Augmenting End-to-End Electromagnetic Simulation with AI/ML: From Physics to Prediction

Overview

Electromagnetic simulation is rapidly evolving with the integration of Artificial Intelligence (AI) and Machine Learning (ML), enabling engineers to move beyond conventional physics-only workflows toward faster, more adaptive, and data-driven design approaches. By combining high-fidelity simulation with AI-assisted models, organizations can accelerate product development while improving design accuracy and engineering efficiency. In this webinar, we will explore how AI/ML can be integrated into electromagnetic simulation workflows within the Ansys ecosystem. The session will demonstrate how data-driven models and surrogate techniques can complement physics-based solvers to accelerate design validation, optimize performance, and enable predictive insights across complex electromagnetic applications.

Who Should Attend

• Antenna Designers
• EM Engineers
• EMI/EMC Engineers
• Signal Integrity (SI) Engineers
• Product Development Engineers
• R&D Engineers / Research Scientists
• Data Scientists working in engineering domains
• Engineering Managers and Technical Leads

Focused Industries

Key Highlights

• How AI/ML models can augment physics-based simulation methods
• Techniques for building surrogate models for faster prediction
• Workflow for integrating simulation data with AI/ML tools
• Methods to improve design optimization and reduce simulation time
• Applications of AI/ML in EMC, signal integrity, and system-level analysis