The goal of this funded project is to develop methods to reduce patient safety errors in the hospital. This environment is monitored using an array of sensors including the Kinect. Research problems of interest include single- and multi- sensor robust activity recognition, modeling inter-user variability, robust tracking in crowded environments and learning domain specific priors for scene understanding.
The candidate will have the chance to work closely with Profs. Suchi Saria (machine learning and health systems analysis), Rene Vidal (computer vision and machine learning), Greg Hager (computer vision and human-machine systems) and Peter Pronovost (MacArthur fellow, medicine and critical care). In addition, this project will take place in the Laboratory for Computational Sensing and Robotics (LCSR). LCSR is home to 80 faculty, students, postdocs, and staff, and is known as one of the preeminent institutions worldwide integrating engineering and medicine.
This project will expose candidates to the emerging and growing application area of computational healthcare and medicine. They will also acquire the necessary skills to lead multidisciplinary research, valuable in seeking positions downstream within academia and industry. The chosen candidate will also be encouraged to seek out new research opportunities within LCSR and to develop independent research projects.
The ideal candidate for this position should have a strong background in low-level image processing. Significant exposure to machine learning (probabilistic modeling approaches, structured prediction, dimensionality reduction) or human activity modeling would be a plus. The project will require engineering contributions, and interaction with an interdisciplinary group of researchers. Candidates for the postdoctoral or research scientist position must have a PhD in computer science, electrical engineering, statistics, biomedical engineering or related disciplines. Those with an interest in moving towards healthcare applications are especially encouraged to apply.
CONTACT: Prof. Suchi Saria at ssaria@cs.jhu.edu with a CV or apply online.