Population Health Data Science Program.
About Us
The overarching goal of the Population Health Data Science (PHDS) Program is to advance the development and quality of data science research in population health. We seek to foster new collaborations between researchers across multiple scientific disciplines, provide community members with resources and opportunities for training in data science, and generate new insights to improve population health.
Seminars and Workshops
We convene and promote seminars and workshops aimed at increasing population health data science literacy and knowledge. Topics include: Machine Learning, Artificial Intelligence, Natural Language Processing, Data Visualization Techniques, Wearable Medical Technology, Deep Learning, Medical Imaging Analysis, Data Management and Reproducible Research.
Student and Trainee Engagement
The PHDS Program engages students and trainees in population health data science research by serving as a bridge to potential data science faculty mentors for mentored projects and internships.
Support for Early-Career Faculty
We host research-in-progress seminars to support the development of data science research in population health, particularly for junior faculty who wish to pursue grant funding and lead manuscripts.
Seed Funding Opportunities
The PHDS Program provides flexible seed funding for population health data science projects to help position faculty to be more competitive when applying for external funding. The goal is to catalyze a broad range of novel data science research, e.g. data-driven collaborative research studies, methodological research, development of new tools to address big data analytics, etc.
Our People
Director
Associate Director
Advisory Board
Faculty Affiliates
The PHDS Program includes faculty affiliates from across Boston University including the School of Public Health, Chobanian & Avedisian School of Medicine, Goldman School of Dental Medicine, College of Arts and Science, College of Engineering, and the Hariri Institute for Computing. PHDS affiliated faculty have a wide range of expertise in data science including machine learning, artificial intelligence, data visualization techniques, deep learning, and reproducible research.
Industry Affiliates
The PHDS Program has partners from industry who are actively working in health data science. Industry affiliates enhance our program by sharing scientific questions and challenges they are confronting in industry and providing new opportunities for collaboration with our community. In addition, our industry affiliates may serve as mentors to students, providing training opportunities through mentored projects and internships.
If you are BU faculty interested in becoming a PHDS Faculty Affiliate, please complete this brief form. We welcome all members of the BU Community (including students, postdocs, research associates, and research scientists) to participate in our program activities. If you would like to be included on our email distribution list announcing upcoming events, please complete this brief form.
The Health Data Science Distinguished Speaker Series
June 1, 2023
12-1pm EST
Hiebert Lounge & Zoom
What is Data Science?
Rafael Irizarry
Chair, Department of Data Sciences
Dana-Farber Cancer Institute
Professor of Biostatistics
Harvard T.H. Chan School of Public Health
September 21, 2023
12-1pm EST
Hiebert Lounge & Zoom
Register here
Principles for Designing Complex Data Analyses
Roger Peng
Professor of Statistics and Data Sciences
University of Texas, Austin
October 17, 2023
2-3PM EST
Hiebert Lounge & Zoom
AI & Population Health
Isaac Kohane
Founding Chair, Department of Biomedical Informatics
Harvard Medical School
Inaugural Editor-in-Chief, NEJM AI
November 2, 2023
12-1PM EST
Hiebert Lounge & Zoom
Machine Learning in Population Health: Challenges & Opportunities
Rumi Chunara
Associate Professor of Biostatistics
Director, Center for Health Data Science
New York University
January 24, 2024
12-1pm EST
BUMC (ROOM TBD) & Zoom
Ethics & Data Science
Suresh Venkatasubramanian
Professor of Data Science and Computer Science
Brown University
Former Advisor, White House Office of Science & Technology Policy
February 15, 2024
12-1PM EST
BUMC (ROOM TBD) & Zoom
Toward a Taxonomy of Trust in Data Science Methods
Tamara Broderick
Associate Professor
Department of Electrical Engineering & Computer Science
Massachusetts Institute of Technology
March 7, 2024
12-1PM EST
BUMC (ROOM TBD) & Zoom
Data Visualization for Inference: Opportunities & Challenges
Jessica Hullman
Ginni Rometty Associate Professor
Computer Science
Northwestern University
This Health Data Science Distinguished Speaker Series is co-sponsored by the BUSPH Population Health Data Science Program, the Hariri Institute for Computing, the BUSPH Department of Biostatistics, and the Providence/Boston Center for AIDS Research (CFAR).