Nima Hosseini Dashtbayaz
PhD student in Computer Science at Western University
I’m Nima, Computer Science PhD student at the University of Western Ontario exploring deep learning applications in physics using Physics-informed Neural Networks and Neural Operators. Currently, I’m working on incorporating transfer learning methods for physics. Outside of research, I enjoy hiking and mountain biking.
Experience
- Research Intern at Autodesk (Toronto), 2024 - April 2025
- Physics-Informed Machine Learning Research Internship
Publications
[1] “Physics-informed Reduced Order Modeling of Time-dependent PDEs via Differentiable Solver” Nima Hosseini Dashtbayaz, Hesam Salehipour, Adrian Butscher, and Nigel Morris. NeurIPS 2025 (arXiv)
[2] “Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations” Nima Hosseini Dashtbayaz, Ghazal Farhani, Boyu Wang, and Charles Ling. IJCAI 2024 (arXiv)
Education
- PhD in Computer Science, University of Western Ontario, Sep 2023 - Present
- Supervisor: Prof. Boyu Wang
- MSc in Computer Science, University of Western Ontario, Sep 2022 - Aug 2023
- Supervisor: Prof. Boyu Wang
- Vector Scholarship in AI Recipient
- Transferred to PhD
- BSc in Computer Science, Amirkabir University of Technology, Sep 2018 - Aug 2022
- GPA: 4.0/4.0
- Thesis: Few-shot Domain Adaptation and Cross-Domain Few-shot Learning, A Survey (Manuscript)
Projects
- Tensorflow 2 Implementation of PINNs: Github Keras and TF2 implementation for PINNs, including Burger’s, Schrodinger’s, Pisson’s, Wave, Heat, and Advection equations so far.
- Few-shot Domain Adaptation and Cross-Domain FSL, A Survey. Part of my undergrad thesis work at Amirkabir University of Technology.