Human-AI collaboration in expert workflows
Understand people's goals, work contexts, and collaboration with AI to design assistance that fits their needs.
Human-AI Interaction | Natural Language Processing | Computational Social Science
I’m a senior applied scientist at the IDEAS Research group at Microsoft, led by Scott Counts.
I study human-AI collaboration in work that requires expertise and judgment. My research examines how people communicate their needs and interact with AI, how LLMs behave and can be steered, and how using AI changes people’s work. I use interaction traces to make this collaboration visible over time, examining how people steer AI, evaluate its outputs, and recover from failures. I ask when AI expands people’s capabilities, when it creates additional work, and how people can stay in control.
I did my PhD in the Minnesota NLP group with Prof. Dongyeop Kang, co-advised by Prof. Jaideep Srivastava, and interned as a doctoral student at Microsoft Research and 3M R&D.
Understand people's goals, work contexts, and collaboration with AI to design assistance that fits their needs.
Characterize how language models reason and generate, and how inputs and steering shape their behavior.
Examine the benefits, burdens, and demands of AI use on people, with attention to oversight and meaningful control.
Each circle is one paper. Hover for details; click to open it.
CHI 2027, under submission
USERSIM at NeurIPS
TIIS
Journal of Institutional and Theoretical Economics
PaperProceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
PaperSecond Conference on Language Modeling (COLM)
PaperarXiv preprint arXiv:2401.14698
PaperFindings of the Association for Computational Linguistics: NAACL 2024
PaperFindings of the Association for Computational Linguistics: ACL 2023
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