Advances in low- and no-power sensing, communication and interaction technologies offer new possibilities for blending digital innovation with our physical environment.
From gesture recognition that allows people to interact with objects in new ways, to low-power sensors that collect and transmit data about temperature, air quality, urban accessibility and more, our researchers are tapping into the potential of computation to transform how we experience the world around us.
Research Groups & Labs
UbiComp Lab
The Ubiquitous Computing (UbiComp) Lab develops innovative systems for health sensing, low-power sensing, energy sensing, activity recognition and novel user interface technology for real-world applications.
Robotics and State Estimation Lab
We are interested in the development of computing systems that interact with the physical world in an intelligent way. To investigate such systems, we focus on problems in robotics and activity recognition.
Faculty Members
Centers & Initiatives
Computing for the Environment (CS4Env) at the University of Washington supports novel collaborations across the broad fields of environmental sciences and computer science & engineering. The initiative engages environmental scientists and engineers, computer scientists and engineers, and data scientists in using advanced technologies, methodologies and computing resources to accelerate research that addresses pressing societal challenges related to climate change, pollution, biodiversity and more.
DFab is a network of researchers, educators, industry partners, and community members advancing the field of digital fabrication at UW and in the greater Seattle region.
Highlights
Computing Research Association
The Computing Research Association recognized Schulz for her research and leadership in computer graphics, including her work to advance new computational tools for manufacturing-oriented design.
UW News
Researchers in the Allen School’s UbiComp Lab created the ProxiCycle sensor system to get a handle on which routes are best — and worst — for bikes, finding a significant correlation between the sensor data and other indicators of cycling risk.
Allen School News
The ACM Special Interest Group on Computer-Human Interaction recognized Fogarty’s leadership and contributions to human-computer interaction research including ubiquitous computing, interactive machine learning, accessibility and personal health informatics.