Florian Rossmannek
Assistant Professor | NTU Singapore
About Me
I am a Nanyang Assistant Professor at NTU Singapore in the Division of Mathematical Sciences doing research on the mathematics of machine learning.
Prior to that, I was a Postdoctoral Fellow at NTU Singapore, mentored by Juan-Pablo Ortega.
I obtained my doctoral degree from ETH Zurich in March 2023, advised by Patrick Cheridito and Arnulf Jentzen.
I am an alumnus of the Schmidt AI in Science program and of the RiskLab Switzerland.
Recent Highlights
- Committe member and speaker at IAS Frontiers Conference on Geometry, Dynamics, and Learning @NTU
- Invited session organizer and speaker at IntelligenceX: The Global Quantum x AI Frontier @NUS
- Research visit at ETH Zurich
- New paper out with M. Petreczky, J-P. Ortega, and B. Daróczy
- Invited talk at the Asia-Pacific Summer School and Conference on Networks and Complex Systems 2026 @NTU
- Invited talk at the HUN-REN AI Symposium 2026 (picture)
Research Interest
I work on the mathematical foundation of machine learning, where I am particularly interested in the mechanisms of models (such as reservoir computers, state-space systems, kernel methods, etc.) used for learning and forecasting of (deterministic and stochastic) dynamical systems.
My earlier work concerned approximation and optimization problems in (static) neural network theory.
Research Articles
Publications
- Stability of input-output maps and their minimal realizations in state-linear, state-affine, LPV, and linear switched systems (with M. Petreczky, J-P. Ortega, and B. Daróczy),
IEEE Control Syst. Lett., vol 10, 2026 [journal / arXiv]
- Echoes of the past: A unified perspective on fading memory and echo states (with J-P. Ortega),
Neural Comp., vol 38(5), 2026 [journal / arXiv]
- Stochastic dynamics learning with state-space systems (with J-P. Ortega),
Math. Models Methods Appl. Sci., vol 36(8), 2026 [journal / arXiv]
- Fading memory and the convolution theorem (with J-P. Ortega)
IEEE Trans. Autom. Control, vol 70(12), 2025 [journal / arXiv]
- State-space systems as dynamic generative models (with J-P. Ortega)
Proc. R. Soc. A, vol 481(2309), 2025 [journal / arXiv]
- Gradient descent provably escapes saddle points in the training of shallow ReLU networks (with P. Cheridito and A. Jentzen)
J. Optim. Theory Appl., vol 203(3), 2024 [journal / arXiv]
- Landscape analysis for shallow neural networks: complete classification of critical points for affine target functions (with P. Cheridito and A. Jentzen)
J. Nonlinear Sci., vol 32(5), 2022 [journal / arXiv]
- A proof of convergence for gradient descent in the training of artificial neural networks for constant target functions (with P. Cheridito, A. Jentzen, and A. Riekert)
J. Complexity, vol 72, 2022 [journal / arXiv]
- Non-convergence of stochastic gradient descent in the training of deep neural networks (with P. Cheridito and A. Jentzen)
J. Complexity, vol 64, 2021 [journal / arXiv]
- Efficient approximation of high-dimensional functions with neural networks (with P. Cheridito and A. Jentzen)
IEEE Trans. Neural Netw. Learn. Syst., vol 33(7), 2022 [journal / arXiv]
Preprints
- Efficient Sobolev approximation of linear parabolic PDEs in high dimensions (with P. Cheridito), 2023 [arXiv]
Miscellaneous
- PhD thesis: The curse of dimensionality and gradient-based training of neural networks: shrinking the gap between theory and applications (2023) [link]
- An exercise in combinatorics: Christmas Stars (2021) [pdf]
- MSc thesis: Magnetic and Exotic Anosov Hamiltonian Structures (2019)
Teaching
BSc (NTU)
- MH4931 — Special Topics in Applied Mathematics (AY26/27, details)
MSc in Modelling and Simulation (NTU)
- MH6505 — Machine Learning and Artificial Intelligence: Principles and Techniques (AY26/27)
- MH6551 — Modelling and Simulation in Data Science and Computing Engineering (AY25/26)
Resume
Employment
| Since 2025 | Assistant Professor | NTU Singapore |
| 2023 - 2025 | Postdoctoral Fellow | NTU Singapore |
| 2019 - 2023 | Research Assistant | ETH Zurich |
Education
| 2019 - 2023 | PhD Mathematics | ETH Zurich |
| 2017 - 2019 | MSc Mathematics | ETH Zurich |
| 2014 - 2018 | BSc Mathematics | ETH Zurich |
Fellowships / Grants
| 2025 | Nanyang Assistant Professorship Startup Research Grant |
| 2023 | Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship |
Selected Talks
2026
- GDL (IAS Frontiers Conference on Geometry, Dynamics, and Learning); NTU
- IntelligenceX (The Global Quantum x AI Frontier); Session on Reservoir Computing and Dynamical Systems; NUS
- APCNCS (Asia-Pacific Summer School and Conference on Networks and Complex Systems); Focus Session on Complexity of AI; NTU
- HUN-REN AI Symposium; Budapest
- MLDS5 & DEDS (5th Symposium on Machine Learning and Dynamical Systems & Differential Equations for Data Science); Kyoto
2025
2024
