Research
Research Groups > Human-Computer Interaction
-- Faculty Images ----> Timothy Bickmore Timothy Bickmore Magy Seif El Nasr Magy Seif El-Nasr Harriet Fell Harriet Fell Carole Hafner Carole Hafner Stephen Intille Stephen Intille Marty Vona Marty VonaNortheastern's human-computer interaction (HCI) group examines new ways of working with computers. From interactive agents and sensor-enabled mobile technologies to help people manage their health to devices that monitor whether a driver is paying attention to the road, the group develops tools that improve quality of life.
The group’s primary research areas include artificial intelligence; speech and natural language processing with a focus on health informatics; computational sensing for health technologies; simulation and conversational agents; and speech channels as input to computers.
Team Achievements
- Developed medical ontologies to enable researchers to more effectively search medical databases to find information relevant to their needs;
- Created software to analyze infants' babble and provide diagnostic information on whether a child may be at risk for speech-related problems;
- Created an animated virtual nurse that educates hospital patients about their health conditions and post-discharge self-care, encourages people to exercise and take medications as prescribed, and simulates face-to-face conversations between patients and healthcare professionals;
- Investigated the use of mobile phone technology to monitor the physical activity of children and adults and motivate them to change their behavior to promote long term weight management;
- Applied human attention models to the design of mobile and ubiquitous computing systems to design safer interfaces for environments in which multiple tasks must be attended to (such as driving a car while using an electronic navigation system);
- Developed methods for enabling 3-D object recognition with learning.
- Assisted NASA with challenges related to the human operation of complex robots
- Created hardware and software sensing systems for home environments that automatically detect health-related behaviors and respond with tailored, just-in-time feedback to create persuasive computing technologies.
