👋🏼 Hello there, I’m Aayushi!

I’m a third-year Ph.D. student, advised by Dr. Julie Kientz, in the department of Human Centered Design & Engineering at the University of Washington. My research focuses on using AI and machine learning to develop accessible learning technologies for children with speech and language difficulties. I’m also passionate about helping children build AI literacy competencies so they can understand and interact with AI in thoughtful, informed ways.

Previously, I worked as a middle school Computer Science teacher at Ridgefield Academy. I also served as a research assistant at Utah State University with Dr. Kristin Searle, contributing to projects that integrated electronic textiles into computer science education.

I received my BA from Swarthmore College, with a double major in Computer Science and Studio Arts. During my time at Swarthmore, I founded Nepali Girls Code, an initiative that provides culturally responsive computer science education to middle school girls in Nepal. I interned at Autodesk, and I am a CERES scholar with the Jacobs Foundation.


Recent News

- Sep 2024: Excited to be sharing new research at AIES 2024. We’ve made preprints available for our accepted work on representation bias of adolescents in AI models. Please get in touch if you’d like to connect in Santa Clara this October!

- Sep 2024: Presented a poster on interactive play for developing AI literacy at the CERES Fall Intensive.

- Aug 2024: Congratulations to my REU students, Trushaa and Arya, for presenting their first posters at the DUB REU Poster Showcase 🎉.

- Aug 2024: Received Honorable Mention Best Paper Award for our research on AI based support for Speech-Language Pathologists.


Selected Publications

see my Google Scholar for the full list of publications

Mediating Culture: Cultivating Socio-cultural Understanding of AI in Children through Participatory Design.
Designing Interactive Systems (DIS) 2024.
Aayushi Dangol, Michelle Newman, Robert Wolfe, Jin Ha Lee, Julie Kientz, Jason Yip, Caroline Pitt
Summary: Introduces participatory approach to co-designing AI with kids in ways that facilitate an understanding of generative AI as a mediator of culture.

Representation Bias of Adolescents in AI: A Bilingual, Bicultural Study.
AI Ethics and Society (AIES) 2024
Robert Wolfe, Aayushi Dangol, Bill Howe, & Alexis Hiniker
Summary: Study comparing biases about adolescents learned by AI to similar biases identified in traditional and news media sources in both the U.S. and Nepal. Conducts workshops with 13 U.S. teenagers and 18 Nepalese teenagers to understand how teenagers themselves view fair representation in media and AI.

Opportunities and Challenges for AI-Based Support for Speech-Language Pathologists.
Best Paper Honorable Mention, Human-Computer Interaction for Work (CHIWORK) 2024.
Hyewon Suh, Aayushi Dangol, Hedda Meadan, Carol Miller, Julie Kientz
Summary: Study offers insights into how AI can be integrated to address Speech-Language Pathologists’ needs, increase their capacity, and improve job satisfaction.