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Today’s mobile computers provide omnipresent access to information, creation and communication facilities. It is undeniable that they have forever changed the way we work, play and interact. However, mobile interaction is far from solved. Diminutive screens and buttons mar the user experience, and otherwise prevent us from realizing their full potential. We explored and prototyped a powerful alter

Faster Progress Bars: Manipulating Perceived Duration with Visual Augmentations Progress bars, typically used to visualize the progression of an extended operation, are prevalent in current user interfaces. In desktop systems, advanced users often multitask during these periods. However, it is not uncommon for advanced users to watch an install finish or file transfer complete – especially if they

Skinput: Appropriating the Body as an Input Surface Devices with significant computational power and capabilities can now be easily carried on our bodies. However, their small size typically leads to limited interaction space (e.g., diminutive screens, buttons, and jog wheels) and consequently diminishes their usability and functionality. Since we cannot simply make buttons and screens larger with

We present Scratch Input, an acoustic-based input technique that relies on the unique sound produced when a fingernail is dragged over the surface of a textured material, such as wood, fabric, or wall paint. We employ a simple sensor that can be easily coupled with existing surfaces, such as walls and tables, turning them into large, unpowered and ad hoc finger input surfaces. Our sensor is suffic

I'm an Associate Professor of Human-Computer Interaction at Carnegie Mellon University, directing the Future Interfaces Group. My research group creates new sensing and interface technologies that open new modes of interaction between humans and computers. These efforts often lie in emerging use domains, such as smart environments, wearable computing, and augmented reality. Please see my research

Web Trigrams: Visualizing Google's Tri-Gram Data Back in late 2006, Google released a massive set of web n-gram data (basically pieces of sentences). A trigram (n=3), for example, might be "I like food" or "frog is tasty." Each n-gram is also labeled with the number of times it appeared in Google's corpus. The entire archive, which is almost 100GB uncompressed, has unigrams (n=1) through fivegrams

I'm an Associate Professor of Human-Computer Interaction at Carnegie Mellon University, directing the Future Interfaces Group. My research group creates new sensing and interface technologies that open new modes of interaction between humans and computers. These efforts often lie in emerging use domains, such as smart environments, wearable computing, and augmented reality. Please see my research

Introduction Wikipedia is an interesting dataset for visualization. As an encyclopedia, it's articles span millions of topics. Being a human edited entity, connections between topics are diverse, interesting, and sometimes perplexing - five hops takes you from subatomic particles to Snoop Dog. Wikipedia is revealing in how humans organize data and how interconnected seemingly unrelated topics can

This visualization shows the structure of three levels of Wikipedia category pages and their interconnections. Centered in the graph is a parent node. Pages that are linked from this parent node are rendered inside the ball. Finally, pages that are linked to the latter (secondary) nodes are rendered on the outer ring. Links between category pages are illustrated by edges, which are color coded to