This research project is funded by the U.S. National Science Foundation (NSF) under the award CNS-2335686. We are developing a framework to assess and improve the privacy and security of mobile health applications (apps) that collect and use personal health data.

This research project was funded by the U.S. National Science Foundation (NSF) under the award SES-1834597 from May 2018 to March 2022. Changes in the meaning of information as it passes through cyberspace can mislead those who access the information. We develop new datasets and algorithms to identify and categorize medical information based on whether it remains true to the original meaning or undergoes distortion.

Hospitals amass crucial textual data for healthcare, often in disorganized forms within Electronic Health Record (EHR) systems. The semantics of language used in such texts differs a lot from ordinary English. Understanding the domain-specific semantics has consequential applications in streamlining health data, reducing redundancy, identifying errors, and retrieving and preserving valuable information.