Ariel Rokem

Image of Ariel Rokem

Ariel Rokem, Ph.D.

Research Associate Professor
Kincaid 546
Advising: Possibly accepting new graduate students in 2023-2024, please email with questions.
Interests: Neuroinformatics, Data Science, Connectomics, Machine learning, Brain imaging, Human Neuroscience

Research

The brain is a tremendously complex system and in order to understand it we are going to need large amounts of data from many different kinds of measurements. Me and my colleagues use data science methods to integrate the information provided by these measurements into a coherent picture. In particular, we develop statistical analysis techniques to decipher the role of networks of brain areas in complex behaviors and in brain disorders, and I implement these techniques in robust, efficient, and openly-available computer software.

Education

University of California, Berkeley (2010)

  • Richie-Halford, A., Cieslak, M., Ai, L. et al. An analysis-ready and quality controlled resource for pediatric brain white-matter research. Sci Data 9, 616 (2022). https://doi.org/10.1038/s41597-022-01695-7
  • Kruper J, Yeatman JD, Richie-Halford A, et al. Evaluating the reliability of human brain white matter tractometry (in press). Aperture. https://www.biorxiv.org/content/10.1101/2021.02.24.432740v2
  • Richie-Halford A, Yeatman JD, Simon N, Rokem A. Multidimensional analysis and detection of informative features in human brain white matter. PLoS Comput Biol. 2021;17(6):e1009136.