The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research, from […]
Active Learning for Physics Informed Data Sampling and Construction of Free Energy Representations
When Is Big Data Biased?
Computational Methods in Chemistry
This event is the first of its kind, dedicated to scientific foundation models (SciFM), that are set to revolutionize science in the same way Generative AI has transformed natural language. This two-day conference will bring together some of the most renowned experts from the field of scientific foundation models who will share their insights and […]
This event is the first of its kind, dedicated to scientific foundation models (SciFM), that are set to revolutionize science in the same way Generative AI has transformed natural language. This two-day conference will bring together some of the most renowned experts from the field of scientific foundation models who will share their insights and […]
Applications for the $4,500 2024-2025 MICDE Graduate Fellowships will open May 1, 2024. Please join this Zoom session to learn more about the fellowships and how to submit a great application!
The educational programs represented are: PhD in Scientific Computing (MICDE) Graduate Certificate in Computational Discovery & Engineering (MICDE) Graduate Certificate in Computational Neuroscience (MICDE) Graduate Certificate in Data Science (MIDAS) These programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range […]
The educational programs represented are: PhD in Scientific Computing (MICDE) Graduate Certificate in Computational Discovery & Engineering (MICDE) Graduate Certificate in Computational Neuroscience (MICDE) Graduate Certificate in Data Science (MIDAS) These programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range […]
Zoom link Abstract: Simulating complex physical systems often requires joining non-uniform subsystems, which may be characterized by different geometries or mesh topologies. Coupling these separate subsystems often relies on time-intensive meshing workflows or empirical coupling models, which may not generalize well across all operational regimes. The Schwarz alternating method proposes to overcome these issues, establishing […]