Human-computer interaction
Redefining human experiences through innovations in research, design, and technology.
Video
Keynote: Intentional Approaches to Human-Computer Collaboration
Emerging technologies like artificial intelligence and mixed reality have the potential to upend the way we create, work, and interact with one another. This disruption is an opportunity and a challenge. As we see technologies…
Video
Drawiz: Making Technical Diagrams Accessible to People with Visual Impairments
We have all heard the saying that a picture is worth a thousand words. It is particularly true in STEM fields where technical diagrams are used universally as a core construct for communicating ideas. And…
Video
Task Intelligence: Doing More with Less
Tasks—defined pieces of work ranging in scope from the specific, such as sending an email, to the broad, such as shipping a feature—are central to all aspects of personal and team productivity. Task intelligence spans…
Video
Recommendation and Learning to Improve Personal Productivity
Artificial intelligence has the potential to improve productivity throughout the workplace by leveraging how people communicate to proactively connect a person to the right people and information. Providing this benefit requires key system capabilities, including…
Video
Microproductivity: Getting Big Things Done Using Smaller Moments
In today’s world, people have to attend to a number of tasks near simultaneously, and with the widespread use of mobile devices, tasks can be tackled almost anywhere at any time. It is not surprising,…
Publication
Decentralized & Collaborative AI on Blockchain
Tool
Bidirectionally transformed strings
The bistring library provides non-destructive versions of common string processing operations like normalization, case folding, and find/replace. Each bistring remembers the original string, and how its substrings map to substrings of the modified version.
Tool
Human pose estimation
The project is an official implementation of our CVPR2019 paper “Deep High-Resolution Representation Learning for Human Pose Estimation”