Mark Dredze, the John C. Malone Associate Professor in the Department of Computer Science, is internationally recognized for mining big language data to pioneer new applications in public health informatics. One of the founders of this emerging field, he develops machine learning and natural language processing tools to gain insights from the web’s endless data to better understand human behavior and to inform public health policy and interventions.

His research is providing unprecedented insights on suicide prevention, vaccine refusal, HIV, tobacco, gun violence, and other public health issues. In 2017, he and Michael Paul, University of Colorado assistant professor of information science, co-authored “Social Monitoring for Public Health”—the first book surveying this nascent field.

Dredze develops new methods based on machine learning for a wide range of natural language processing tasks, including information extraction, semantics, speech processing, and topic modeling. He is especially interested in low-resource settings, such as domain adaptation or low-resource languages. Additionally, he is one of the leaders at Johns Hopkins University and Hospital in mining the free text found in clinical patient records to support patient care and discover population trends. He collaborates broadly with clinicians in the Johns Hopkins School of Medicine and the Bloomberg School of Public Health.

Dredze holds a secondary appointment in the Johns Hopkins University School of Medicine Department of Health Sciences Informatics and is a visiting professor at the Applied Physics Laboratory. His affiliations underscore his commitment to interdisciplinary cross-pollination: the Center for Language and Speech Processing; the Malone Center for Engineering in Healthcare; the Human Language Technology Center of Excellence; the Center for Population Health Information Technology; and the Institute for Global Tobacco Control. From 2015 to 2016, while on sabbatical, he explored the uses of social media in financial applications at Bloomberg LP. He has also spent time at Google Research, IBM Research, and Microsoft.

Among his awards are the “Best Paper Award” at the 2016 COLING Workshop on Noisy User-generated Text (W-NUT); CHI Honorable Mention Award 2016; Society of Behavioral Medicine Citation Award 2015; and an Altmetric Top 20 paper for 2018. With more than 200 publications, an h-index of 46 (46 papers with at least 46 citations), an i10-index of 127 (119 papers with ten citations), and more than 10,000 citations, Dredze has one of the most extensive publication records in his community at his level of seniority. He publishes in leading health journals, including the Journal of the American Medical Association and the American Journal of Preventative Medicine. His research on how social media activity influences offline behavior on public health matters has been profiled frequently in national media outlets, including NPR, The New York Times, The Washington Post, and CNN. In August 2017, he co-authored a paper with public health researcher John Ayers (University of California, San Diego) on increased interest in suicide following the Netflix show, “13 Reasons Why”, which was covered by nearly 1,000 media outlets from NBC and Reuters to Mashable and Forbes.

Dredze founded and served as faculty adviser of the Mid-Atlantic Student Colloquium on Speech, Language, and Learning (MASC) and is active in outreach to promote STEM diversity. Since 2010, he has coordinated the North American Computational Linguistics Olympiad (NACLO) and has participated in women in computer science programs at Johns Hopkins, the University of Pennsylvania, local high schools, IBM camps, and Microsoft’s DigiGirlz program.

He received a BS in Computer Science, BS in Computer Engineering, and Minor in Psychology from the Robert R. McCormick School of Engineering & Applied Science, Northwestern University (2003), an MA in Modern Jewish History, Bernard Revel Graduate School of Jewish Studies, Yeshiva University (2004), and a PhD in Computer Science from the School of Engineering and Applied Science, University of Pennsylvania (2009).