lab

members of the scienceNLP lab


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Janina Sarol


PhD student, Informatics

My research interest is in using text mining, natural language processing, and network analysis to develop tools that enhance the productivity of researchers.


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Lan Jiang


PhD student, Information Science

Research interests: natural language processing, machine learning, responsible AI

My research primarily focuses on natural language processing, with an emphasis on text assessments across various contexts, including education and biomedical domains. I am also interested in uncovering and eliminating bias in natural language processing to improve fairness.


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Mengfei Lan


PhD student, Information Science

My research interest lies in scientific literature processing and information extraction. Specifically, I am exploring how to apply cutting-edge natural language processing methods to extract important information from unstructured literature text. The extraction outcomes will improve the downstream tasks such as evidence synthesis.


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Shufan Ming


PhD student, Information Science

My research focuses on biomedical natural language processing, specifically by integrating external knowledge into large language models to enhance their performance in tasks such as relation extraction and automatic text summarization.


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Gibong Hong


PhD student, Information Science

Research interests: information extraction, LLM-based reasoning, biomedical NLP


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Evan Guerra


PhD student, Information Science

I am a second year PhD student interested in using NLP methods to further our understanding of smell and taste. I have worked on classification of taste language in Amazon food reviews, biomedical named entity recognition, and evaluating LLMs on smell taste and nutrition tasks.


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Joe Menke


PhD student, Information Science

My long-term research goal is to improve the efficacy and efficiency of biomedical research, largely through natural language processing (NLP) applications. My current work focuses on (1) improving reporting quality and transparency within randomized controlled trials and (2) effectively automating publication type and study design indexing for research articles.