Dissertation Proposal Defense - Mingrui Ray Zhang
You are cordially invited to join us for the Proposal Defense of Mingrui Ray Zhang, to be held on Tuesday, March 16, 2021, via Zoom from noon to 2 p.m. PST.
Title: Intelligent Text Input Methods and Metrics
Abstract:
Text input serves as a fundamental interactive part of almost any human-computer system. Traditional desktop settings employ hardware keyboards for text input, which worked well for skilled typists. However, the devices in the current era are becoming mobile and ubiquitous, and have various form factors, and we need new text input interactions to communicate with them. On the other hand, devices are becoming “intelligent”, with powerful hardware processors to run advanced algorithms. Text input can take advantage of these capabilities but only if new algorithms and interaction techniques are developed.
To address the need, I develop intelligent interactions, utilizing the state-of-the-art machine learning techniques, to improve the text input experience on various platforms. My proposed work includes three text input interactions for daily typing in the ubiquitous computing environment: 1) TypeAnywhere: a QWERTY-based text input interaction that detects finger taps with a wearable device and decodes the taps into text. 2) TypeAnywhere One: a single-hand extension for TypeAnywhere, and a friendly version for situational impairments when one hand is occupied. 3) AnchorKeyboard: a non-visual QWERTY keyboard for large touch screens. Together with my previous work, the dissertation contributes to the field of HCI by demonstrating the thesis: artificial intelligence can enable and improve advanced text input interactions, including the entering and editing of text, and the entering of emojis; these interactions, in turn, warrant new text entry metrics for their evaluation.
Committee members:
- Jacob O. Wobbrock, Chair
- Alexis Hiniker, Member
- Leah Findlater, Member
- Shumin Zhai, Member
- James Fogarty, GSR
Zoom Link Details:
https://washington.zoom.us/j/94831135716
Meeting ID: 948 3113 5716
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