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Hardware and Devices

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.

Gordon Bell, Supercomputers: The Amazing Race, no. MSR-TR-2015-2, 1 January 2015.

Dimitris Papanikolaou, A.J. Brush, and Asta Roseway, BodyPods: Designing Posture Sensing Chairs for Capturing and Sharing Implicit Interactions, in In Proceedings of TEI 2015, ACM – Association for Computing Machinery, January 2015.

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