Selected Publications
Contextual Scaffolding and Self-Efficacy: Supporting Computer Skill Development among Blind Learners in India
ACM CHI '26 • April 2026
Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
Inclusive computer literacy initiatives for blind or visually impaired (BVI) learners are growing, but research largely reflects well-resourced Global North settings. To understand challenges in resource-constrained, multicultural contexts like India, we conducted a four-month contextual inquiry at two training centers serving 94 BVI students. We found rigid, experience-driven instruction and a visually centered curriculum that overlooks BVI learners’ lived experiences and weakens self-efficacy. We argue for culturally responsive computing pedagogy supported by locally adaptable scaffolds for BVI students in developing societies.
Insights in Adaptation: Examining Self-reflection Strategies of Job Seekers with Visual Impairments in India
ACM CSCW • October 2025
Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
We present a study on self-reflection strategies among blind and visually impaired (BVI) job seekers in India. Despite gaining digital skills, many face challenges aligning with industry expectations due to limited personalized feedback and inaccessible job-prep tools. Self-reflection is often a social process shaped by peer interactions, yet current systems lack the tailored support needed for effective growth. Our findings inform the design of future tools to better guide reflective job-seeking and address the unique needs of BVI individuals in the Global South.
Best Paper Award
Adapting Online Customer Reviews for Blind Users: A Case Study of Restaurant Reviews
ACM Web4All • April 2025
Mohan Sunkara, Akshay Kolgar Nayak, Sandeep Kalari, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
We present QuickCue, an assistive browser extension that improves the usability of online restaurant reviews for blind screen reader users. QuickCue restructures review content into a hierarchical format organized by aspects (e.g., food, service, ambiance) and sentiment (positive/negative), enabling faster, more focused exploration with minimal navigation. Powered by GPT-4, it performs aspect-sentiment classification and generates targeted summaries, significantly reducing listening fatigue and helping users make more informed decisions.
Towards Enhancing Low Vision Usability of Data Charts on Smartphones
IEEE VIS (TVCG) • September 2024
Yash Prakash, Pathan Aseef Khan, Akshay Kolgar Nayak, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
We present GraphLite, a mobile assistive system that makes data charts more usable for low-vision screen magnifier users. GraphLite transforms static, non-interactive charts into customizable, interactive views that preserve visual context under magnification. Users can selectively focus on key data points, personalize chart appearance, and reduce panning effort through simplified gestures.
