Since October 2017: Research Assistant and PhD candidate at Munich School of Engineering (MSE) and Institute for Information-Oriented Control (ITR), Technical University of Munich
-> Supervisor: Prof. Sandra Hirche, Technical University of Munich
October 2016: M.Sc. in Mechanical Engineering (cum laude), RWTH Aachen, Germany
-> Thesis title: Design and Optimization of a Three-Phase Reactive Batch Distillation Column as an Underdetermined System of Differential-Algebraic Equations with Optimization Criteria
-> Supervisor: Prof. Alexander Mitsos
July 2014: B.Eng. in Mechanical Engineering RWTH Aachen, Germany
-> Thesis title: Modelling and Feedback Control of a 6-Phase Drive System
-> Supervisor: Prof. Dirk Abel, RWTH Aachen
Research Interests
Energy Systems Modelling and Optimization
Smart Grids
Reinforcement Learning
Gaussian Processes
Working Field
My current research focuses on Gaussian Processes in Control-oriented settings. I am also interested in applying machine learning methods to energy systems.
Current Projects
I am currently involved in the MEMAP Project, a collaboration between MSE, ITR and multiple firms with ties to the energy sector. My goal within the project is to apply machine learning to district energy systems.
Please feel free to contact me if any of the topics above interest you for a Bachelor's or Master's thesis, or if you have a topic of your own.
Contact
Motivated students are encouraged to contact me via E-mail if interested in doing their Bachelor's or Master's thesis under my supervision. Please include your CV and credentials with your application.
N. Das; J. Umlauft; A. Lederer; A. Capone; T. Beckers; S. Hirche: Deep Learning based Uncertainty Decomposition for Real-time Control. 2023, The 22nd World Congress of the International Federation of Automatic Control, 2023 mehr…BibTeX
2022
A. Capone; A. Lederer; S. Hirche: Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications. Proceedings of the 39th International Conference on Machine Learning, 2022 mehr…BibTeX
J. Brüdigam; M. Schuck; A. Capone; S. Sosnowski; S. Hirche: Structure-Preserving Learning Using Gaussian Processes and Variational Integrators. 4th Annual Conference on Learning for Dynamics and Control, 2022 mehr…BibTeX
Jiao, Junjie; Capone, Alexandre; Hirche, Sandra: Backstepping tracking control using Gaussian processes with event-triggered online learning. IEEE Control Systems Letters, 2022, 3176 - 3181 mehr…BibTeX
2021
A. Lederer; A. Capone; T. Beckers; J. Umlauft; S. Hirche: The Impact of Data on the Stability of Learning-Based Control - Extended Version. Learning for Dynamics and Control, 2021 mehr…BibTeX
2020
A. Capone; G.Noske; J. Umlauft; T. Beckers; A. Lederer; S. Hirche: Localized active learning of Gaussian process state space models. Learning for Dynamics & Control, 2020 mehr…BibTeX
A. Capone: C. Helminger: S. Hirche: Day-Ahead Scheduling of Thermal Storage Systems Using Bayesian Neural Networks. IFAC World Congress 2020, 2020 mehr…BibTeX
A. Capone; A. Lederer; J. Umlauft; S. Hirche: Data Selection for Multi-Task Learning Under Dynamic Constraints. IEEE Control Systems Letters 5 (3), 2020, 959-964 mehr…BibTeX
A. Capone; G. Noske; J. Umlauft; T. Beckers; A. Lederer; S. Hirche: Localized Active Learning of Gaussian Process State Space Models. 2020 mehr…BibTeX
A. Lederer; A. Capone; S. Hirche: Parameter Optimization for Learning-based Control of Control-Affine Systems. Learning for Dynamics & Control, 2020 mehr…BibTeX
A. Lederer; A. Capone; J. Umlauft; S. Hirche: How Training Data Impacts Performance in Learning-based Control. IEEE Control Systems Letters 5 (3), 2020, 905-910 mehr…BibTeX
Capone, Alexandre, Hirche, Sandra: Anticipating the Long-Term Effect of Learning in Control. American Control Conference 2020, 2020 mehr…BibTeX
Capone, Alexandre, Lederer, Armin, Hirche, Sandra: Anticipating Learning in Multi-Step Ahead Predictions of Learning-Based Control. IFAC World Congress 2020, 2020 mehr…BibTeX
J. Umlauft; T. Beckers; A. Capone; A. Lederer; S. Hirche: Smart Forgetting for Safe Online Learning with Gaussian Processes. Learning for Dynamics & Control, 2020 mehr…BibTeX
2019
A. Capone; S. Hirche: Backstepping for Partially Unknown Nonlinear Systems Using Gaussian Processes. IEEE Control Systems Letters 3 (2), 2019, 416 - 421 mehr…BibTeX
Capone, A.; Hirche, S.: Interval Observers for a Class of Nonlinear Systems Using Gaussian Process Models. 2019 18th European Control Conference, IEEE, 2019 mehr…BibTeX
