Summary
Shusen Liu is a computer scientist with a decade of experience developing high-dimensional data visualization and interpretable machine learning techniques, currently based at Lawrence Livermore National Laboratory. His work spans academic and national-lab settings—from PhD research in computer graphics and visualization at the University of Utah to postdoctoral and staff roles—focusing on multivariate volume visualization, projections, and uncertainty visualization for complex scientific datasets. He has a strong background in GPU-accelerated rendering and parallel volume rendering from early research at Wuhan and Argonne, which informs his practical approach to scalable visualization pipelines. Known for bridging theory and application, he translates advanced visualization concepts into tools for real-world scientific problems, particularly in interpreting ML models and large-scale simulation data. Operating at the intersection of biomedical engineering, computer graphics, and data science, he brings deep domain knowledge and a track record of multidisciplinary collaboration to solve challenging data-intelligence problems.
10 years of coding experience
10 years of employment as a software developer
The University of Utah
BE/BS, Biomedical Engineering / Computer Science, BE/BS, Biomedical Engineering / Computer Science at Huazhong University of Science and Technology
English, Chinese