Anind Dey

Much of Dey's research deals with the construction and intersectional nature of ubiquitous computing. In 2002, in a research project at the University of California, Berkeley alongside Scott Lederer and Jennifer Mankoff, the team developed a conceptual model exploring the tangibility and accessibility of everyday end-user privacy in ubicomp environments. The model takes considerations from societal influences, contextual factors, and subjectivity to develop a far-reaching scope for ubicomp privacy. The model was then used to explore an interactional metaphor called situational faces, which makes the issue of privacy in ubiquitous computing environments more accessible to users. This facade presents an abstraction of advanced privacy settings to allow users to more easily establish their preferences.[5]

In 2006,[6] Dey developed a research paper alongside Min Kyung Lee, Scott Davidoff, and John Zimmerman, all of Carnegie Mellon University, exploring and evaluating the usage of home automation technology and their effects on family life. As a collaboration between the School of Design and the Human-Computer Interaction Institute, the research sought to uncover areas of human-centered design that could complement family life, thus providing insight on the potential roles a smart home could play. Following a heuristic design process, the team interviewed dual-income families in their own homes, gauging cultural and ethnographic information, leading to the generation and experimentation of a design concept. The study concluded that such accommodations would allow families to avoid breakdowns in developed routines and improve emotional connectivity between family members and the home, while allowing parents to devote more time and attention to children.[7]

In 2010,[8] Dey, alongside Dana Pavel and Vic Callaghan of the School of Computer Science and Electronic Engineering at the University of Essex, evaluated and presented a highly interfaced system for users to understand and express their own lifestyles and habits through an analysis of compiled data into a story-based representation.[9] Initial findings of the research suggested that data generated from a user base recording a user's daily activity reveals actionable personal goals that a user can draw from to improve their lifestyle. This research, presented at the 6th International Conference on Intelligent Environments in 2010, retrieved data from a number of devices and methods, including a Garmin Forerunner fitness monitor, a heart monitor, mobile phone usage data, and Internet history. This resulted in the design of a story-based presentation of data that connected the data to reveal tendencies within a user's lifestyle.