IV Ramakrishnan

schoolStony Brook Universitybar_chart#544 Global Rank

Total Papers

HCI Rank

#544

Research Areas

Years Active

Recent Publications

Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users’ Support Needs

Accessibility forums and, more recently, generative AI tools have become vital resources for blind users seeking solutions to computer-interaction issues and learning about new assistive technologies, screen reader features, tutorials, and software updates. Understanding user experiences with these resources is essent…

CHI '265th+ AuthorSoft Keyboard & Virtual Keyboard Design +1

KeySense: LLM-Powered Hands-Down, Ten-Finger Typing on Commodity Touchscreens

Existing touchscreen software keyboards prevent users from resting their hands, forcing slow and fatiguing index-finger tapping (“chicken typing”) instead of familiar hands-down ten-finger typing. We present KeySense, a purely software solution that preserves physical keyboard motor skills. KeySense isolates intention…

CHI '265th+ AuthorVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille) +3

Lost in Instructions: Study of Blind Users’ Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Products

AI tools like ChatGPT and Be-My-AI are increasingly being used by blind individuals. Although prior work has explored their use in some Do-It-Yourself (DIY) tasks by blind individuals, little is known about how they use these tools and the available product-manual resources to assemble, operate, and troubleshoot physi…

UIST '255th+ AuthorVoice Accessibility +2

Enabling Auto-Correction on Soft Braille Keyboard

A soft Braille keyboard is a graphical representation of the Braille writing system on smartphones. It provides an essential text input method for visually impaired individuals, but accuracy and efficiency remain significant challenges. We present an intelligent Braille keyboard with auto-correction ability, which use…

CHI '255th+ AuthorHuman-LLM Collaboration

Tap&Say: Touch Location-Informed Large Language Model for Multimodal Text Correction on Smartphones

While voice input offers a convenient alternative to traditional text editing on mobile devices, practical implementations face two key challenges: 1) reliably distinguishing between editing commands and content dictation, and 2) effortlessly pinpointing the intended edit location. We propose Tap&Say, a novel multimod…

CHI '253rd AuthorEV Charging & Eco-Driving Interfaces +1

LLM Powered Text Entry Decoding and Flexible Typing on Smartphones

Large language models (LLMs) have shown exceptional performance in various language-related tasks. However, their application in keyboard decoding, which involves converting input signals (e.g. taps and gestures) into text, remains underexplored. This paper presents a fine-tuned FLAN-T5 model for decoding. It achieves…

UIST '245th+ AuthorVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille) +1

Accessible Gesture Typing on Smartphones for People with Low Vision

While gesture typing is widely adopted on touchscreen keyboards, its support for low vision users is limited. We have designed and implemented two keyboard prototypes, layout-magnified and key-magnified keyboards, to enable gesture typing for people with low vision. Both keyboards facilitate uninterrupted access to a…

CHI '242nd AuthorHand Gesture Recognition +1

Hand Gesture Recognition for Blind Users by Tracking 3D Gesture Trajectory

Hand gestures provide an alternate interaction modality for blind users and can be supported using commodity smartwatches without requiring specialized sensors. The enabling technology is an accurate gesture recognition algorithm, but almost all algorithms are designed for sighted users. Our study shows that blind use…

CHI '235th+ AuthorVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)

Modeling Touch-based Menu Selection Performance of Blind Users via Reinforcement Learning

Although menu selection has been extensively studied in HCI, most existing studies have focused on sighted users, leaving blind users' menu selection under-studied. In this paper, we propose a computational model that can simulate blind users’ menu selection performance and strategies, including the way they use techn…

CHI '235th+ AuthorEye Tracking & Gaze Interaction

GlanceWriter: Writing Text by Glancing Over Letters with Gaze

Writing text with eye gaze only is an appealing hands-free text entry method. However, existing gaze-based text entry methods introduce eye fatigue and are slow in typing speed because they often require users to dwell on letters of a word, or mark the starting and ending positions of a gaze path with extra operations…

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