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Personal profile

Research Interests

Past research has focused on understanding the real-time processes involved in reading and picture perception. This work has mainly been conducted using research methods based on the recording of eye movements.

My current research includes the following projects:

1. Cognition and Eye Movement Control during Reading. (UIUC Research Board grant). The goal of this project is to understand how cognitive processes influence eye behavior, so that eye movement data can be used more effectively in the study of cognition.

2. NSF-ITR: Multimodal Human Computer Interaction: Toward a Proactive Computer. (Tom Huang and McConkie, co-PI's) An interdisciplinary project (6 faculty members) investigating ways of giving computers more information about their users so the computers can be more proactive in helping children learn science. My part focuses on using eye movement information to indicate cognitive states (types of processing taking place, indications of processing difficulty, etc.)

3. Visual Attention in Speech Reading: Charissa Lansing, PI. We are using eye movement methods to study the visual cues that deaf people attend to in understanding spoken and signed language.

4. Gaze contingent multi-resolutional displays: (funded by Kodak). We are exploring the effects of visual displays in which only the region to which the gaze is directed is presented in high resolution, with lower resolution at more peripheral locations. This technique can reduce the computation and bandwidth requirements for displays; it also gives information about the nature of human visual perception and attention.

5. Dyslexia: In this research we are studying the use of eye movement data to indicate the processing level at which reading difficulties are being encountered.

I want to understand how cognitive processes are involved in the control of eye behavior, and, from that, just what information about cognition, attention and perception can be obtained from eye movement recording. Also, how this information can be used to increase the effectiveness of human-computer interaction and the identification of processing difficulties.


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