Dr. Joseph Moscoso is a computational physicist and postdoctoral researcher at the University of Maryland, working within @NDB, a National Science Foundation Focused Research Hub in Theoretical Physics spanning eleven institutions. He holds a Ph.D. in Physics from the University of North Carolina at Chapel Hill and undergraduate degrees in both Physics and Mathematics & Statistics from Florida International University. His technical practice centers on large-scale numerical simulation and the statistical analysis that turns simulation output into defensible quantitative conclusions. He writes and validates production scientific software in C — including a Monte Carlo simulation code built from scratch and parallelized across CPU and GPU architectures with MPI, OpenMP, and CUDA — and runs terabyte-scale computational campaigns on Department of Energy leadership-class supercomputing systems. Uncertainty quantification is a primary deliverable of his current work: separating statistical noise from systematic error rather than reporting a single unqualified number. Separately, for three and a half years he served as a statistical verifier at the UNC Odum Institute for Research in Social Science, independently reproducing the analyses behind manuscripts accepted at peer-reviewed journals and documenting specification errors, silent data defects, and non-reproducible results. He has published nine peer-reviewed papers, including two 2024 Editors' Suggestions in the Physical Review journals. He previously held a Department of Energy Office of Science SCGSR Fellowship at Lawrence Berkeley National Laboratory and was a National Science Foundation Graduate Research Fellow.