M.A. (Miguel) Bessa PhD
M.A. (Miguel) Bessa PhD
Contact
Profile
Biography
Miguel's research involves understanding and modeling materials at every scale in a unique experimentally-validated and self-consistent computational framework. He envisions a new era of data-driven design of materials and structures based on Physics-informed machine learning, reduced order models and genetic optimization. Miguel feels very fortunate to have worked with outstanding colleagues and mentors throughout his career, from the first steps at the University of Porto (1st ranked in the entire Department) to the doctoral work at Northwestern University (Fulbright scholar; 4.0 GPA) and the postdoctoral work at the California Institute of Technology. At the TU Delft he intends to apply the computational methods he continuously creates and develops with the hope that they will bring tangible benefits to Engineering and Applied Science.
Expertise
Publications
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2024
Centimeter-scale nanomechanical resonators with low dissipation
Andrea Cupertino / Dongil Shin / Leo Guo / Peter G. Steeneken / Miguel A. Bessa / Richard A. Norte
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2024
Continual learning for surface defect segmentation by subnetwork creation and selection
Aleksandr Dekhovich / Miguel A. Bessa
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2024
Neural network relief: a pruning algorithm based on neural activity
Aleksandr Dekhovich / David M.J. Tax / Marcel H.F. Sluiter / Miguel A. Bessa
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2024
Ultralight Membrane Structures Toward a Sustainable Environment
Alessandro Comitti / Harikrishnan Vijayakumaran / Mohammad Hosein Nejabatmeimandi / Luis Seixas / Adrian Cabello / Diego Misseroni / Massimo Penasa / Christoph Paech / Miguel Bessa / More Authors
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2024
iPINNs: incremental learning for Physics-informed neural networks
Aleksandr Dekhovich / Marcel H.F. Sluiter / David M.J. Tax / Miguel A. Bessa
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Courses 2022
Courses 2021
Media
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2019-10-15
Bicycles, dinner tables & umbrellas could soon become pocket-sized
Appeared in: TweakTown