基本信息
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职业迁徙
个人简介
I am a fourth-year Ph.D. Candidate in Computer Science at Columbia University, advised by Prof. Luis Gravano and Prof. Daniel Hsu. My research interests lie at the intersection of Machine Learning, Information Extraction, and Natural Language Processing.
Currently, my research focuses on minimally-supervised learning frameworks for knowledge extraction from text, which can be applied in low-resource settings with limited or no labeled training data. I have been developing frameworks that leverage noisy labels and/or less expensive human supervision such as domain-specific keywords and rules. I have demonstrated the benefits of weak supervision across multiple text mining domains, languages, and tasks including knowledge graph construction, sentiment analysis, news document classification, topic extraction, cross-lingual learning, and mining social media for rare events related to public health.
Currently, my research focuses on minimally-supervised learning frameworks for knowledge extraction from text, which can be applied in low-resource settings with limited or no labeled training data. I have been developing frameworks that leverage noisy labels and/or less expensive human supervision such as domain-specific keywords and rules. I have demonstrated the benefits of weak supervision across multiple text mining domains, languages, and tasks including knowledge graph construction, sentiment analysis, news document classification, topic extraction, cross-lingual learning, and mining social media for rare events related to public health.
研究兴趣
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arxiv(2022)
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arXiv (Cornell University) (2021)
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SocialNLP@NAACLpp.36-60, (2021)
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (2020)
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