Open House: Machine Learning for Materials Informatics

Virtual Open House for Machine Learning for Materials Informatics

Title: Open House: Machine Learning for Materials Informatics
Date: Thursday, May 9, 2024
Time: 12 PM EDT
Duration: 60 minutes
Instructor: Markus Buehler

Machine learning-assisted computational modeling and simulations are speeding the pace at which engineers are developing new materials. Intelligent materials design not only creates better and stronger materials but can do so more cost-efficiently and with a more sustainable usage of resources and unconventional materials. It is essential that engineers are familiar with the fundamentals of machine learning tools to keep pace with the advancements in materials science.

Machine Learning for Materials Informatics is a four-day, live virtual course taught by MIT Professor Markus J. Buehler. Participants will learn how to speed their design process and streamline prototyping in their organization, from the molecular to the macro level. Professor Buehler will introduce the foundations of materials informatics and lead a variety of labs using tools like Pytorch and Tensorflow. By the end of the course, learners will have the codes and templates they need to build their own AI platforms.

At this virtual open house, you will:

Meet Markus Buehler, Jerry McAfee (1940) Professor in Engineering; Professor of Civil and Environmental Engineering
Explore the learning outcomes, such as how to build predictive models, solve inverse design problems with AI, shape general-purpose models for materials applications, and more
Envision how this curriculum, the interactive labs, and the accomplished peers you network with over the four days can inspire new ways of approaching your work challenges
Ask your questions during a live Q&A session

Not able to make the live Open House?

Register today

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About the Faculty

Markus Buehler is the Jerry McAfee (1940) Professor in Engineering; Professor of Civil and Environmental Engineering. A frequent industry collaborator, his primary research interest lies in identifying and applying innovative approaches to design better materials from less, using a combination of high-performance computing and AI, new manufacturing techniques, and advanced experimental testing. He directs the Laboratory for Atomistic and Molecular Mechanics, and is principal investigator on numerous national and international research programs.

Why MIT Professional Education?

MIT Professional Education delivers timely, relevant programs to a global audience of scientists, engineers, technicians, managers, consultants, and others from industry, government, the military, non-profit, and academia. The MIT Professional Education mission is to provide a gateway to renowned MIT research, knowledge and expertise for those engaged in science and technology worldwide, through advanced education programs designed for working professionals. The programs are delivered by MIT faculty and promote technical excellence through ongoing educational engagement with communities of practice. Under the leadership of the School of Engineering, MIT Professional Education supports the development of creative leaders equipped to address complex problems.

For more information visit professional.mit.edu