cv
Curriculum Vitae
Basics
| Name | Arash Sarshar |
| Label | Assistant Professor |
| arash.sarshar@csulb.edu | |
| Url | https://sarshar.dev |
| Summary | Assistant Professor at California State University, Long Beach. Research focuses on Scientific Machine Learning, Computational Science, and Deep Uncertainty Quantification. |
Work
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2022.08 - Present Assistant Professor
California State University, Long Beach
Department of Computer Engineering and Computer Science. Director of the Computational Science and Machine Learning Lab (CSML).
- Scientific Machine Learning
- Physics-Informed Neural Networks
- Uncertainty Quantification
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2021.01 - 2022.07 Postdoctoral Associate
Virginia Tech
Physics-informed machine learning for forward and inverse problems.
- Deep Learning
- Numerical Methods
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2019.05 - 2019.08 Research Intern
Toyota Racing Development
Developed predictive models based on CFD simulations.
- Computational Fluid Dynamics
- Machine Learning
Education
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2015.08 - 2020.12 Blacksburg, VA
PhD
Virginia Tech, Blacksburg, VA
Computer Science and Applications
- Numerical Methods
- Machine Learning
- Scientific Computing
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2009.09 - 2012.06 Mashhad, Iran
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2004.09 - 2008.06 Tehran, Iran
Skills
| Scientific Computing | |
| Numerical Methods | |
| ODEs/PDEs | |
| Large-scale Simulations | |
| High Performance Computing |
| Machine Learning | |
| Deep Learning | |
| Physics-Informed Neural Networks | |
| Bayesian Learning | |
| Uncertainty Quantification |
| Programming | |
| Python | |
| MATLAB | |
| Julia | |
| PyTorch | |
| JAX |
Interests
| Scientific Machine Learning | ||||
| Data-driven modeling | ||||
| Physics-informed neural networks | ||||
| Operator learning | ||||
| Computational Science | ||||
| Numerical methods | ||||
| Real-world scientific problems | ||||
| Large-scale simulations | ||||
| Uncertainty Quantification | ||||
| Probabilistic machine learning | ||||
| Bayesian inference | ||||
| Prediction uncertainty | ||||