Boris Landa, PhD
Assistant Professor of Electrical and Computer Engineering
What do you do with Data Science?
My research focuses on developing computational and theoretical tools for analyzing complex data, especially in high-dimensional, noisy, and heterogeneous settings that arise in modern scientific and engineering applications. I am particularly interested in uncovering low-dimensional structure—such as manifolds, subspaces, and networks—hidden in large-scale datasets, and in understanding when methods remain reliable under challenging conditions. I use ideas from geometry and topology, high-dimensional probability, random matrix theory, and harmonic analysis to develop robust and scalable techniques with theoretical guarantees. I also collaborate closely with practitioners in biomedical areas such as genomics and transcriptomics to develop software implementations and extract scientific insights from their data.