My Research and Passion

Seyed Sadjad Abedi-Shahri

Faculty of Engineering, University of Isfahan

About Me

  • 🎓 Background:
    • BSc in Mechanical Eng.
    • MSc and PhD in Biomedical Eng.
  • 💼 Current Position:
    • Assistant Professor of Biomedical Engineering

Research Interests

  1. Numerical Methods (FEM, SBFEM)
  2. Scientific Computing
  3. Computational (Bio)Mechanics
  4. Computational Geometry
  5. Machine Learning for Biomedical Applications

(go down to see details)

Numerical Methods (FEM)

  • Linear and Nonlinear Problems
  • Viscoelastic and Hyperelastic Materials
  • Impact Simulation
  • Buckling and Post-Buckling Analysis
  • Homogenization Techniques
  • Tools: ABAQUS, LS-DYNA, and Open-Source Solutions

Numerical Methods (SBFEM)

  • Developing formulation for specific problems
  • Linear and Nonlinear Problems
  • Viscoelastic and Hyperelastic Materials
  • Tools: In-house program for 2D Viscoelastic and Nonlinear Problems

Scientific Computing

  • Developing Research Software
  • Best Practices in Research Software Engineering (RSE)
  • Contribution to Open-Source Programs
  • Implementation in Fields of PDEs, Matrix Computations, etc.
  • Scientific Visualization
  • Tools: Python, Fortran, Octave/MATLAB

Computational (Bio)Mechanics

  • Nonlinear Solid Mechanics
  • Soft & Hard Tissue Biomechanics
  • Trauma Biomechanics
  • Image-Based Simulations
  • Impact Mechanics (Low & High velocity)
  • Fracture Mechanics
  • Topology Optimization
  • Inverse Problems

Computational Geometry

  • Mesh Generation and Optimization
  • Computational Topology in Meshing
  • Image-Based Mesh Generation
  • Delaunay and Voronoi-Based Methods

Machine Learning for Biomedical Applications

  • Data-driven Surrogate Models
  • Artificial Neural Networks for PDEs
  • Selected applications in Biomedical Image Processing

Some Examples of Projects

  1. SBFEM
  2. Head Impact
  3. pyPolyMesher
  4. QTREEMESH
  5. Bone Microcracks
  6. Composite Design Assistant(ComDA)
  7. Machine Learning for Biomedical Applications

(go down to see details)

Scaled Boundary Finite Element Method (SBFEM)

  1. A Scaled Boundary Finite Element Formulation for Solving Plane-Strain Viscoelastic Problems
  2. NL-SBFEM: A pure SBFEM formulation for geometrically and materially nonlinear problems

Head Trauma

pyPolyMesher

pyPolyMesher is a python package for generating unstructured polygonal meshes in arbitrarily defined 2D domains. It allows users to mathematically specify domains using signed distance functions (SDFs).

QTREEMESH

QTREEMESH is a python package that can create a Quadtree structure from an image. The Quadtree algorithm in this package is based on pixels’ intensity.

Bone Microcracks

  • Generation of bone RVE with random osteons and microcracks (using ABAQUS & python script) for homogenization problem

Composite Design Assistant(ComDA)

  • Composite Design Assistant(ComDA) is a scientific toolbox that provides a straightforward framework for industrial and academic analysis and design of composite structures.

Machine Learning for Biomedical Applications

  1. Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes Using Histological Microscopy Images
  2. Neural Network-Based Inverse Model for Non-Invasive Estimation of Corneal Mechanical Properties

Ongoing Projects

  • Finite Strain Viscoelasticty in SBFEM
  • Neural Network-Based Inverse Model for Cornea
  • DL in Pulmonary Vascular Histological Images

Collaboration & Contact

🤝 Open to research collaborations

📧 Email

🌐 Website

🔗 LinkedIn

👨‍💻 GitHub

Thank You! 🎤