User Interfaces delivered with today's software are usually created in a one-size-fits-all manner, making implicit assumptions about the needs, abilities, and preferences of the "average user" and the characteristics of the "average device." I argue that personalized user interfaces, which are adapted to a person’s devices, tasks, preferences, and abilities, can improve user satisfaction and performance. In this talk, I focus on the portion of my research, which demonstrates how this approach benefits people with motor impairments. I present three concrete systems:

-- SUPPLE, which uses decision-theoretic optimization to automatically generate user interfaces adapted to a person’s device;

-- ARNAULD, which allows optimization-based systems to be adapted to users’ preferences; and

-- SUPPLE++, a system that first performs a one-time assessment of a person’s motor capabilities and then automatically generates user interfaces adapted to that user.
My experiments show that these automatically generated, personalized user interfaces significantly improve speed, accuracy, and satisfaction for users with motor impairments compared to manufacturers’ default interfaces.