Public Biography
Dr. Li stands at the forefront of medical informatics research, with a professional journey spanning over 15 years. Her expertise lies in data mining, machine learning, and natural language processing, focusing on their practical applications in addressing significant healthcare-related challenges. Dr. Li specializes in extracting, integrating, and transforming both structured and unstructured into valuable and actionable insights. These data sources encompass real-world instances such as electronic health records (EHRs), claims databases, literature, social media platforms, the internet, and internally generated data from corporations.
After obtaining her PhD in Biomedical Informatics from Columbia University, she served at IBM Research in the Center for Computational Health for five years. During her tenure, she played a pivotal role as a research staff member, spearheading the Watson for Patient Safety research prototype.
In recent years, Dr. Li has been serving as a Director of Health Economics and Outcome Research at Regeneron Pharmaceuticals. Her work primarily centers on using real-world data, literature and trial registries to address a variety of business needs within the comprehensive drug development process.
After obtaining her PhD in Biomedical Informatics from Columbia University, she served at IBM Research in the Center for Computational Health for five years. During her tenure, she played a pivotal role as a research staff member, spearheading the Watson for Patient Safety research prototype.
In recent years, Dr. Li has been serving as a Director of Health Economics and Outcome Research at Regeneron Pharmaceuticals. Her work primarily centers on using real-world data, literature and trial registries to address a variety of business needs within the comprehensive drug development process.
Affiliations
Knowledge Discovery and Data Mining
Working Group
Past Chair 2025
Knowledge Discovery and Data Mining focuses on the process of extracting meaningful patterns from biomedical data (knowledge discovery), using automated computational and statistical tools and techniques on large datasets (data mining).
Learn more about this group
Fellows of AMIA (FAMIA)
FAMIA stands for “Fellow of the American Medical Informatics Association” and it recognizes the contributions and professional accomplishments of AMIA members who apply informatics skills and knowledge to their practice – be that in a clinical setting, a public or population health capacity, or as a clinical researcher.
Year Inducted
2023