Sharifa Alghowinem received her Ph.D. at the Australian National University, Computer Science Research School in 2015.
She received her MSc in Software Engineering at the University of Canberra in 2010, and her BSc in Computer Applications at King Saud University in 2004.
Her research interests include speech processing, computer vision, affective computing, and machine learning.
She worked as a lecturer at the University of Canberra in 2011, and currently holds a research and teaching position at Prince Sultan University.
She also worked as a postdoc at Australian National University for Human-Centered Computing group, and at Massachusetts Institute of Technology in the Personal-Robot group.
MIT Fellowship Research Abstract:
Social robots are great medium for coaching intervention to maintain the healthy physical and mental wellbeing of their owners. Several projects are currently running in this context including a social robot for medical adherence intervention and emotional wellness intervention (e.g. stressed, lonely). For the medical adherence intervention, the social robot monitors pill bottle usage to give real-time feedback on medication intake. For example, if a patient was reminded by the robot to take a medication, then they picked the wrong bottle, the robot will notify them to pick the correct one. On the other hand, in emotional wellness projects, the social robot is used to track and improve the user's emotions. For example, when the robot detects that the owner had a low mood, it could coach them in some positive psychology conversations that might lead to enhancing their mood.