Information Director

Information Director

-  102 posts

Sushant is a Ph.D. candidate at the Golisano College of Computing and Information Sciences at the Rochester Institute of Technology, where he specializes in accessibility for people with disabilities, human-computer interaction and computational linguistics. He is interested in building machine learning (ML) systems that model human communication with a goal to enhance human-to-human or human-to-machine interaction.

2007 Best Student Paper

Slipping and Drifting: Using Older Users to Uncover Pen-Based Target Acquisition Difficulties

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2007 Best Paper

Evaluating American Sign Language Generation Through the Participation of Native ASL Signers

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Individual-Technology Fit: Matching Individual Characteristics and Features of Biometric Interface Technologies with Performance

biometric describes physiological measures that may be used for non-muscularly controlled computer applications, such as brain-computer interfaces

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The Disability Divide: A Study into the Impact of Computing and Internet-related Technologies on People who are Blind or Vision Impaired

The purpose of this study was to find the reasons behind this digital divide for people with disabilities and provide solutions.

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ASSETS 2006

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Socio-Technical Environments Supporting Distributed Cognition for Persons with Cognitive Disabilities

MAPS (Memory Aiding Prompting System), aims to provide a simple effective prompting system for individuals with cognitive disabilities with an interface for designing prompting scripts by caregivers

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The Accessibility and Usability of Websites: Relationships between Measures from Users, Experts and Guidelines

Overall, the main outcome from this study shows that the severity ratings provided by the accessibility and usability guidelines are not valid: although researchers and participants agree each other both within and between groups, there is no agreement with the guidelines’ ratings of severity.

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EdgeWrite: A Versatile Design for Text Entry and Control

EdgeWrite was designed to provide accessible text entry on a variety of platforms to people with motor impairments and to able-bodied users of small devices.

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Generating American Sign Language Classifier Predicates For English-To-ASL Machine Translation

This project has created an English-to-ASL MT design capable of producing classifier predicates.

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Multi-Modal Exploration

we focus on the presentation of multi-modal documents through refreshing pin displays.

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