Miguel A. Bessa Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Associate Professor

John Brown University

faculty

21 h-index 90 pubs 3,315 cited

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Biography and Research Information

OverviewAI-generated summary

Dr. Miguel Bessa envisions a new paradigm for material and structural design through the application of artificial intelligence. After earning his PhD in Mechanical Engineering from Northwestern University in 2016 and postdoctoral work at Caltech, he rapidly advanced to Associate Professor at Delft University of Technology before joining Brown University's Solid Mechanics Group. Bessa's research encompasses the mechanical behavior of composites, mechanical and optical resonators, and numerical methods in engineering, including topology optimization. His work includes the development of machine learning methodologies for composite laminate design. He also explores the application of machine learning to quantify nanoscale forces in dynamic atomic force microscopy, and the use of Bayesian optimization for metamaterial design.

Metrics

  • h-index: 21
  • Publications: 90
  • Citations: 3,315

Selected Publications

  • Multi-Objective Bayesian Optimisation of Spinodoid Cellular Structures for Crush Energy Absorption (2024) DOI
  • f3dasm: Framework for Data-Driven Design and Analysisof Structures and Materials (2024) DOI
  • Data and code for "Centimeter-scale nanomechanical resonators with low dissipation" (2024) DOI
  • Data and code for "Centimeter-scale nanomechanical resonators with low dissipation" (2024) DOI
  • Bayesian optimisation of hexagonal honeycomb metamaterial (2023) DOI
  • CRATE: A Python package to perform fast materialsimulations (2023) DOI

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