Milad Ramezankhani

Senior Research Engineer, Quantiphi

Joined

April 2024

Names

Milad Ramezankhani (Preferred)

Emails

****@quantiphi.com (Confirmed)

****@gmail.com (Confirmed)

****@ubc.ca

Personal Links

Career & Education History

Senior Research Engineer

Quantiphi (quantiphi.com)

2023 – Present

Postdoc

Engineering, University of British Columbia (ubc.ca)

2023 – 2023

PhD student

Engineering, University of British Columbia (ubc.ca)

2018 – 2023

Advisors, Relations & Conflicts

Coauthor

Dagnachew Birru

2023 – Present

Coauthor

Anirudh Deodhar

2023 – Present

Coauthor

Rishi Yash Parekh

2023 – Present

PhD Advisor

Abbas S. Milani

2018 – 2023

Expertise

Graph Representation Learning

2024 – Present

Scientific Machine Learning

2020 – Present

Physics-informed Neural Networks

2020 – Present

Neural Operators

2020 – Present

AI for Science

2020 – Present

Publications

DETNO: A DIFFUSION-ENHANCED TRANSFORMER NEURALOPERATOR FOR LONG-TERM TRAFFIC FORECASTING
Owais Ahmad, Milad Ramezankhani, Anirudh Deodhar
- DAI Oral
- Readers: Everyone
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
Milad Ramezankhani, Janak M. Patel, Anirudh Deodhar, Dagnachew Birru
- CO-BUILD Poster
- Readers: Everyone
Accelerated Gradient-Based Design Optimization via Differentiable Physics Informed Neural Operator for Composite Materials Processing
Janak M. Patel, Milad Ramezankhani, Anirudh Deodhar, Dagnachew Birru
- AI4MAT-ICLR-2025 Poster
- Readers: Everyone
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
- Readers: Everyone
An Advanced Physics-Informed Neural Operator for Dynamic, Zero-shot, and Near Real-time Simulation of Aerospace Composite Material Curing Process
Milad Ramezankhani, Anirudh Deodhar, Rishi Yash Parekh, Dagnachew Birru
- AI4Mat-Vienna-2024 Oral
- Readers: Everyone
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
- ICML2024-AI4Science Poster
- Readers: Everyone
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
- Readers: Everyone
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
- Readers: Everyone
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
- Readers: Everyone
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
- Readers: Everyone

View all 14 publications

Milad Ramezankhani

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Co-Authors