Niels Skovgaard Jensen, TICRA
Simulations have become a fundamental aspect of nearly every engineering and physical science discipline. While large language models (LLMs) and generative AI are transforming our interactions with text and multimedia, a less visible revolution is occurring within simulation software. Here, Scientific Machine Learning (SciML) is poised to have a profound impact on how we simulate, design, and understand the world around us.
Based in Copenhagen, TICRA’s antenna simulation software products are trusted globally as the reference standard for antenna design and development. These tools rely on state-of-the-art numerical simulations and optimisation methods. Over the past five years, we at TICRA have increasingly invested in developing scientific machine learning techniques to accelerate simulation speeds and enhance the usability of our design tools for our customers.
In this talk, Niels will discuss the future of SciML in simulation software, drawing on lessons learned at TICRA and exploring the directions that TICRA and the broader industry are taking. The talk will provide a glimpse of a future where ML can accelerate simulations and model the currently infeasible, resulting in better engineering designs and offering us another tool for tackling our most complex engineering and science challenges.
Bio:
Niels Skovgaard Jensen is a machine learning engineer and industrial Ph.D. candidate at TICRA, a Copenhagen-based company specializing in electromagnetic simulation software. While at TICRA, he has worked on several scientific machine learning projects in collaboration with the European Space Agency. Currently, as an industrial Ph.D. candidate, he is researching complex-valued machine learning models to accelerate computations in antenna design and electromagnetics.
