Link Tejavibulya

Research Scientist, Circus Artist

About

Hi, I'm Link, yes like Legend of Zelda Link.
I'm a research scientist and a circus artist.Previously, I completed my BA at NYU's Gallatin School of Individualized Study. Presently, I am pursuing my PhD in Neuroscience at Yale University.

Technical Skills

Python, MySQL, R, Matlab

Research

My research seeks to understand how brain networks differ between sexes and handedness preferences across the human lifespan. In doing so, my research utilizes multivariate statistical methods and machine learning to predict these traits from functional magnetic resonance imaging (fMRI) scans.

SELECT Publications

  • Rosenblatt, M. Tejavibulya, L., Camp, C., Jiang, R., Westwater, M.L., Noble, S., Scheinost, D. (2024) Power and reproducibility in the external validation of brain-phenotype relationships. Nature Human Behavior

  • Rosenblatt, M., Tejavibulya, L., Jiang, R., Noble, S., Scheinost, D. (2024) Data leakage inflates prediction performance in connectome-based machine learning models. Nature Communications

  • Rodriguez, R.X., Noble, S., Tejavibulya, L., Scheinost, D. (2022) Leveraging edge-centric networks complements existing network-level inference for functional connectomes. NeuroImage

  • Tejavibulya, L., Rolison, M., Gao, S., Liang, Q., Peterson, H., Dadashkarimi, J., Farruggia, M.C., Hahn, C.A., Noble, S., Lichenstein, S., Pollatou, A., Dufford, A.J., Scheinost, D. (2022). Predicting the future of neuroimaging predictive models in mental health. Molecular Psychiatry

  • Horien, C., Floris, D.L., Greene, A.S., Noble, S., Rolison, M., Tejavibulya, L., O’Connor, D., McPartland, J.C., Scheinost, D., Chawarska, K., Lake, E.M.R., Constable, R.T. (2022). Functional connectome-based predictive modelling in autism spectrum disorder. Biological Psychiatry

  • Tejavibulya, L., Peterson, H., Greene, A., Gao, S., Noble, S., Rolison, M., Scheinost, D. (2022). Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity. NeuroImage

  • Horien, C., Lee, K., Westwater, M.L., Noble, S., Tejavibulya, L., Kayani, T., Constable, R.T., Scheinost, D. (2022). A protocol for working with open-source neuroimaging datasets. STAR protocols

  • Tejavibulya, L., Scheinost, D. (2020). Big data approaches to identifying sex differences in long-term memory. Cognitive Neuroscience

Circus