Overview

Research activities in 5 interconnected “pillars”

MIDAS focuses on five pillars, described below, within its overall effort to support data science and Artificial Intelligence (AI) research. Across these pillars, MIDAS promotes responsible research practices, supports the adoption of new data types and methodologies, and facilitates convergence science. The pillars will change over time: current pillars will be retired or shift focus, and new pillars established.  Furthermore, these pillars are interconnected where possible, to maximize the synergies between them and leverage the interdisciplinary MIDAS community and the collaborative spirit U-M is known for.

In addition to supporting research within the pillars, MIDAS fosters connections and collaborations in data science and AI for the entire University, maintains a large umbrella covering all relevant research areas, and supports an inclusive community of researchers.  MIDAS also continues to promote cutting-edge methodological development as the foundation for data science and AI.

For more information or to participate in any of the activities, contact: midas-contact@umich.edu

Pillars

Responsible Research Pillar

MIDAS collaborates with our researchers to develop foundational principles, developing methodology and tools, and deploying such tools for the ethical use of data and algorithms.

Data Pillar

MIDAS supports the development and use of data science and AI methods to better understand society through new data types such as text, video, sensor and digital trace data. 

Analytics Pillar

MIDAS collaborates with campus partners to enable the adoption of cutting-edge analytics and modeling of complex data to boost U-M’s biomedical and healthcare research.

AI Pillar

MIDAS catalyzes creative and transformative applications of AI with the potential to lead to major scientific breakthroughs across a range of science and engineering domains.

Emerging Pillar

MIDAS pursues team activities in strategic research areas that have the potential to grow into pillars.