State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

Faculty

Current Faculty

Jing Sui Ph.D.• Brain Imaging/Multimodal Fusion/Biomarker Identification.

• Psychosis. Adolescent Development. Autism. ADHD

• Machine Learning. Deep Learning. ICA.
jsui#bnu.edu.cn https://scholar.google.com/citations?user=xuJq9McAAAAJ&hl=en

Educational Experience

PhD　2007.3　Optical Engineering (in major of Image/Signal Processing),
Beijing Institute of Technology (BIT), Beijing, China.

BS　2002.6　Optical Technology and Photoelectric Instrumental, BIT

Minor　2001.12　Computer Science, Beijing Institute of Technology

Professional Experience

2021-present　Professor, Beijing Normal University, Beijing, China

2016-2021　Professor, University of Chinese Academy of Sciences, Beijing, China

2013-2021　Professor, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2012-2013　Assistant Professor, The Mind Research Network, Albuquerque, NM, USA

2010-2012　Research Scientist, The Mind Research Network , USA

2007-2009　Postdoctoral Fellow, The Mind Research Network, USA.

Research Description

Dr. Sui has been focusing on the interdisciplinary research frontier of brain science and artificial intelligence, aiming to solve the key challenges in pattern recognition of brain imaging data analysis. Our research interests include multivariate, multimodal MRI fusion method development, biomarker/neuromarker identification, adolescent psychotic risk prediction, individualized MDD/ADHD treatment optimization, multiple cognitive ability evaluation etc. Dr. Sui has published 120+ peer-reviewed journal articles and 100+ conference papers/abstracts, including the esteemed journals such as Nature Communications, Brain, Biological Psychiatry, and Schizophrenia Bulletin etc. She also serves as Associate editor/Editor board member for multiple journals, and grant reviewers of dozens of domestic and international funding agencies. Sui Lab warmly welcome self-motivated students, visiting scholars and postdocs who are interested in the multidisciplinary brain research.

Publications

See full paper list on：https://scholar.google.com/citations?user=xuJq9McAAAAJ&hl=en

1. Jiang RT, Noble S, Rosenblatt M, Dai W, Ye J, Liu S, Qi SL, Calhoun VD, Sui J* and Scheinost D 2024. The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression. Nature Communications 2024. 15(1).

2. Sui J*^#, Qi S^#, van Erp TGM, Bustillo J, Jiang R, Lin D, Turner JA, Damaraju E, Mayer AR, Cui Y, Fu Z, Du Y, Chen J, Potkin SG, Preda A, Mathalon DH,…McMahon A, Jiang T, and Calhoun VD*. Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion. Nature Communications. 2018. 9(1): 3028.

3. Qi S*, Sui J*, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, Turner JA, Fu Z, Shao W, Jiang R, Yang X, Liu J, Du Y, Chen J*, Zhang D*, and Calhoun VD. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nature Communications. 2022. 13(1): 4929

4. Feng G, Chen J, Sui J, Calhoun VD. Cellular and molecular associations with intrinsic brain organization. Nature Communications. 2025.16(1):11641.

5. Jiang R, Woo C-W, Qi S, Wu J, and Sui J*. Interpreting brain biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging. IEEE Signal Processing Magazine. 2022. 39(4): 107-118.

6. Yan W, Qu G, Hu W, Abrol A, Cai B, Chen Q, Plis SM, Wang Y-P, Sui J*, and Calhoun VD*. Deep learning in neuroimaging: Promises and challenges. IEEE Signal Processing Magazine 2022. 39(2): 87-98.

7. Zhao M, Yan W, Luo N, Zhi D, Fu Z, Du Y, Yu S, Jiang T, Calhoun V, Sui J*. An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. Medical Image Analysis. 2022. 78: 102413.

8. Feng A, Zhi D, Feng Y, Jiang R, Fu Z, Xu M, Zhao M, Yu S, Stevens M, Sun L*, Calhoun V*, Sui J*.(2024) Functional imaging derived ADHD biotypes based on deep clustering: a study on personalized medication therapy guidance. eClinicalMedicine. 2024;77: 102876.

9. Fu Z, Sui J, Iraji A, Liu J, and Calhoun VD. Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (n > 10,000) children population. Mol Psychiatry. 2025. 30(2): 402-413.

10. Xu M, Li X, Teng T, Huang Y, Liu M, Long Y, Lv F, Zhi D, Li X, Feng A, Yu S, Calhoun V, Zhou X, and Sui J*. Reconfiguration of structural and functional connectivity coupling in patient subgroups with adolescent depression. JAMA Network Open. 2024. 7(3): e241933.

11. Qi S, Calhoun VD, Zhang D, Miller J, Deng ZD, Narr KL, Sheline Y, McClintock SM, Jiang R, Yang X, Upston J, Jones T, Sui J*, and Abbott CC*. Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder. BMC Medicine. 2022. 20(1): 477.

