Physics-Informed Neural Networks (PINNs)

Aim

Workshop Structure

📘 Day 1 — Foundations of PINNs and Basic Implementation

• Focus: Understanding the fundamentals of Physics-Informed Neural Networks (PINNs) and implementing a basic model
• Key Topics:
  • Introduction to Scientific Machine Learning and the limitations of data-only models
  • Physics-Informed Neural Networks (PINNs): concept, motivation, and architecture
  • Governing equations: ODEs, PDEs, boundary conditions, and initial conditions
  • Loss formulation: data loss and physics residual loss
  • Training workflow and optimization challenges
• Hands-on (Google Colab):
  • Task: Build a simple neural network in Python, solve a basic ODE using PINNs, and compare predicted results with the analytical solution

⚙️ Day 2 — Solving PDEs and Advanced PINN Techniques

• Focus: Extending PINNs to partial differential equations and improving model convergence
• Key Topics:
  • Extending PINNs from ODEs to PDE problems
  • Automatic differentiation for computing derivatives
  • Applying boundary and initial conditions effectively
  • Training stability, convergence issues, and scaling strategies
  • Introduction to inverse problems
• Hands-on (Google Colab):
  • Task: Implement a PINN to solve a simple PDE, apply boundary conditions, compute residual errors, and analyze training behavior

🌐 Day 3 — Inverse Problems, Parameter Estimation, and Applications

• Focus: Applying PINNs to inverse problems, sparse-data learning, and real-world scientific applications
• Key Topics:
  • Parameter estimation and inverse problems using PINNs
  • Data-efficient learning with sparse measurements
  • Applications in engineering, fluid mechanics, materials, and physics
  • Model validation and physical consistency checks
  • Limitations and future directions of PINNs
• Hands-on (Google Colab):
  • Task: Estimate an unknown parameter in a differential equation, train a PINN with limited synthetic data, and evaluate prediction accuracy

Who Should Enrol?

Important Dates

Workshop Outcomes

Fee Structure

What You’ll Gain