Our lab’s Github page:
https://github.com/amir-cardiolab
Py4SciComp (Python for scientific computing):
Please visit Py4SciComp’s Github page for a series of tutorials (sample codes, data, and Youtube tutorials). In the future theoretical lectures supporting the tutorials will be also added.
Our Youtube channel:
https://www.youtube.com/channel/UCfCxgTGZAMaWbJhH11yg16g
Some of our conference talks, education material (e.g., Py4SciComp) are available on our Youtube channel. We have also created a youtube playlist of some select interesting webinars on Scientific Machine Learning (this playlist is occasionally updated).
Open Science Matters!:
We have created a comprehensive list of publicly available webinar series in various disciplines (machine learning, fluid/solid mechanics, computational modeling, biomechanics, applied math, etc.). Please check them out here and enjoy learning: Open Science Matters webpage.
Open-source/free software:
- SimVascular: A comprehensive software from medical image data to patient-specific blood flow simulation.
- Vascular Modeling Toolkit (VMTK): A collection of Python libraries for image-based modeling of blood vessels.
- FEniCS: A flexible finite element method (FEM) platform for solving arbitrary PDEs using a Python interface.
- The Visualization Toolkit (VTK): A collection of C++ libraries for visualization and post-processing of a wide range of data. VTK libraries are available in Python, providing powerful and efficient post-processing of different types of computational data.
- ParaView: A powerful VTK based visualization/post-processing software.
- VolView: Medical image data visualization.
- OpenFlipper: Processing mesh data.
- Meshmixer: Processing triangle surface mesh data.
- FreeCAD: Scriptable 3D CAD modeler.
- FlowVC: Lagrangian processing of velocity data. FTLE, particle residence time, particle tracking, ..
A short tutorial by Dr. Arzani on advanced vector field (velocity and WSS) visualization for creating figures for papers/presentations:
Useful online lectures:
- Linear Algebra (MIT, Dr. Gilbert Strang).
- Computational Science and Engineering 1 (MIT, Dr. Gilbert Strang).
- Computational Science and Engineering 2 (MIT, Dr. Gilbert Strang).
- Nonlinear Dynamics and Chaos (Cornell, Dr. Steven Strogatz).
- Nonlinear Dynamics and Chaos (Virginia Tech, Dr. Shane Ross).
- Finite Element Methods in Scientific Computing (Texas A&M, Dr. Wolfgang Bangerth).
- Nonlinear Finite Element for Solids and Structures (MIT, Dr. Klaus-Jürgen Bathe).
- Finite element methods for scientific computing (University of Colorado, Dr. Wolfgang Bangerth)
- Introduction to Computer Science and Programming in Python (MIT).
- Computational Fluid Dynamics (Boston University, Dr. Lorena Barba).
- Computational Fluid Dynamics (University of Florida, Dr. Miller).
- Classical Fluid Mechanics Lecture Series.
- Cardiovascular Fluid Mechanics (IIT Guwahati, Dr. Gupta).
- Data Driven Modeling, Fluid mechanics, and Dynamical Systems (University of Washington, Steve Brunton)
- Data Driven Modeling and Scientific Computation (University of Washington, Nathan Kutz)
- Machine learning (Stanford, Dr. Andrew Ng)
- Deep learning (NYU, Dr. LeCun & Dr. Canziani)
- Deep learning (Tübingen, Dr. Geiger)
- Foundations of deep learning: An ADVANCED course (University of Maryland, Dr. Soheil Feizi)
- Deep Learning in Scientific Computing (ETH)
Dr. Arzani’s course: