Grants

• 2024-2027, ORNL’s PI of a $7M DOE ASCR AI for Science-funded project focused on developing federated learning methods to enhance privacy preservation in foundational models. More info here.
• 2024-2025, PI for a $240K ORNL-LDRD funded project aimed at creating scalable privacy algorithms and designing benchmark analyses for federated learning frameworks.
• 2023-2025, Co-PI of a $900K DOE-ASCR EXPRESS funded project titled Physics-Aware Acceleration for Federated Learning on Scientific Data, aimed at developing energy-efficient, privacy-preserving methods.
• 2021-2022, PI of a $180K ORNL-SEED funded project to create a comprehensive privacy framework for streaming data and edge computing.
• 2020-2022, Co-PI of a $900K ORNL-LDRD funded project addressing privacy challenges in low-shot learning for GeoAI applications.