The explosion of biomedical big data and information in the past decade created new opportunities for discoveries to improve the treatment and prevention of human diseases. But the large body of knowledge presents a grand new challenge. Individual scientists around the world are increasingly finding themselves overwhelmed by the sheer volume of research literature and are struggling to keep up to date and to make sense of this wealth of textual information.
Dr. Lu's research aims to break down this barrier and to empower scientists towards accelerated knowledge discovery. In this talk, Dr. Lu will present his work on developing large-scale, machine-learning based tools for better understanding scientific text in the biomedical literature. He will also demonstrate uses in real-world applications such as improving PubMed searches (Fiorini et al., Nature Biotechnology 2018), supporting precision medicine with LitVar (Allot et al., Nature Genetics 2023), and taming COVID-19 pandemic paper tsunami in LitCovid (Chen et al., Nature 2000).
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Presenter
Dr. Zhiyong Lu is a (tenured) Senior Investigator at the National Institutes of Health (NIH) Intramural Research Program, leading research in biomedical text and image processing, information retrieval, and AI/machine learning.
In his role as Deputy Director for Literature Search at National Center of Biotechnology Information (NCBI), Dr. Lu oversees the overall R&D efforts to improve literature search and information access in resources like PubMed and LitCovid, which are used by millions worldwide each day. With over 300 peer-reviewed publications, Dr. Lu is a highly cited author (an h-index over 70 with 30,000 citations) and a Fellow of the American College of Medical Informatics (ACMI). Additionally, Dr. Lu serves as an Associate Editor of Bioinformatics, and Organizer of the BioCreative NLP challenge. Over the last 15 years, Dr. Lu has mentored over 60 trainees, many of whom have gone on to become independent faculty members/researchers at academic institutions in the US, Europe, and Asia.