MO-A4.1A: Optimization and Machine Learning
Mon, 14 Jul, 08:00 - 09:40
Location: Room 212
Session Type: Oral
Session Co-Chairs: Vikass Monebhurrun, CentraleSupélec and Agostino Monorchio, Università di Pisa
Track: AP-S: Computational and Analytical Techniques
Mon, 14 Jul, 08:00 - 08:20

MO-A4.1A.1: Physics-Constrained Neural Networks for Electromagnetic Surrogate Modelling
Niels Skovgaard Jensen, Frederik Faye, Lasse Hjuler Christiansen, Oscar Borries, Min Zhou, TICRA, Denmark; Erio Gandini, ESA-ESTEC, Denmark
Mon, 14 Jul, 08:20 - 08:40

MO-A4.1A.2: Smart Absorbing Material Positioning for Bistatic RCS Reduction: a Reinforcement Learning Approach
Edoardo Giusti, Pierpaolo Usai, Danilo Brizi, Agostino Monorchio, Università di Pisa, Italy
Mon, 14 Jul, 08:40 - 09:00

MO-A4.1A.3: Non-Parametric and Surrogate Model Assisted Optimization of Stacked Patch Antenna in CST Studio Suite
Md Khadimul Islam, Bidisha Barman, Enow Tanjong, Apra Pandey, Dassault Systemes, United States
Mon, 14 Jul, 09:00 - 09:20

MO-A4.1A.4: Novel application of GUM for uncertainty quantification in SAR simulations
Yiwen Zhang, Vikass Monebhurrun, CentraleSupélec, France
Mon, 14 Jul, 09:20 - 09:40

MO-A4.1A.5: Efficient Uncertainty Analysis for Printed Microstrip Antennas Using a Physics-Informed Deep Operator Network
Shutong Qi, Costas Sarris, University of Toronto, Canada