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Multiscale Modeling of Materials and Machine Learning Laboratory (M4L Lab)


To provide insights and enrich the theoretical and experimental knowledge of the Materials by Design paradigm.

Research Overview

Understanding and predicting the mechanical response of advanced materials subjected to extreme environments is critical from both scientific and engineering viewpoints. In particular, discovering, manufacturing and deploying these advanced materials in a shorter time and at a reduced cost are active challenges that require a multidisciplinary approach where experimental tools, computational tools and digital data must be effectively integrated.

The Multiscale Modeling of Materials and Machine Learning Lab focuses on creating and validating computational models to predict materials behavior across multiple spatial and temporal scales, with special interest in studying material behavior under extreme environments and the potential of machine learning for these applications.


The M4L Lab is equipped with ERG-HPC: Engineering Research Group, High Performance Computing.

Principal Investigator

David Cecera, Ph.D.

Dr. David Cereceda
Assistant Professor, Mechanical Engineering 
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