Machine Learning Models of Propagation Structures

• US Patent (2022)
• Young Scientist Award to be received at the International Union of Radio Science (URSI GASS 2023), Dates. August, 2023. (2023)
• Best Paper award (€ 1000) in the Student Paper competition of the International Conference on Electromagnetic and Multiphysics Modeling and Optimization (NEMO2022) sponsored by IEEE MTT Society and held in Limoges (France) July 6-8, 2022, with the paper “Vector-Valued Kernel Ridge Regression for the Modeling of High-Speed Links,” N. Soleimani, R. Trinchero, F. Canavero. (https://www.linkedin.com/posts/detpolito_phd-candidate-nastaran-soleimani-received-activity-6952236349693308929-ROv8?utm_source=linkedin_share&utm_medium=member_desktop_web) (2022)

• Soleimani, Nastaran; Trinchero, Riccardo; Canavero, Flavio G. (2023)
  Bridging the Gap Between Artificial Neural Networks and Kernel Regressions for Vector-Valued Problems in Microwave Applications. In: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, vol. 71, pp. 2319-2332. ISSN 0018-9480
  Contributo su Rivista
• Soleimani, Nastaran; Manfredi, Paolo; Trinchero, Riccardo (2023)
  Efficient Implementation of the Vector-Valued Kernel Ridge Regression for the Uncertainty Quantification of the Scattering Parameters of a 2-GHz Low-Noise Amplifier. In: IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO'2023), Winnipeg, MB (CAN), 28-30 June 2023, pp. 143-146. ISBN: 979-8-3503-4740-1
  Contributo in Atti di Convegno (Proceeding)
• Ahmadi, Mohsen; Sharifi, Abbas; Jafarian Fard, Mahta; Soleimani, Nastaran (2023)
  Detection of brain lesion location in MRI images using convolutional neural network and robust PCA. In: INTERNATIONAL JOURNAL OF NEUROSCIENCE, pp. 1-12. ISSN 0020-7454
  Contributo su Rivista
• Soleimani, Nastaran; Trinchero, Riccardo; Canavero, Flavio (2023)
  Modeling of a High-Speed Link Based on an Efficient Implementation of Vector-Valued Machine Learning Kernel Regression. In: 21ème Colloque International et Exposition sur la Compatibilité ÉlectroMagnétique (CEM 2023), Toulouse, France, 13-15 juin 2023
  Contributo in Atti di Convegno (Proceeding)
• Soleimani, Nastaran (2023)
  Machine Learning based Surrogate Modeling of Electronic Devices and Circuits. relatore: TRINCHERO, RICCARDO; CANAVERO, Flavio; , 35. XXXV Ciclo, P.: 112
  Doctoral Thesis
• Soleimani, Nastaran; Trinchero, Riccardo (2023)
  Efficient Implementation of the Vector-Valued Kernel Ridge Regression for the Parametric Modeling of the Frequency-Response of a High-Speed Link. In: 35th URSI General Assembly and Scientific Symposium (URSI GASS 2023), Sapporo, Japan, 19-26 August 2023. ISBN: 978-9-4639-6809-6
  Contributo in Atti di Convegno (Proceeding)
• Telescu, M; Trinchero, R; Soleimani, N; Tanguy, N; Stievano, Is (2023)
  Stochastic Time-Domain Mapping for Comprehensive Uncertainty Assessment in Eye Diagrams. In: IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, vol. 65, pp. 1930-1938. ISSN 0018-9375
  Contributo su Rivista
• Kushwaha, Suyash; Soleimani, Nastaran; Treviso, Felipe; Kumar, Rahul; Trinchero, ... (2022)
  Comparative Analysis of Prior Knowledge-Based Machine Learning Metamodels for Modeling Hybrid Copper–Graphene On-Chip Interconnects. In: IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, vol. 64, pp. 2249-2260. ISSN 0018-9375
  Contributo su Rivista
• Soleimani, Nastaran; Trinchero, Riccardo; Canavero, Flavio (2022)
  Vector-Valued Kernel Ridge Regression for the Modeling of High-Speed Links. In: 2022 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO), Limoges, France, 06-08 July 2022, pp. 1-4. ISBN: 978-1-6654-8633-0
  Contributo in Atti di Convegno (Proceeding)
• Soleimani, N.; Trinchero, R. (2022)
  Compressed Complex-Valued Least Squares Support Vector Machine Regression for Modeling of the Frequency-Domain Responses of Electromagnetic Structures. In: ELECTRONICS, vol. 11. ISSN 2079-9292
  Contributo su Rivista
• Soleimani, N.; Trinchero, R.; Canavero, F. (2020)
  Application of Different Learning Methods for the Modelling of Microstrip Characteristics. In: 2020 IEEE Electrical Design of Advanced Packaging and Systems, EDAPS 2020, chn, 2020, pp. 1-3. ISBN: 978-1-7281-9412-7
  Contributo in Atti di Convegno (Proceeding)
• Soleimani, Nastaran; Alijani, Mohammad G. H.; Neshati, Mohammad H. (2019)
  Crosstalk analysis at near-end and far-end of the coupled transmission lines based on eigenvector decomposition. In: AEÜ. INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, vol. 112. ISSN 1434-8411
  Contributo su Rivista
• Soleimani, Nastaran; Alijani, Mohammad G. H.; Neshati, Mohammad H. (2019)
  Crosstalk analysis of multi‐microstrip coupled lines using transmission line modeling. In: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, vol. 29. ISSN 1096-4290
  Contributo su Rivista
• GHadikolaei Alijani, Mohammad; Soleimani, Nastaran; Hassan Neshati, Mohammad (2019)
  Power transmission through a single conductive element. N. brevetto: 10868525, propr. brevetto: 4 - Soggetti terzi
  Brevetti
• Soleimani, N.; Alijani, M. G. H.; Neshati, M. H. (2019)
  Crosstalk analysis of uniform and nonuniform lossy microstrip-coupled transmission lines. In: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, vol. 29. ISSN 1096-4290
  Contributo su Rivista