Connecting users more naturally with their computing environment
Our research focuses on developing devices that will connect users more intimately, naturally, and efficiently with their computing environment. The devices range from large displays to wearable devices to micro-electro-mechanical systems. We collaborate with other groups to build the hardware that will support the next generation of software. We’ve developed ideas for new types of microphones and unique data-input devices, and we’re researching reconfigurable computing hardware.
Lijun Zhu and Dinei Florencio, 3D numerical modeling of parametric speaker using finite-difference time-domain, IEEE – Institute of Electrical and Electronics Engineers, April 2015.
Nathan Wiebe, Ashish Kapoor, and Krysta M. Svore, Quantum Nearest-neighbor Algorithms for Machine Learning, in Quantum Information and Computation, vol. 15, no. 3&4, pp. 0318-0358, Rinton Press, March 2015.
Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, and Eric S. Chung, Accelerating Deep Convolutional Neural Networks Using Specialized Hardware, 23 February 2015.
Yunxin Liu, Zhen Qin, and Chunshui Zhao, AutoCharge: Automatically Charge Smartphones Using a Light Beam, no. MSR-TR-2015-5, January 2015.
Gordon Bell, Supercomputers: The Amazing Race, no. MSR-TR-2015-2, 1 January 2015.
- Sparse Reflections Analysis: Sensor Data from ECCV 2014 Paper
- Foveated 3D Graphics
- .NET Gadgeteer
- Speedy Bus-Mastering PCI Express
- Eye Gaze Keyboard
- Indoor patrol robot
- Project Blush
- Eye Gaze Wheelchair
- Tablet and Stylus Interaction
- EmotoCouch: An exploration in interactive furniture
- Sparse Reflections Analysis
- Compression Accelerators
- Circuit Stickers and Conductive Printing
- Windows 8 + Windows Phone Better Together SDK
- Reducing Disruption from Subtle Information Delivery during a Conversation
- In-Place: Interacting with Large Displays
- Phytics: Physical Analytics
- Celebrity Face Match