I am a CS PhD Candidate at Matter of Tech Lab and Apple AIML PhD Scholar Fellow, advised by Prof. Thijs Roumen at Cornell Tech and co-advised by Prof. Stephanie Valencia from UMD. My research interests center on reimagining augmentative and alternative communication (AAC) as a vehicle for personal expression rather than a mere substitute for speech. I develop AI-driven tools that transcend basic transactions to foster truly expressive conversational engagement. I focus on creating and researching AAC systems that prioritize user agency and personal identity. By addressing privacy and adaptability, my work seeks to unlock meaningful communication for those whose expressive voices are often ignored.
My research is supported by the Apple Scholar in AIML PhD Fellowship (2026)
Areas of interest: accessibility, disability, AAC, expressive communication, LLMs, human-AI interaction, human-centered machine learning, and HCI.
We study how ultra-personalized AI can support AAC usersβ voices. A 10-month auto-ethnography shows how fine-tuned models enhance fluency while raising new questions around agency, identity, and privacy
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We investigate how CAD interfaces can guide exploration and comparison of workflows. Specifically, comparison can advance users' reasoning about design decisions. We developed a prototype interface, CAMeleon, which lets users compare fabrication workflows. Users load 3D models and preview outcomes from different workflows.
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We study how AAC users create and negotiate expressive backchanneling using multi-modal cues, this study reveals design opportunities to support real-time presence and conversational rhythm in AAC technology.
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Best Paper Honorable Mention Award (best 5%) π
Jury Best Demo Award π
We study how AI-powered AAC interfaces can help users with speech disabilities deliver timely, humorous comments. This study highlights design insights to improve expressivity and timing in AAC technology.
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Best Paper Honorable Mention Award (best 5%) π
We present SplatOverflow, a workflow to support end-users, community members and manitainers asynchronously troubleshoot hardware issues.
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