Toward Using Few-Shot Learning for Prediction of Complex In-Service Defects of Composite Products: A case Study. - Mohamad Khajezade; Milad Ramezankhani; Fatemeh Hendijani Fard; Mohamed S. Shehata; Abbas S. Milani (CCECE, 2021)

An Active Transfer Learning (ATL) Framework for Smart Manufacturing with Limited Data: Case Study on Material Transfer in Composites Processing. - Milad Ramezankhani; Apurva Narayan; Rudolf J. Seethaler; Abbas S. Milani (ICPS, 2021)

A Data-driven Multi-fidelity Physics-informed Learning Framework for Smart Manufacturing: A Composites Processing Case Study. - Milad Ramezankhani; Amir Nazemi; Apurva Narayan; Heinz Voggenreiter; Mehrtash Harandi; Rudolf J. Seethaler; Abbas S. Milani (ICPS, 2022)

Investigation of a Sparse Autoencoder-Based Feature Transfer Learning Framework for Hydrogen Monitoring Using Microfluidic Olfaction Detectors. - Hamed Mirzaei; Milad Ramezankhani; Emily Earl; Nishat Tasnim; Abbas S. Milani; Mina Hoorfar (Sensors, 2022)

A Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing. - Milad Ramezankhani; Abbas S. Milani (CoRR, 2023)

Non data hungry smart composite manufacturing using active transfer learning with sigma point sampling (SPSATL). - Debangsha Sarkar; Milad Ramezankhani; Apurva Narayan; Abbas S. Milani (Comput. Ind., 2023)

FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition. - Milad Ramezankhani; Rishi Yash Parekh; Anirudh Deodhar; Dagnachew Birru (CoRR, 2024)

Smart manufacturing under limited and heterogeneous data: a sim-to-real transfer learning with convolutional variational autoencoder in thermoforming. - Milad Ramezankhani; Mehrtash Harandi; Rudolf J. Seethaler; Abbas S. Milani (Int. J. Comput. Integr. Manuf., 2024)

An advanced physics-informed neural operator for comprehensive design optimization of highly-nonlinear systems: An aerospace composites processing case study. - Milad Ramezankhani; Anirudh Deodhar; Rishi Yash Parekh; Dagnachew Birru (Eng. Appl. Artif. Intell., 2025)

Accelerated Gradient-based Design Optimization Via Differentiable Physics-Informed Neural Operator: A Composites Autoclave Processing Case Study. - Janak M. Patel; Milad Ramezankhani; Anirudh Deodhar; Dagnachew Birru (CoRR, 2025)

GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations. - Milad Ramezankhani; Janak M. Patel; Anirudh Deodhar; Dagnachew Birru (CoRR, 2025)

State of Health Estimation of Batteries Using a Time-Informed Dynamic Sequence-Inverted Transformer. - Janak M. Patel; Milad Ramezankhani; Anirudh Deodhar; Dagnachew Birru (CoRR, 2025)