Charlotte Geier, MSc

Bio: Charlotte received her Master of Science in Theoretical Mechanical Engineering in 2021 from Hamburg University of Technology (TUHH) after completing her Bachelor of Science in General Engineering Science in 2017. During her studies, she spent two semesters abroad: She visited the INSA Toulouse (France) for the summer term of 2016 during her BSc. and the University of Waterloo (Canada) for a trimester in 2018 while pursuing her Masters Degree. In 2021, she joined the Dynamics Group as a research associate. In her free time, Charlotte enjoys exploring the "great outdoors" via sailing, hiking, climbing or simply the own garden.

Research: Charlottes research interests include nonlinear dynamics, complex networks, physics-informed machine learning and data-driven system identification of nonlinear dynamical systems. Her current research activities focus on complex network approaches as a novel perspective on nonlinear engineering vibrations. Previous research includes physics-informed machine learning applications for friction-excited systems.

Collaborations and student projects: Charlotte is happy to collaborate on projects regarding complex networks and nonlinear dynamics! Interested students can contact her via Email.

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ORCID

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ResearchGate

TUHH Tore

Geier, C., Hamdi, S., Chancelier, T., Dufrénoy, P., Hoffmann, N., Stender, M.: Machine learning-based state maps for complex dynamical systems: applications to friction-excited brake system vibrations. Nonlinear Dynamics (2023). https://doi.org/10.1007/s11071-023-08739-6

Geier, C., Stender, M. Hoffmann, N.: Data-driven reduced order modeling for mechanical oscillators using Koopman approaches. Frontiers in Applied Mathematics and Statistics 9 (2023). https://doi.org/10.3389/fams.2023.1124602

 

 

March 2024: C. Geier, M. Stender, N. Hoffmann: Complex dynamics of coupled nonlinear oscillators from a functional networks perspective. 94th GAMM Anual Meeting 2024, Magdeburg, Germany.

January 2024: C. Geier, N.Hoffmann:Analysis of nonlinear mechanical systems using recurrence network methods. (Poster). International School and Conference on Network Science NetSciX 2024, Venice, Italy.

June 2023: C. Geier, S. Hamdi, T. Chancelier, N. Hoffmann and M. Stender: Generating machine learning-based state maps from real-world friction-induced vibration data. Third International Nonlinear Dynamics Conference NODYCON 2023, Rome, Italy.

August 2022: C. Geier, M. Stender, S. Hamdi, N. Hoffmann and T. Chancelier: Data-driven stability maps for friction induced vibrations. GAMM Anual Meeting 2022, Aachen, Germany. Full slides available.

June 2022: C. Geier, M. Stender and N. Hoffmann: A network perspective on nonlinear machine dynamics. International Workshop "Intelligent Machines? – Self-organized Nonlinear Dynamics of Machines across Scales" at MPIPKS Dresden, Germany.

September 2021: M. Stender, C. Geier and N. Hoffmann: Koopman-driven identification of mechanical oscillators. DMV-ÖMG Annual Conference 2021, virtual event.

Vibration Theory - Technische Schwingungslehre