Lance Drane Research Software Engineer Contact DRANELT@ORNL.GOV All Publications Interpretable machine learning models classify minerals via spectroscopy Privacy Preserving Federated Learning for Advanced Scientific Ecosystems A Microservices Architecture Toolkit for Interconnected Science Ecosystems Best practices for documenting a scientific Python project Leveraging Single-Page Applications for Seamless Scientific Workflows: DevSecOps Considerations Enabling Interconnected Science Workflows through an Adapter Approach Towards a Software Development Framework for Interconnected Science Ecosystems REAL-TIME AUTOMATED HEALTH INFORMATION TECHNOLOGY HAZARD DETECTION Key Links GitHub Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Advanced Computing Systems Research Section Software Engineering Group
Research Highlight Discovery of Spectrographic Features in Uranium Compounds through Machine Learning
