Fang and Rashidi receive distinguished recognition as ‘Rising Stars (Engineering)’ from the Academy of Science, Engineering, and Medicine of Florida

Drs. Ruogu Fang and Parisa Rashidi have achieved the distinguished recognition of Rising Stars (Engineering) from the Academy of Science, Engineering, and Medicine of Florida (ASEMFL). They received this recognition for pioneering contributions in medical artificial intelligence for brain health and for their tireless education of diverse, transdisciplinary researchers.

The ASEMFL is an esteemed gathering of Florida’s preeminent scholars, encompassing individuals who both reside and work in the state. Situated at the University of Central Florida in Orlando, ASEMFL is a non-profit organization that unites top-tier scholars and researchers from various universities, public agencies, and industries throughout Florida. Their collective mission is to delve into critical issues at the intersection of science, engineering, and medicine that have a direct impact on the people of Florida. Furthermore, they provide impartial and expert advice concerning these matters.

Dr. Fang’s research revolves around the integration of artificial intelligence (AI) and deep learning with the intricacies of the human brain. Her research encompasses two principal themes: AI-empowered precision brain health and brain/bio-inspired AI. Her work addresses compelling questions such as using machine learning techniques to quantify brain dynamics, facilitating early Alzheimer’s disease diagnosis through novel imaging, predicting personalized treatment outcomes, designing precision interventions, and leveraging principles from neuroscience to develop the next generation of AI. At the heart of her work is the Smart Medical Informatics Learning and Evaluation (SMILE) lab, where she is dedicated to creating groundbreaking brain and neuroscience-inspired medical AI and deep learning models, as well as educating diverse, transdisciplinary researchers. The primary objective of these models is to comprehend, diagnose, and treat brain disorders, all while navigating the complexities of extensive and intricate datasets.

Dr. Rashidi’s research aims to develop intelligent patient monitoring systems using artificial intelligence and sensing technology. Her methodology involves developing scalable machine learning techniques to tackle challenging problems in the context of intelligent patient monitoring systems. In the inpatient setting, her lab is transforming patient care in the Intensive Care Unit (ICU) by developing autonomous monitoring tools for incorporating granular and autonomous visual assessments, and for predicting the acuity state of patients in real-time. In the outpatient setting, she is developing intelligent tools for monitoring the cognitive and mental health of community-dwelling patients using wearable and digital sensor technology powered by machine learning.