AI-Accelerated Engineering for RF, Antennas and High-Frequency Electronics
ILKM explores the intersection of artificial intelligence, electromagnetic simulation and RF engineering to help engineers discover, evaluate and optimize high-performance antennas, RF circuits and high-frequency PCB structures.
Optimization Goal: Return Loss
28 GHz BandCandidate Geometry Generation
Microstrip PatchHigh-Frequency Design Is a Multi-Dimensional Optimization Problem
RF performance depends on tightly coupled variables including geometry, materials, frequency, substrate properties, impedance, bias conditions, thermal behavior, and manufacturing tolerances. Traditional optimization requires repeated full-wave EM simulations, resulting in painfully slow engineering iterations.
ILKM investigates hybrid workflows combining electromagnetic simulation, engineering constraints, and AI-based optimization to reduce the number of expensive design iterations while preserving physics-based verification.
Antenna Engineering
From simple microstrip patches to complex phased arrays and mmWave structures, exploring topologies for optimal S11, bandwidth, and radiation efficiency.
RF & Microwave Circuits
Optimizing matching networks, filters, power amplifiers, and passive structures for superior S-parameters, gain, and noise figure.
High-Frequency PCB
EM-aware layout optimization for controlled-impedance routing, via transitions, launch structures, and minimizing parasitic coupling.
The AI-Assisted Engineering Workflow
Integrating machine learning into standard electromagnetic engineering pipelines to augment design-space exploration.