Before arriving at the University of Utah, Connor Scully-Allison studied at two prior institutions. First, at the University of Nevada, Reno he received a Bachelors of Arts in Philosophy. After working for a few years he pivoted to Computer Science and graduated with a Masters of Computer Science and Engineering in 2019. Following from that he moved to the University of Arizona to study data visualization with Dr. Kate Isaacs.
At the university of Arizona, he studied scalable design of gantt charts, visualization optimization and tree visualizations for performance analysis. He also served as the president of the Computer Science Grad Student Council for 2 years and won an award for service to the Department of Computer Science and College of Science.
Presently, Connor is continuing his work with Dr. Isaacs as a Graduate Research Assistant at SCI. In close collaboration with colleagues at Lawerence Livermore National Lab he is researching how data visualizations can be integrated into exploratory coding workflows. He is specifically examining how this approach of more integrated visualization can aid performance analysts optimizing simulation code for supercomputer systems.
Performance Analysis Visualizations
Scientific Data Management
Programmatic Performance Analysis