Driver distraction has become a significant cause of severe traffic accidents over the past
decade. Despite the growing development of vision-driven driver monitoring systems, the …

We present a new on-road driving dataset, called “Look Both Ways”, which contains
synchronized video of both driver faces and the forward road scene, along with ground truth …

Voice assistants (VAs) are increasingly integrated into everyday activities and tasks, raising
novel challenges for users and researchers. One emergent research direction concerns …

Imagine a near-future smart home. Home-embedded visual AI sensors continuously monitor
the resident, inferring her activities and internal states that enable higher-level services …

We develop data-driven models to predict when a robot should feed during social dining
scenarios. Being able to eat independently with friends and family is considered one of the …

Background: Hypoglycemia is a frequent and acute complication in type 1 diabetes mellitus
(T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be …

A lack of sufficient situational awareness is a primary cause of traffic crashes due to human
error. Redirecting a driver's attention to critical objects is essential, but alerting driver about …

Understanding drivers' states is essential for providing personalized interventions and
adaptive feedback in vehicles, thereby ensuring safer driving and a more comfortable driver …

Prior research has designed and evaluated Voice Assistance (VA) for different settings such
as the home, school, and public spaces. Office environments have been relatively …

Despite the benefits of autonomous vehicles, their many challenges have made their wide
scale deployment and adoption slower than hoped for. In order to help spread the potential …