Adam Szypula

An engineer with over eight years of experience across both industrial and academic environments, specializing in Machine Learning, Deep Learning, and modern AI techniques for advanced engineering applications. His work focuses on leveraging computational intelligence to optimize and design next‑generation electric powertrains, with a particular emphasis on Noise, Vibration and Harshness (NVH) performance.
In his current role Adam applies modeFRONTIER to conduct a wide range of multi‑objective and multidisciplinary optimization studies for electric motors. His work involves balancing competing design requirements and pushing optimization workflows to their practical limits, enabling more efficient, robust, and high‑performance solutions for e‑machine designs.
Prior to his current position, Adam worked at the University of Warwick on several R&D programmes involving electric machine testing, battery characterization, and the development of experimental methodologies. This experience provided a strong foundation in measurement, validation, and system‑level understanding—expertise that continues to inform his data‑driven approach to engineering optimization.