Xinyi Liu
I am a second-year PhD student in Computer Science at Northeastern University, advised by Prof. David A. Smith.
My research focuses on evaluating and aligning LLMs and AI agents, particularly how their reasoning, behavior, and interactions with humans remain consistent with human goals and agency. I am broadly interested in LLM/agent evaluation, alignment and AI safety, structured reasoning and information extraction, and human–AI interaction.
Previously, I conducted research at Microsoft Research in the Social Computing group and at Harvard Medical School in the HIDIVE Lab, where I was advised by Prof. Nils Gehlenborg. I received my M.S. from The University of Texas at Austin and my B.S. in Computer Science and Economics from the University of Maryland, College Park, where I worked with Prof. Zhicheng Liu and Prof. Hannah Bako.
Current Research
Open to Collaboration
If you are interested in joining, collaborating, or discussing a research idea, feel free to reach out by email.
news
| Sep 01, 2026 | Serving as a Teaching Assistant for CS 7170: Seminar in AI at Northeastern University for Fall 2026. |
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| Jan 01, 2026 | Our paper, “Can LLMs bridge domain and visualization? A case study on high-dimension data visualization in single-cell transcriptomics,” was published in IEEE TVCG. |
| Nov 02, 2025 | Served as Technology Chair on the Organizing Committee of IEEE VIS 2025. |
| Jan 05, 2025 | Served as an Associate Chair for ACM Creativity & Cognition 2025. |
| Nov 30, 2024 | Awarded as a Super Reviewer for ACM CHI 2025. |
selected publications
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Can LLMs Bridge Domain and Visualization? A Case Study on High-Dimension Data Visualization in Single-Cell TranscriptomicsIEEE Transactions on Visualization and Computer Graphics, 2026 -
Unveiling how examples shape visualization design outcomesIEEE Transactions on Visualization and Computer Graphics, 2024 -
Evaluating the semantic profiling abilities of llms for natural language utterances in data visualizationIn 2024 IEEE Visualization and Visual Analytics (VIS), 2024 -
Creating an authoring tool for k-12 teachers to design ml-supported scientific inquiry learningIn Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024 -
Understanding how designers find and use data visualization examplesIEEE Transactions on Visualization and Computer Graphics, 2022