This research combines CT and MRI brain imaging using machine learning to detect stroke risk markers more quickly. By translating fast CT scans into MRI-level insights, clinicians may identify dangerous intraplaque hemorrhages earlier, improving stroke prevention and diagnosis. The multimodal approach could also enhance imaging for neurological diseases such as Alzheimer’s and Parkinson’s.

This research develops a novel MRI-based method to detect blood–brain barrier leakage associated with stroke. By comparing pre- and post-contrast brain images, the approach enables early detection, monitoring of treatment response, and risk prediction, offering new possibilities for stroke prevention and improved patient outcomes

Aphasia impairs language but not necessarily communication. My research explores how people with aphasia use nonverbal cues, interaction with conversation partners, and contextual support to communicate effectively despite limited language skills. By testing these elements in the lab, the work aims to improve therapy methods and real-world communication outcomes for people with aphasia.