Axel Ringh

Assistant Professor at Applied Mathematics and Statistics

My research interests are in the intersection of applied mathematics and areas such as control theory, signal processing, inverse problems, and machine learning. In particular, I am interested in computational optimal transport, especially the Sinkhorn iterations and its connections to other areas, and applications of optimal transport. The latter includes problems in formation control, state estimation for ensembles, dynamic flow problems, and various applications in machine learning.

Personal homepage: https://sites.google.com/view/axelringh/

Source: chalmers.se
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Showing 10 publications

2024

Inverse optimal control for averaged cost per stage linear quadratic regulators

Han Zhang, Axel Ringh
Systems and Control Letters. Vol. 183
Journal article
2024

Scalable Computation of Dynamic Flow Problems via Multimarginal Graph-Structured Optimal Transport

Isabel Haasler, Axel Ringh, Yongxin Chen et al
Mathematics of Operations Research. Vol. 49 (2), p. 986-1011
Journal article
2024

Graph-structured tensor optimization for nonlinear density control and mean field games

Axel Ringh, Isabel Haasler, Yongxin Chen et al
SIAM Journal on Control and Optimization. Vol. 62 (4), p. 2176-2202
Journal article
2023

Mean field type control with species dependent dynamics via structured tensor optimization

Axel Ringh, Isabel Haasler, Yongxin Chen et al
IEEE Control Systems Letters. Vol. 7, p. 2898-2903
Journal article
2022

Low Phase-Rank Approximation

Di Zhao, Axel Ringh, Li Qiu et al
Linear Algebra and Its Applications. Vol. 639, p. 177-204
Journal article
2022

Statistically Consistent Inverse Optimal Control for Linear-Quadratic Tracking with Random Time Horizon

Han Zhang, Axel Ringh, Weihan Jiang et al
Chinese Control Conference, CCC. Vol. 2022-July, p. 1515-1522
Paper in proceeding
2022

Gain and phase type multipliers for structured feedback robustness

Axel Ringh, Xin Mao, Wei Chen et al
Preprint

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Showing 1 research projects

2023–2026

New conditions for optimized freight transport solutions

Ann-Brith Strömberg Applied Mathematics and Statistics
Anna Dubois Supply and Operations Management
Frida Lind Supply and Operations Management
Axel Ringh Applied Mathematics and Statistics
Leo Laine Mechanics and Maritime Sciences (M2)
Joseph Löfving Applied Mathematics and Statistics
Jonathan Stål Supply and Operations Management
VINNOVA

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