Mr. Daniel Adams

Daniel is an Associate R&D Scientist with the Human Geography group at Oak Ridge National Laboratory. His research interests encompass topics on inherent randomness, data mining, and structured decision-making within the geospatial sciences. He has applied his expertise across diverse fields such as human dynamics, environmental characterization, climate science, and landscape ecology. Daniel's preferred methodologies are rooted in probability, statistics, Bayesian reasoning, and machine learning, including deep learning techniques.

Holding degrees from Tennessee Technological University in Geoscience and Informatics, Daniel is also a doctoral candidate in the Environmental Sciences, specializing in GeoAI & Intelligent Systems. Before joining ORNL, Daniel held the position of Data Science Coordinator at the U.S. Fish & Wildlife Service (USFWS) Science Applications program. In this capacity, he focused on various projects that catered to the scientific needs of the biological staff in the Middle Southeast and Caribbean geographies of the U.S. Daniel's work involved both the development and delivery of applied research, targeting the unique requirements of the biological staff, as well as landscape-scale strategic habitat conservation through the Southeast Conservation Adaptation Strategy.