Qi Zhao

I am a first-year PhD student in Human-Centered Computing at University of Maryland, Baltimore County, advised by Dr. Yasmine Kotturi. Previously, I received my Master in Human-Computer Interaction from Indiana University Indianapolis, and my Bachelor in Computer Science and Technology from Hangzhou Dianzi University.

My research focuses on designing and deploying AI systems that support people with varied digital literacy in everyday work and community contexts. I am interested in how we evaluate AI-generated content, and how tools can be shaped so that people can trust, adapt, and use them to meet their own needs. Currently, I am working on BizChat, an AI-powered business plan writing tool for small business owners and to see how people collectively evaluate AI-generated businessp plans.

qiz1@umbc.edu CV Scholar LinkedIn GitHub

Selected Projects and Publications

  • BizChat thumbnail

    BizChat: AI-Powered Business Planning for Small Business Owners

    Ongoing Project

    How can AI support small business owners in business plan writing and evaluation? BizChat is an AI-powered tool that helps entrepreneurs draft and refine business plans through conversational guidance, making business planning more accessible and less overwhelming. Through system deployments in the workshop, BizChat could support entrepreners to collectively evaluate their business plans.

    Try out BizChat

  • CHI Poster 2026 thumbnail

    "I don't feel lonely because I don't work alone most of the time": Exploring Gig Work as an Opportunity for Social Participation Among Older Adults

    Qi Zhao, Aqueasha Martin-Hammond

    CHI Poster 2026

    What social benefits does gig work offer older adults after retirement? Through interviews with 14 retired online personal shoppers (e.g., Instacart, Shipt), we find that hybrid gig work supports multiple levels of social participation—being with others, interacting, doing activities together, and helping others—beyond financial needs alone.

    PDF

  • Crepe thumbnail

    Crepe: A Mobile Screen Data Collector Using Graph Query

    Yuwen Lu, Meng Chen, Qi Zhao, Victor Cox, Yang Yang, Meng Jiang, Jay Brockman, Tamara Kay, Toby Jia-Jun Li

    CHI 2026 · Honourable Mention Award

    How can academic researchers collect mobile screen data without relying on commercial data monopolies? Crepe is an Android app that lets researchers demonstrate the on-screen data to collect; a novel Graph Query technique then identifies and extracts those UI elements across screens, while giving participants full transparency and easy opt-out.

    PDF Code

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