The Johns Hopkins University Data Science and AI Institute has selected the recipients of its inaugural Data Science and AI Trusted Dataset Awards.
Mathias Unberath, the John C. Malone Assistant Professor of Computer Science as of July 1, was selected for his project, “A Trusted Living Dataset and Compute Infrastructure for Ambient Intelligence in JHM Operating Rooms.”
A core faculty member in the Malone Center for Engineering in Healthcare and the Laboratory for Computational Sensing and Robotics, Unberath works to advance healthcare by creating collaborative intelligent systems that support clinical workflows.
The Data Science and AI Institute recognizes that trusted datasets form the core of much of its scholarship and translation and are critical for the development of trustworthy AI systems. Part of the Data Science and AI Institute’s mission is to establish Johns Hopkins as a premier source of trusted datasets for research, scholarship, and translation. The Data Science and AI Trusted Dataset Awards are intended to further this aspect of its mission.
These inaugural funding awards support projects that address key aspects of data creation, documentation, quality assurance, and data integrity critical for developing trustworthy AI systems.
Jim Bellingham, the Johns Hopkins Data Science and AI Institute research director for safety and assurance, said, “Data is the foundation on which we build our research programs and AI systems. We were delighted with the strong response to our Trusted Dataset Program, and we are excited to launch our first teams.”