Carnegie Mellon University
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AI in Science

Mellon College of Science researchers are guiding pivotal turning points for artificial intelligence applications to foundational sciences. Through processing and analyzing big data, physicists are advancing our understanding of the universe while biologists use vision learning to enhance insights into the dynamics of biological processes. Chemists using large language models are transforming the field of computational chemistry at the same time as building foundational models for others to follow. The use of computer aided mathematical reasoning underpins the foundation of the future in uncertainty and stochastic problems. The Pittsburgh Computer Center enables these and others outside of CMU with a rich, unified environment for AI, machine learning and big data applications.

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Research Centers

NSF AI Planning Institute for Data-Driven Discovery in Physics

Physics applications of AI have led to some of the most exciting recent breakthroughs, from the synthesized radio imaging of the event horizon of a black hole (which used Machine Learning for image reconstruction) to explorations of the functioning of the human genome (Deep Learning for regulatory genomics and cellular imaging).

Pittsburgh Supercomputing Center AI & Big Data Group

PSC’s Artificial Intelligence and Big Data group converges AI and high performance computing capabilities, empowering research to grow beyond prevailing constraints. Experts provide consultation to address pressing scientific problems and accelerate discovery through harnessing the power of Bridges-2, PSC’s flagship supercomputer.

Pittsburgh Supercomputing Center’s Neocortex

The PSC’s Neocortex AI system is part of a pilot program to support novel and transformative AI research and education at a national scale. The National AI Research Resource (NAIRR) will use allocations software and procedures developed by PSC and others in the National Science Foundation-funded ACCESS project.

Pittsburgh Supercomputing Center’s Bridges-2

PSC's flagship HPC system that integrates new technologies for converged, scalable HPC, machine learning and data; prioritizes researcher productivity and ease of use; and provides an extensible architecture for interoperation with complementary data-intensive projects. A free resource for open research.

Carnegie Mellon University Cloud Lab

The Carnegie Mellon University Cloud Lab is based on the platform of the CMU-alumni founded Emerald Cloud Lab. The remote-controlled, automated lab will allow researchers and students from high schools, universities, industry and nonprofits to program experiments from anywhere in the world on more than 130 unique pieces of equipment.

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AI Courses in Science

For More Information

AI at CMU
Discover how interdisciplinary artificial intelligence research and education efforts at Carnegie Mellon University are shaping new frontiers and humanity. Learn more

MCS AI Academic Research Contact
Manfred Paulini, associate dean for research
paulini@jyycl.com
412-268-3887

MCS AI Corporate Research Contact
Ed Dunlea, senior director, Government and Corporate Relations
edunlea@andrew.jyycl.com
412-268-3207