Grants

• (2024-2027) Institutional PI of a $7M DOE ASCR AI for Science-funded project focused on developing federated learning methods to enhance privacy preservation in foundational models.
• (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.