Doctoral Candidate
Sarvin Moradi
Department / Institute
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.
Recent Publications
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Sarvin Moradi,G.I. Beintema,N.O. Jaensson,Roland Tóth,Maarten Schoukens
Output Error Port-Hamiltonian Neural Network
(2023) -
Sarvin Moradi,N.O. Jaensson,Roland Tóth,Maarten Schoukens
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models
IFAC-PapersOnLine (2023) -
Sarvin Moradi,Gerben Beintema,Nick Jaensson,Roland Tóth,Maarten Schoukens
Output error port Hamiltonian neural networks
(2023) -
Sarvin Moradi,Nick Jaensson,Roland Tóth,Maarten Schoukens
Learning physical models using Hamiltonian Neural Networks with output error noise models
(2023) -
Sarvin Moradi,Nick Jaensson,Roland Tóth,Maarten Schoukens
Output error Hamiltonian neural networks (OE-HNN)
(2022)
Ancillary Activities
No ancillary activities