I am a graduate student in computational neuroscience at GSN-LMU and I am currently in the preparatory year prior to my PhD phase.

Before my fast-track PhD program at GSN-LMU, I obtained my bachelor's degree in psychology at the University of Amsterdam after my transferring from Beijing Normal University. During my undergraduate period, I completed a research project where I was trying to decode visual experience from EEG data using MVPA and comparing the performance of two preprocessing methods (high-pass filtering and detrending). In another internship, I investigated the Bayesian model comparison method and showed the intransitivity in the Leave-One-Out Cross-Validation (LOO-CV) method.

For more information, please visit my personal website: https://jiashun97.github.io

I joined the lab in September 2020 as a research intern to work on a collaborative project with Prof. Gemma Roig.

My research interest lies in how machine learning can help understand visual processing. Specifically, I am comparing the performance of different machine learning models in predicting brain data (e.g. EEG, MEG, and fMRI).