MIDAS advances cross-cutting research in data science theory, methodology and applications, and its positive impact on our society. We offer research funding, facilitate ideas development, foster collaboration, enable access to important datasets, and provide grant proposal support. Please also visit our Research Accomplishments page.

RESEARCH HUBS

SUPPORT FOR DATA SCIENTISTS

FOSTERING RESEARCH IDEAS AND TEAMS

MIDAS facilitates research idea development and collaboration through formal and informal interactions with U-M data scientists. We help researchers identify collaborators. We also organize research working groups for faculty and research staff based on research themes and funding opportunities. The themes cut across traditional disciplines and foster interaction between theorists and application scientists. We encourage researchers to work with MIDAS to start working groups or mini-workshops.
FUNDING

MIDAS research funding supports high-impact and innovative research in data science theory, methodology, applications in all research domains, and encourages research with significant and positive societal impact. During Phase I of funding support (2015-2018), the MIDAS Challenge Initiative provided $10 million funding for projects in data-intensive transportation research, health science, social science, and learning analytics. MIDAS also funds the Data Science for Music research program. The first round of pilot funding, Propelling Original Data Science (PODS), was launched in 2019 and supports 15 projects in a diverse range of application domains.
GRANT SUPPORT PROGRAM

MIDAS provides support for U-M investigators to improve the data science component of grant proposals in many different ways, ranging from a simple description of MIDAS facilities and resources to substantial collaborative research.
DISCUSSION BOARD

Our first discussion board, “Data Science Methods in Python”, is open to all University of Michigan members and welcomes questions at all levels. Users of the group as well as consultants at CSCAR will respond to questions. Questions not addressed here can be addressed through in-person consultation sessions with CSCAR.
RESEARCH DATASETS

MIDAS manages and promotes the use of large datasets that could be of value to many U-M data scientists.