An ability to process, understand, and share data is critical to many of today’s computational tasks. Our group’s work takes a human centered view on data analytic problems. Some of our advances include a machine learning algorithm that tries to minimize the burden on people answering questions needed to support prediction and decreasing the impact of uncertainty by carrying it forward into interactive systems rather than guessing the correct interpretation without any knowledge of the user who is interacting with a system.
Quantifying Aversion to Costly Typing Errors in Expert Mobile Text Entry Text entry is an increasingly important activity for mobile device users. As a result, increasing text entry speed of expert typists is an important design goal for physical and soft keyboards. Mathematical models that predict text entry speed can help with keyboard design and […]
Leveraging Human Routine Models to Detect and Generate Human Behaviors An ability to detect behaviors that negatively impact people’s wellbeing and show people how they can correct those behaviors could enable technology that improves people’s lives. Existing supervised machine learning approaches to detect and generate such behaviors require lengthy and expensive data labeling by domain […]
Watch-ya-doin is an innovative experienced based sampling framework for longitudinal data collection and analysis. Our system consists of a smartwatch and an android device working unobtrusively to track data. Our goal is to train on and recognize a specific activity over time. We use a simple wrist-worn accelerometer to predict eating behavior and other activities. These are inexpensive […]
Modeling and Understanding Human Routine Behavior Human routines are blueprints of behavior, which allow people to accomplish their purposeful repetitive tasks and activities. People express their routines through actions that they perform in the particular situations that triggered those actions. An ability to model routines and understand the situations in which they are likely to […]
In recent years, surveys have been shifting online, offering the possibility for adaptive questions, where later questions depend on responses to earlier questions. We present a general framework for dynamically ordering questions, based on previous responses, to engage respondents, improving survey completion and imputation of unknown items. Our work considers two scenarios for data collection […]
Improving the information economy for tenants pre-lease signing.
Improving healthcare decision making with better workflow and information flow.
The goal of the Stepgreen project is to leverage Internet scale technologies to create opportunities for reduced energy consumption. The original vision of the project was to leverage existing online social networks to encourage individual change. Since then the project has broadened to include a number of other ideas. We have explored the impact of […]