Data taken directly from the brain, such as from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), holds many secrets. Processing that data remains the biggest obstacle. Artificial intelligence (AI) may help unlock some of the brain’s biggest mysteries.
Data scientist Fahad Saeed uses AI to pinpoint everything from when a seizure may strike — to finding new ways to diagnose autism and attention-deficit/ hyperactivity disorder (ADHD). Saeed creates different AI-powered machine learning models to do what no human can — parse through lots of data to detect patterns that may hold important clues.
Saeed’s National Science Foundation funded project focuses on developing an algorithm to predict when a seizure might strike. It monitors EEG data and tracks any unusual electrical activity in the brain that causes epileptic seizures.
His technology will be incorporated into wearable sensors that feed information to a smartphone. If it detects any irregularities in brain waves, it would prompt an early alert notification that a seizure is about to happen, giving people precious time to prepare and take safety precautions.
Saeed is also working on AI models to pinpoint clues in brain scans that could pinpoint markers for autism, which can be difficult to diagnose. His model would be another tool in the toolbox for doctors and psychologists.
Fahad Saeed
Associate Professor in the Knight Foundation School of Computing and Information Sciences, College of Engineering & Computing
“Impact is what I’m after and to conduct research that can be translated from lab to real life."