MICDE’s depth and breadth of innovation in computational science is reflected in our affiliated faculty’s discoveries, groundbreaking ideas and achievements. Our research centers highlight new tools and methodologies being develop at U-M to accelerate and expand scientific discovery.

Research Centers

Climate visualization

Center for Data-Driven Computational Physics

Modeling of Multi-scale Physical Systems

The mission of the Center for Data-Driven Computational Physics is to usher in the future of large-scale, data-driven modeling of multi-scale physical systems. We focus on data-driven solutions to these problems using high performance computing clusters. However, the interaction of high performance computing for physics with large-scale data is itself a challenging problem, meriting new hardware configurations, software, and computational methods. The Center will respond to this challenge via the ConFlux facility, conceived by MICDE faculty and hosted by ARC-TS.

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Center for Network and Storage-Enabled Collaborative Computational Science

Improving collaboration on large datasets

The  Center for Network and Storage-Enabled Collaborative Computational Science seeks to address the challenges of extracting scientific results collaboratively from large, distributed or diverse data. Included in the Center is the NSF-funded OSiRIS project, a collaborative, multi-university venture led by MICDE faculty, and hosted by ARC-TS.

Highlights

2016-2017 MICDE Research Snapshot

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2016-2017 has been a year of sustained growth for MICDE's research portfolio. The number of faculty affiliated with the institute stands at 130, spanning 30 departments and eight schools and…

U-M fosters thriving artificial intelligence and machine learning research

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Research using machine learning and artificial intelligence — tools that allow computers to learn about and predict outcomes from massive datasets — has been booming at the University of Michigan.…

The University of Michigan is live on IBM.com

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IBM is showcasing the current research developed with ConFlux, our ground-breaking cluster that uses IBM's HPC and storage technology to enable scientists to draw on huge volumes of bid data and use machine learning…

U-M joins NSF-funded SLATE project to simplify scientific collaboration on a massive scale

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From the Cosmic Frontier to CERN, New Platform Stitches Together Global Science Efforts SLATE will enable creation of new platforms for collaborative science Today’s most ambitious scientific quests -- from…