Dr. Jingwei Li

Contact

+49 2461/61-85858

+49 2461/61-1880

E-Mail

Address

Forschungszentrum Jülich GmbH
Wilhelm-Johnen-Straße
52428 Jülich

Institute of Neurosciences and Medicine (INM)

Brain and Behaviour (INM-7)

Building 14.6y / Room 2035

About me

I obtained my B.Eng. in Automation in 2015 at Shanghai Jiao Tong University, China, and my Ph.D. in Electrical and Computer Engineering in 2019 at National University of Singapore, Singapore. Since 2020, I joined the INM-7 at FZJ as a postdoc. My research focuses on using machine learning to predict human behavioral phenotype from neuroimaging data, in particular the unfairness problem of machine learning models.

Publications

Wu, J., Li, J., Eickhoff, S.B., Hoffstaedtera, F., Hanke, M., Yeo, B.T.T., & Genon, S. (2022). Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns. NeuroImage. 262, 119569.

Deng, S., Li, J., Yeo, B.T.T., & Gu, S. (2022). Control theory illustrates the energy efficiency in the dynamic reconfiguration of functional connectivity, Communications Biology, 5(1), 1-12.

Li, J., Bzdok, D., Chen, J., Tam, A., Ooi, L.Q.R., Holmes, A.J., Ge, T., Patil, K.R., Jabbi, M., Eickhoff, S.B., & Yeo, B.T.T., (2022). Cross-ethnicity/race generalization failure of behavioral prediction from resting-state functional connectivity. Science Advances, 8(11), eabj1812.

Anderson, K.M., Collins, M.A., Kong, R., Fang, K., Li, J., He, T., Chekroud, A.M., Yeo, B.T.T., & Holmes, A.J. (2020). Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder. Proceedings of the National Academy of Sciences, 117 (40), 25138-25149.

Bolton, T.A., Kebets, V., Glerean, E., Zöller, D., Li, J., Yeo, B.T., Caballero-Gaudes, C., & Van De Ville, D. (2020). Agito ergo sum: Correlates of spatio-temporal motion characteristics during fMRI. NeuroImage, 209, 116433.

Orban, C., Kong, R., Li, J., Chee, M.W., & Yeo, B.T.T. (2020). Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity. PLoS Biology, 18 (2), e3000602.

Kebets, V., Holmes, A.J., Orban, C., Tang, S., Li, J., Sun, N., Kong, R., Poldrack, R.A., & Yeo, B.T.T. (2019). Somatosensory-motor dysconnectivity spans multiple transdiagnostic dimensions of psychopathology. Biological Psychiatry, 86 (10), 779-791.

Li, J.*, Bolt, T.*, Bzdok, D., Nomi, J.S., Yeo, B.T.T., Spreng, R.N., & Uddin, L.Q. (2019). Topography and behavioral relevance of the global signal in the human brain. Scientific Reports, 9(1), 1-10.

Li, J.*, Kong, R.*, Liégeois, R., Orban, C., Tan, Y., Sun, N., Holmes, A.J., Sabuncu, M.R., Ge, T., & Yeo, B.T.T. (2019). Global signal regression strengthens association between resting-state functional connectivity and behavior. NeuroImage, 196, 126-141.

Kong, R., Li, J., Orban, C., Sabuncu, M.R., Liu, H., Schaefer, A., Sun, N., Zuo, X.N., Holmes, A.J., Eickhoff, S.B., & Yeo, B.T.T. (2019). Spatial topography of individual-specific cortical networks predicts human cognition, personality, and emotion. Cerebral Cortex, 29(6), 2533-2551.

Liégeois, R., Li, J., Kong, R., Orban, C., Van De Ville, D., Ge, T., Sabuncu, M.R., & Yeo, B.T.T. (2019). Resting brain dynamics at different timescales capture distinct aspects of human behavior. Nature Communications, 10(1), 1-9.

Kashyap, R., Kong, R., Bhattacharjee, S., Li, J., Zhou, J., & Yeo, B.T.T. (2019). Individual-specific fMRI-Subspaces improve functional connectivity prediction of behavior. NeuroImage, 189, 804-812.

Yang, B., Li, J., Han, Q., He, T., Chen, C., & Guan, X. (2016). Distributed control for charging multiple electric vehicles with overload limitation. IEEE Transactions on Parallel and Distributed Systems, 27(12), 3441-3454.

Li, J., Yang, B., Xu, Y., Chen, C., Guan, X., & Zhang, W. (2014, July). Scheduling of electric vehicle charging request and power allocation at charging stations with renewable energy. In Proceedings of the 33rd Chinese Control Conference (pp. 7066-7071). IEEE.

Last Modified: 04.09.2023