Human-Computer Interaction

Conquer it! is a lightweight proof-of-concept exertion game that demonstrates Body Channel Communication (BCC) in a smart environment.

In this work, we leverage advances in semiconductor optics, RF antenna design and system integration to create a hybrid RFID reader and smart LED lamp, in the form factor of a standard light bulb.

We performed three studies to examine the effects of accurate program response times, repeating unanswered questions, and providing feedback on the children’s likelihood of response.

We propose ways to increase the displayed image pixel resolution without having to manufacture any additional pixels, while at the same time maintaining full-color 24-bit images.

We explore online reinforcement learning techniques to find good policies to control the orientation of a mobile robot during social group conversations.

We propose and demonstrate the viability of using OAM to create an automultiscopic 3D display.

We propose a novel error tolerant optimization approach to generate a high-quality photometric compensated projection.

We show that with selective coding OAM states, off‐axis points and spatial variables encoded with OAM are reproducible.