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What Do AI Agents Need to Know? Designing User-Controlled Context for Data Workflows
Onging work 2026 - Present
I am investigating what information people want AI agents to retain across data workflows, how they want to manage it, and how it relates to their goals and values.
I will develop and evaluate an agent harness that enables users to inspect and control the context agents use across data-related tasks.
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How Do People Debug Complex SQL Queries With LLMs? A Qualitative Study
Nicole Sullivan, Ella Cao, Leilani Battle, and Magdalena Balazinska 2025 - Present
Conducted a user study examining how novice and expert users interact with
LLMs when debugging NL2SQL queries, with the goal of informing more effective
human-AI collaboration in data-driven tasks.
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KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration
Guorui Xiao, Enhao Zhang, Nicole Sullivan, Will Hansen, Magdalena Balazinska
CIDR, 2026 | 2025 - Present
Exploring the human-AI interaction layer of a explainable multimodal DBMS. Interested in
how users query, debug, and interpret multimodal results, and how the system can
best surface explanations and lineage to support understanding and trust.
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Virtual Fidgets: Opportunities and Design Principles for Bringing Fidgeting to Online Learning
Sam Ross, Nicole Sullivan, Jina Yoon
CHI EA, 2023
Explored how virtual fidgets could support attention during online lectures.
Through a study with eight students, we identified eight themes in their
experiences and proposed four design principles for future virtual fidgets.
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Interactive Dataset Visualization Tool for Environmental Justice Community Groups
Microsoft Research - Undergraduate Research Porgram, May 2021 - Aug. 2021
Created an interactive dataset visualization tool with R to enable environmental justice community
groups
to explore air quality concerns in their community with the Project Eclipse sensor data.
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Bison Hacks the Yard: Assisting Underrepresented Students Overcome Impostor Syndrome with Augmented Reality and Artificial Intelligence
Nicole Sullivan
AAAI Undergraduate Consortium, 2021
Aimed to reduce impostor syndrome in underrepresented students through strengthening data structure
skills with an agumented reality application.
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Soul Glow: Enhancing Digital Mental Health Support for Underrepresented Students
University of California, Irvine - STAR Lab, Aug. 2020 - May 2021
Assisted with the qualitative coding of an exploratory survey and participatory design workshops aimed at gathering insights of Black and
Latinx students' perspectives of campus services accessibility.
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Sea Level Predictions using Machine Learning
New York University - CDS Undergraduate Research Porgram, Jan. 2021 - May 2021
Attempted to provide probabilistic forescasts of sea levels using Gaussian Process,
Neural Networks, and different variations of these models. (Github Repo)
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