Connor Scully-Allison is a postdoctoral scholar and visualization researcher with 11 years of hands-on experience building data-intensive tools and conducting human-centered computing studies. He writes production-quality code across C, C++, Python, JavaScript, and full-stack web technologies, and has applied that expertise to HPC profiling, notebook-embedded visualizations, and supercomputer systems data. Connor’s work bridges qualitative HCI methods and software engineering—evaluating how educators and administrators interpret research and designing communication platforms informed by those decisions. His internships at national labs and research roles at multiple universities have produced optimized libraries and deployable tools (e.g., a Guidepost visualization for HPC jobs), reflecting a blend of practical performance optimization and user-focused design. Trained to a PhD level with top grades and a background in philosophy, he brings rigorous analytical thinking to complex visualization problems and team-facing communication.
11 years of coding experience
9 years of employment as a software developer
The University of Arizona
The University of Utah
Master’s Degree, Computer Science, 3.98, Master’s Degree, Computer Science, 3.98 at University of Nevada, Reno
Bachelor’s Degree, Philosophy, 3.8, Bachelor’s Degree, Philosophy, 3.8 at University of Nevada-Reno
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Connor Scully-allison - Postdoctoral Scholar at University of Chicago