun, J., Shi, J., Kosten, T. R., Xue, Y. X., Wu, P., & Lu, L.* (2022). [Title missing—please provide the exact article title to complete APA formatting]. EBioMedicine, 85, 104283.
Assoc. Prof. Dr. Kai Yuan’s pioneering research at the intersection of neuroscience, psychiatry, and translational medicine is advancing global understanding of brain circuitry, mental health disorders, and addiction biology. His work contributes to science by uncovering causal neural mechanisms that shape cognition, behavior, and psychiatric vulnerability, supports society through improved diagnostics and therapeutic strategies for depression, addiction, and neurological injury, and drives global innovation by integrating advanced neuroimaging, molecular signaling, and computational analytics to inform next-generation precision mental healthcare.