12. Zhi DM, Jiang RT, Pearlson G, Fu ZN, Qi SL, Yan WZ, Feng AC, Xu M, Calhoun V*, Sui J*.2024. Triple Interactions between the environment, brain, and behavior in Children: An ABCD Study. Biological Psychiatry 95(9): 828-838.

13. Qi, S., G. Schumann, J. Bustillo, J. A. Turner, R. Jiang, D. Zhi, Z. Fu, A. R. Mayer, V. M. Vergara, R. F. Silva, A. Iraji, J. Chen, E. Damaraju, X. Ma, X. Yang, M. Stevens, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, S. G. Potkin, A. Preda, C. Zhuo, Y. Xu, C. Chu, T. Banaschewski, G. J. Barker, A. L. W. Bokde, E. B. Quinlan, S. Desrivieres, H. Flor, A. Grigis, H. Garavan, P. Gowland, A. Heinz, J. L. Martinot, M. L. Paillere Martinot, E. Artiges, F. Nees, D. P. Orfanos, T. Paus, L. Poustka, S. Hohmann, J. H. Frohner, M. N. Smolka, H. Walter, R. Whelan, V. D. Calhoun*, Sui J*. and IMAGEN. Consortium (2021). Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker. Biological Psychiatry 2021. 90(8): 529-539.

14. Sui J*^#, Jiang R^#, Bustillo J, and Calhoun V. Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: Methods and promises. Biological Psychiatry. 2020. 88(11): 818-828.

15. Sui J*, Pearlson GD, Du Y, Yu Q, Jones TR, Chen J, Jiang T, Bustillo J, and Calhoun VD. In search of multimodal neuroimaging biomarkers of cognitive deficits in schizophrenia. Biological Psychiatry. 2015. 78(11): 794-804.

16. Qi S, Calhoun VD, van Erp TGM, Bustillo J,...Belger A, McEwen S, Potkin SG, Preda A, Jiang T, and Sui J*. Multimodal fusion with reference: Searching for joint neuromarkers of working memory deficits in schizophrenia. IEEE Trans Med Imaging. 2018. 37(1): 93-105.

17. Yao D, Sui J*, Wang M, Yang E, Jiaerken Y, Luo N, Yap PT, Liu M*, and Shen D*. A mutual multi-scale triplet graph convolutional network for classification of brain disorders using functional or structural connectivity. IEEE Trans Med Imaging. 2021. 40(4): 1279-1289.

18. Jiang R, Geha P, Rosenblatt M, Wang Y, Fu Z, Foster M, Dai W, Calhoun VD, Sui J*, Spann MN, and Scheinost D. The inflammatory and genetic mechanisms underlying the cumulative effect of co-occurring pain conditions on depression. Science Advances. 2025. 11(14): eadt1083.

19. Jiang R*, Scheinost D, Zuo N, Wu J, Qi S, Liang Q, Zhi D, Luo N, Xu Y, Sui J* Calhoun VD. A neuroimaging signature of cognitive aging from whole-brain functional connectivity. Advanced Science. 2022.15: e2201621.

20. Sui J, Li X, Bell RP, Towe SL, Gadde S, Chen NK, and Meade CS*. Structural and functional brain abnormalities in human immunodeficiency virus disease revealed by multimodal magnetic resonance imaging fusion: Association with cognitive function. Clinical Infectious Disease. 2021. 73(7): e2287-e2293.

21. Qi S, Yang X, Zhao L, Liu S, Jiang T, Sui J*, and Ma X*. Microrna132 associated multimodal neuro- imaging patterns in unmedicated major depressive disorder. Brain. 2018. 141(3): 916-926.

22. Luo N, Sui J*, Chen J, Zhang F, Tian L, Lin D, Song M, Calhoun VD, Cui Y, Vergara VM, Zheng F, Liu J, Yang Z, Zuo N, Fan L, Xu K, Liu S, Li J, Xu Y, Liu S, Lv L, Chen J, Chen Y, Guo H, Li P, Lu L, Wan P, Wang H, Wang H, Yan H, Yan J, Yang Y, Zhang H, Zhang D, and Jiang T. A schizophrenia-related genetic-brain-cognition pathway revealed in a large chinese population. EBioMedicine. 2018. 37: 471-482.

23. Yan W, Calhoun V, Song M, … Zhang D, Jiang T, and Sui J*. Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site fMRI data. EBioMedicine. 2019. 47: 543-552.

24. Liu SF, Wang HY, .., Jiang TZ and Sui J* .2019. Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population. Schizophrenia Bulletin 45(2): 436-449.

25. Qi S, Morris R, Turner JA, Fu Z, Jiang R, Deramus TP, Zhi D, Calhoun VD, Sui J*. Common and unique multimodal covarying patterns in autism spectrum disorder subtypes. Molecular Autism. 2020. 11(1): 90.