Textual narratives for causality & complex systems
Design space + evaluation showing how narratives can complement visualization for causal reasoning.
Mixed-Methods Researcher
I design and evaluate AI-enabled and multimodal interactive systems, focusing on how people understand, trust, and work with intelligent technologies—especially when default interfaces create barriers.
My work combines mixed-methods research, quantitative evaluation, and prototyping to inform accessible, transparent, and human-centered interactive experiences.
PhD and MS from the University of Maryland, College Park, with industry research experience at Meta and Ericsson, and collaborative research with Adobe Research and the Library of Congress. Prior to my research career, I worked as developer at Deloitte Consulting for 4 years building SAP enterprise applications.
Signature contributions
- Human–centered explanation & understanding
- Designing narratiave and language-based explanations that help users reason about complex, causal, and data-driven systems.
- Multimodal & accessible interaction
- Building and studying touch, sound, and multimodal data interactions for blind/low-vision users and other access needs.
- Research → product translation
- Turning study findings into interaction patterns, guidelines, and decision-ready insights with cross-functional partners.
Contact & other links
Email: cvspramod@gmail.com
LinkedIn
Google Scholar
GitHub
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Feel free to reach out for collaboration, questions, or just to say hi!
Note: I'm on the job market for research roles starting Fall 2025.
Selected highlights
Multimodal chart accessibility (touch + sound + speech)
Systems and studies that make data exploration accessible via sensory substitution and multimodal interaction.
Accessible interactions for wearables
Empirical and participatory research on smartwatch input for people with upper-body motor impairments.