This project supports the BOSS (Best of Statistical Science) Workshop, a focused gathering of early-career and established researchers in Bayesian statistics, to be held in Spring 2026 at Texas A&M University. The primary goal of the workshop is to provide a dynamic platform for graduate students and junior researchers to engage directly with leading experts in Bayesian methodology, applications, and computation. The workshop is designed to foster cross-disciplinary collaboration, promote mentorship, and introduce participants to the breadth of modern developments in statistical science. NSF support will enable the participation of 20 early-career researchers, including postdoctoral scholars, tenure-track faculty, and advanced graduate students from across the United States. By connecting emerging scholars with senior researchers in an inclusive, discussion-oriented setting, the event aims to broaden participation and strengthen the national research capacity in modern statistics. The workshop will feature technical sessions on recent advances in Bayesian methodology, including modern computational approaches such as variational inference, shrinkage priors, and high-dimensional modeling; the use of AI in prior elicitation; and Bayesian machine learning. Applications will span the geosciences, biomedicine, and environmental sciences. Invited speakers will present cutting-edge research, while dedicated poster sessions and mentoring events will facilitate direct interactions