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Research profile
Sarvin Moradi is a Doctoral Candidate at the Control Systems (CS) Group at the Department of Electrical Engineering. Her current research is part of the DAMOCLES (Data-Augmented Modeling Of Constitutive Laws for Engineering Systems) project founded by the EAISI (Eindhoven AI Systems Institute). She is working under the supervision of Roland Tóth, Maarten Schoukens, and Nick Jaensson. Her main research interest is the development of a general framework for modeling engineering systems that combines the favorable characteristics of physics-based and data-based approaches.
Collaborations and top research areas from the last five years
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Projects
- 1 Active
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DAMOCLES: Data-Augmented Modeling Of Constitutive Laws for Engineering Systems
Tóth, R., Moradi, S., Nawijn, H., Hendrix, W. H. A., Schoukens, M. & Jaensson, N. O.
1/09/21 → 31/08/25
Project: 1st tier research
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Learning physical models using Hamiltonian Neural Networks with output error noise models
Moradi, S., Jaensson, N., Tóth, R. & Schoukens, M., 21 Mar 2023, p. 37. 1 p.Research output: Contribution to conference › Abstract › Academic
Open Access -
Output error port Hamiltonian neural networks: a Silverbox example
Moradi, S., Beintema, G., Jaensson, N., Tóth, R. & Schoukens, M., 19 Apr 2023, p. 20. 1 p.Research output: Contribution to conference › Abstract › Academic
Open Access -
Learning Constitutive Laws in Engineering Systems
Moradi, S., Jaensson, N., Tóth, R. & Schoukens, M., 5 Jul 2022, p. 83-83. 1 p.Research output: Contribution to conference › Abstract › Academic
Open AccessFile20 Downloads (Pure) -
Output error Hamiltonian neural networks (OE-HNN)
Moradi, S., Jaensson, N., Tóth, R. & Schoukens, M., 19 Sept 2022, p. 62-62.Research output: Contribution to conference › Poster