Daniel Kifer

Daniel Kifer is a Professor in the Computer Science and Engineering department at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His work bridges computer science, privacy-preserving machine learning, and geoscience applications. With over 10,000 citations and a high h-index, he focuses on methods to unify theoretical and applied research.

• Research Interests: Differential Privacy, Privacy-Preserving Machine Learning, Physics-Informed Neural Networks, Landslide Prediction, and Formal Verification of Privacy Systems.

Recent projects include grants from the National Science Foundation:

• SaTC: CORE: Small (2024): privacy-preserving user data embedding in machine learning pipelines.
• SaTC: CORE: Medium (2017-2023): formal methods for differential privacy and accuracy optimization.

His research outputs span domains like geoscience, database systems, and policy analysis, emphasizing precision and scalability of privacy-preserving algorithms.