Daniel Adams

Bio

Daniel is an Associate R&D Scientist within the at Oak Ridge National Laboratory. His research interests lie at the intersection of spatial data mining, inherent randomness, and structured decision-making in geospatial sciences. He frequently applies probabilistic and machine learning techniques, including Bayesian reasoning and deep learning, to domains such as human dynamics, built environment characterization, climate security, and landscape ecology. Daniel is passionate about turning spatial uncertainty into actionable insight for real-world challenges. He holds a Ph.D. from Tennessee Technological University and currently leads the LandScan Mosaic project, advancing high-resolution population modeling.

Publications