Dr. Ronald Daryll E. Gatchalian obtained his PhD in Nuclear Engineering from Texas A&M University in 2023. In his dissertation research, he developed a data-driven Deep Learning methodology to predict the physics parameters of a subcritical reactor using observable quantities monitored in reactor operation as predictors. This addresses the limitations of standard experimental techniques in reactor physics evaluation thereby contributing to the safe and efficient utilization of PRR1-SATER. Some of his technical skills are radiation transport simulation, computational fluid dynamics, machine learning, radiation detection and measurement, radiological hazards assessment, and nuclear reactor design. He is part of the Nuclear Reactor Operations Section of PNRI and a member of the American Nuclear Society.