I received my M.S. degree in Computational Biology and Quantitative Genetics at Harvard in 2019. My interest focuses on the functional organization of the mind and brain, and computational algorithms that can extract the network from noisy information. When I was in college, I used conditional mutual information-path consistency algorithm combined with network deconvolution to infer direct gene regulatory networks, based on RNA sequencing data. In my master, I studied function connectivity in the human brain among regions with 3-categories visual preferences, based on resting-state fMRI data. Now, I’m exploring how the network analysis methods can contribute to our understanding of functional organization of the brain.