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ORCIDMilad Ramezankhani
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2020 – today
- 2024
[j3]Milad Ramezankhani, Mehrtash Harandi, Rudolf J. Seethaler, Abbas S. Milani:
Smart manufacturing under limited and heterogeneous data: a sim-to-real transfer learning with convolutional variational autoencoder in thermoforming. Int. J. Comput. Integr. Manuf. 37(1-2): 18-36 (2024)- [i4]Milad Ramezankhani, Anirudh Deodhar, Rishi Yash Parekh, Dagnachew Birru:
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study. CoRR abs/2406.14715 (2024) - [i3]Milad Ramezankhani, Rishi Yash Parekh, Anirudh Deodhar, Dagnachew Birru:
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition. CoRR abs/2409.09207 (2024) - 2023
- [j2]Debangsha Sarkar
, Milad Ramezankhani, Apurva Narayan, Abbas S. Milani:
Non data hungry smart composite manufacturing using active transfer learning with sigma point sampling (SPSATL). Comput. Ind. 151: 103989 (2023) - [i2]Milad Ramezankhani, Abbas S. Milani:
A Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing. CoRR abs/2308.06447 (2023) - 2022
- [j1]Hamed Mirzaei, Milad Ramezankhani, Emily Earl, Nishat Tasnim, Abbas S. Milani, Mina Hoorfar:
Investigation of a Sparse Autoencoder-Based Feature Transfer Learning Framework for Hydrogen Monitoring Using Microfluidic Olfaction Detectors. Sensors 22(20): 7696 (2022) - [c3]Milad Ramezankhani, Amir Nazemi, Apurva Narayan, Heinz Voggenreiter, Mehrtash Harandi, Rudolf J. Seethaler, Abbas S. Milani:
A Data-driven Multi-fidelity Physics-informed Learning Framework for Smart Manufacturing: A Composites Processing Case Study. ICPS 2022: 1-7 - [i1]Milad Ramezankhani, Amir Nazemi, Apurva Narayan, Heinz Voggenreiter, Mehrtash Harandi, Rudolf J. Seethaler, Abbas S. Milani:
A Data-driven Multi-fidelity Physics-informed Learning Framework for Smart Manufacturing: A Composites Processing Case Study. CoRR abs/2202.06139 (2022) - 2021
- [c2]Mohamad Khajezade, Milad Ramezankhani, Fatemeh Hendijani Fard, Mohamed S. Shehata, Abbas S. Milani:
Toward Using Few-Shot Learning for Prediction of Complex In-Service Defects of Composite Products: A case Study. CCECE 2021: 1-7 - [c1]Milad Ramezankhani, Apurva Narayan, Rudolf J. Seethaler, Abbas S. Milani:
An Active Transfer Learning (ATL) Framework for Smart Manufacturing with Limited Data: Case Study on Material Transfer in Composites Processing. ICPS 2021: 277-282
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