David Cereceda

ALT Machine Learning for Materials Informatics Learn more here: https://professional.mit.edu/course-catalog/machine-learning-materials-informatics With the success of effective and generalizable deep learning tools, the materials community is primed to take advantage of unprecedented breakthroughs, leveraging materials modeling, analysis, and design toward a more efficient, less costly, and more versatile response to market demands and opportunities. Tap into your existing data and develop an actionable vision for incorporating material informatics into your organization’s current strategies for developing technologies, services and increased revenue. Moreover, with data available from autonomous experimentation or large databases like the Materials Project within the Materials Genome initiative, there exist many opportunities to accelerate and expand your materials design platform.