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Ir. K.J. Cowan, MBA, is a Senior Lecturer and Education Fellow in the Astrodynamics & Space Missions section of the Faculty of Aerospace Engineering at Delft University of Technology. He serves as track coordinator for the Space Flight MSc track. Cowan earned his BSc from The University of Texas at Austin in the United States and his MSc in Aerospace Engineering from TU Delft. He also holds an MBA from Thunderbird School of Global Management. Prior to focusing on academia, he worked in strategic and financial advisory roles, including for the British government.
Cowan teaches MSc courses in Astrodynamics and emphasizes deep conceptual understanding over rote memorization in his pedagogical approach. His research focuses on space trajectories, optimization techniques, low-thrust interplanetary transfers, and applications of machine learning and neural networks to trajectory problems. He has co-authored peer-reviewed conference papers on topics such as global optimization of low-thrust trajectories using machine learning surrogates (2021), improving evolutionary optimization with neural network models (2021), rapid target-search techniques for KBO exploration (2021), unsupervised physics-informed neural networks for optimal transfers (2024), and open-source high-fidelity orbit estimation using Tudat software (2025). In 2017, he received the Aerospace Engineering Teacher of the Year award.
Explore the rapid rise in space engineering applications across European universities, driven by the Elon Musk effect and ESA missions. TU Delft sees 4,300 apps for 440 spots; Politecnico di Milano caps growth at 230 students.
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