When: Friday, April 28, 2:00 PM
Where: CBLS 100
Who: Basheer Qolomany, University of Nebraska at Kearney
The Role of Artificial Intelligence and Machine Learning in Complex Systems
Current methods for diagnosing PAD require specialized vascular laboratory tests and do not allow natural environment detection, monitoring, or management of chronic PAD disease. The research goal of this application is to understand and classify human gait signatures for patients with PAD using ML algorithms. Gait analysis has proven to be important for the determination of the mechanisms and severity of functional limitations, the measurement of treatment effectiveness, and the monitoring of the progression of chronic diseases. Recent advances in wearable sensor technology have enabled continuous and detailed measurement of the movement of patients in their natural environments. Researchers have begun to extract gait features that characterize specific chronic conditions or indicate a clinically significant change in the movement characteristics of a patient.
About the speaker:
Basheer Qolomany received the Ph.D. and second master’s en route to Ph.D. degrees in computer science from Western Michigan University (WMU), Kalamazoo, MI, USA, in 2018 and the B.Sc. and M.Sc. degrees in computer science from the University of Mosul, Iraq, in 2008 and 2011, respectively. He is currently an Assistant Professor with the Department of Cyber Systems, at the University of Nebraska at Kearney (UNK), Kearney, NE, USA. His research interests include Complex systems, evolutionary computation, AI, machine & deep learning, and big data analytics in support of population health, Cybersecurity, and smart services.