Samie’s research focuses on developing mathematically grounded frameworks to advance novel approaches in topological data analysis for uncovering latent structure in complex biological datasets—particularly high-dimensional proteomic data—with the goal of characterizing heterogeneity and inferring mechanisms underlying differential therapeutic response.

Samie holds a Master’s degree in Computer Science, with a focus on control theory in complex networks—specifically using human brain networks as a case study—conducted in collaboration with the National Brain Mapping Laboratory in Iran and in association with Prof. Alex Fornito at Monash University. He also holds a Bachelor’s degree in Information Technology.