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Mark Dredze, M.A., Ph.D.
Joint Appointment in Health Sciences Informatics
Research Interests: Health informatics; Natural language processing; Machine learning; Social media
Dr. Mark Dredze is an assistant research professor of computer science at Johns Hopkins University and a research scientist at the Human Language Technology Center of Excellence. His research focuses on machine learning, natural language processing, speech, intelligent user interfaces and health informatics.
His recent work includes health information applications, including information extraction from social media, biomedical and clinical texts.
Dr. Dredze received his undergraduate degree from Northwestern University. He earned his master's degree from Yeshiva University and his Ph.D. from the University of Pennsylvania.
- Joint Appointment in Health Sciences Informatics
Departments / Divisions
- B.S., Northwestern University (Illinois) (2003)
- M.A., Yeshiva University (New York) (2004)
- Ph.D., University of Pennsylvania (Pennsylvania) (2009)
Research & Publications
Dr. Dredze’s research in natural language processing and machine learning has focused on graphical models, semi-supervised learning, information extraction, large-scale learning and speech processing.
Peng, Nanyun, Mark Dredze. "Learning word segmentation representations to improve named entity recognition for Chinese social media." Association for Computational Linguistics (ACL). 2016.
Benton, Adrian, Raman Arora, Mark Dredze. "Learning multiview embeddings of Twitter users." Association for Computational Linguistics (ACL). 2016.
Broniatowski, David Andre, Mark Dredze, Karen M Hilyard. "Effective vaccine communication during the Disneyland measles outbreak." Vaccine. 2016.
Gao, Ning, Mark Dredze, Douglas Oard. "Knowledge base population for organization in emails." NAACL Workshop on Automated Knowledge Base Construction (AKBC). 2016.
Smith, Michael, David A. Broniatowski, Mark Dredze. "Using Twitter to examine social rationales for vaccine refusal." International Engineering Systems Symposium (CESUN). 2016.