Hossein holds both a Bachelor’s and a Master’s degree in Mechanical Engineering from the Iran University of Science and Technology, where his thesis centered on the experimental, numerical, and analytical investigation of fracture in stainless steel. With a strong foundation in machine learning, optimization techniques, and additive manufacturing, he has developed data-driven and probabilistic physics-based neural networks for fracture and fatigue life prediction. His recent work includes the application of advanced constrained Bayesian optimization for the inverse design of metamaterials. Currently pursuing his PhD at OrthoSens and EPFL, Hossein is focused on designing innovative auxetic metamaterials for spinal implants, with the objective of replicating the natural material properties of the intervertebral disk.
Project objectives
- Create novel auxetic MM designs via FEM simulation, exploring a range of different mechanical properties to mimic natural material properties of intervertebral disks
- Integrate promising MM designs into spinal implants accounting for manufacturing and medical regulatory constraints
- Produce and perform testing on specimen to validate the implant design
- Understand the potential of AI to fine-tuning spinal auxetic MM devices’ properties
Supervision and secondments
Hosted at
OrthoSens SA, Courroux, Switzerland
Supervisors
Mr. Gwenael Hennema
Academic supervisor: Prof. Romain Fleury (EPFL)
PhD enrolment
EPFL, Ph.D. in Electrical Engineering, Lousanne, Switzerland
Secondments
CNRS, UNICAL, IMP-PAN