Sten Ponsioen
Senior Associate Director at MUFG Investor Services
About me
I am a Senior Associate Director in the Research & Data Science group at MUFG Investor Services. I am specialized in machine learning, deep learning, nonlinear dynamics and model reduction. I have 4+ years of experience working for Red Bull Racing, where I have developed and deployed state-of-the-art machine learning models that are used live during F1 races, using model predictions to make informed, strategic and race winning decisions. My academic background includes a Ph.D. in Applied Mathematics obtained from ETH Zürich, and I obtained my B.Sc. and M.Sc. in Mechanical Engineering from Delft University of Technology. If you would like to reach out, feel free to email me or to contact me through the contact page .
Experience
Senior Associate Director
MUFG Investor Services
- Jan. 2024 – Present
- London, United Kingdom
Senior Data Scientist
Red Bull Racing & Red Bull Technology
- Jul. 2022 – Dec. 2023
- Milton Keynes, United Kingdom
- 2023 Drivers’ & Constructors’ World Champion
- 2022 Drivers’ & Constructors’ World Champion
Simulation and Analysis Engineer
Red Bull Racing & Red Bull Technology
- Jul. 2019 – Jun. 2022
- Milton Keynes, United Kingdom
- 2021 Drivers’ World Champion
Research Assistant / Doctoral Candidate
ETH Zürich
- Jan. 2016 – Jun. 2019
- Zürich, Switzerland
Education
- Ph.D. in Applied Mathematics, 2019, ETH Zürich
- M.Sc. in Mechanical Engineering, 2015, Delft University of Technology
- B.Sc. in Mechanical Engineering, 2012, Delft University of Technology
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Ponsioen, S., Jain, S., & Haller, G. (2020). Model reduction to spectral submanifolds and forced-response calculation in high-dimensional mechanical systems. Journal of Sound Vibration, 488, 115640.
Journal
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Veraszto, Z., Ponsioen, S., & Haller, G. (2020). Explicit third-order model reduction formulas for general nonlinear mechanical systems. Journal of Sound and Vibration, 468, 115039.
Journal arXiv
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Ponsioen, S., Pedergnana, T., & Haller, G. (2019). Analytic Prediction of Isolated Forced Response Curves from Spectral Submanifolds. Nonlinear Dynamics, 98(4), 2755–2773.
Journal arXiv
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Ponsioen, S., Pedergnana, T., & Haller, G. (2018). Automated computation of autonomous spectral submanifolds for nonlinear modal analysis. Journal of Sound and Vibration, 420, 269–295.
Journal arXiv
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Haller, G., & Ponsioen, S. (2017). Exact model reduction by a slow–fast decomposition of nonlinear mechanical systems. Nonlinear Dynamics, 90(1), 617–647.
Journal arXiv
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Haller, G., & Ponsioen, S. (2016). Nonlinear normal modes and spectral submanifolds: existence, uniqueness and use in model reduction. Nonlinear Dyn., 86(3), 1493–1534.
Journal arXiv
Conferences
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- Presented
- Attended
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Thirty-sixth Conference on Neural Information Processing Systems.
🇺🇸 Nov. 2022, New Orleans, USA.
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Isolated Forced Response Curves from Non-Autonomous Spectral Submanifolds, Fourth International Conference on Recent Advances in Nonlinear Mechanics.
🇵🇱 May 2019, Lodz, Poland.
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Analytic Prediction of Isolated Forced Response Curves from Spectral Submanifolds, The First International Nonlinear Dynamics Conference.
🇮🇹 Feb. 2019, Rome, Italy.
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Detection of Isolated Forced Response Curves using Non-Autonomous Spectral Submanifolds, 37th International Modal Analysis Conference.
🇺🇸 Jan. 2019, Orlando, USA.
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Automated Computation of Autonomous Spectral Submanifolds for Nonlinear Modal Analysis, IUTAM Symposium on Exploiting nonlinear dynamics for engineering systems.
🇷🇸 Jul. 2018, Novi Sad, Serbia.
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Automated Computation of Spectral Submanifolds for Nonlinear Modal Analysis, 36th International Modal Analysis Conference.
🇺🇸 Feb. 2018, Orlando, USA.
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Applications of Spectral Submanifolds in Nonlinear Modal Analysis, 9th European Nonlinear Dynamics Conference.
🇭🇺 Jun. 2017, Budapest, Hungary.
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Applications of Spectral Submanifolds in Nonlinear Modal Analysis, 35th International Modal Analysis Conference.
🇺🇸 Jan. 2017, Los Angeles, USA.