Xinyi Wang
Princeton, New Jersey, United States
Summary
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SeniorXinyi Wang is a postdoctoral researcher at Princeton University with eight years of experience studying pretraining and reasoning behaviors of large language models. She earned a PhD in Computer Science from UC Santa Barbara, where her work dissected in-context learning, reasoning, and memorization phenomena in LMs. Xinyi has industry research experience from internships at IBM and Microsoft, focusing on how pretraining data and novel prompting mechanisms (e.g., planning tokens) affect chain-of-thought reasoning. Based in New Jersey, she blends rigorous theoretical study with practical experimentation to improve model capabilities and robustness. Notably, her background in both applied mathematics and CS across UCLA, HKUST, and UCSB underpins a quantitative approach to probing model behavior that favors interpretable, data-driven interventions.
8 years of coding experience
Github Skills (10)
algorithms5
prompting5
machine-learning4
large-language-models4
deep-learning3
topic-models3
language-model2
inference2
pytorch1
encoder1
Programming languages (3)
Github contributions (5)
WANGXinyiLinda/WANGXinyiLinda.github.io
Nov 2019 - Feb 2022
:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.
Contributions:80 pushes, 2 branches in 2 years 3 months
blog-siterulerblog-projectjekylljekyll-theme
WANGXinyiLinda/adaptive-count-ception
May 2019 - Sep 2019
Contributions:5 commits, 3 pushes, 1 branch in 4 months
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