Research Post Doc Fellow

The petitioner proposes to develop artificial intelligence methods for analyzing neurodegenerative disorders and their association with specific brain network changes. This work focuses on enhancing early diagnosis and enabling personalized treatment strategies through the integration of AI with medical imaging technologies. The research aims to support clinicians in improving patient outcomes for complex neurological conditions.

The petitioner proposes to develop advanced AI and machine learning models to improve diagnostic accuracy and disease prediction for neurological and oncological disorders. The work involves training AI systems on multimodal biomedical data, including genetic information and brain imaging, to identify early therapeutic targets. The goal is to enhance early detection and inform targeted therapy to improve patient outcomes and reduce U.S. healthcare costs.

The petitioner endeavors to develop deep learning algorithms that accurately interpret and utilize complex real-world data across diverse domains relying on computer vision. His work focuses on enhancing color fidelity in digital media, improving environmental prediction accuracy, and elevating diagnostic precision in healthcare, specifically for conditions like Alzheimer's disease.

The petitioner proposes to continue developing deep-learning techniques for medical image segmentation and super-resolution. Her work focuses on creating active learning frameworks for medical image analysis and identifying structural imaging markers for neurodegenerative conditions like Alzheimer’s and Parkinson’s disease.