cv
Basics
| Name | Ning Liu |
| Label | Machine Learning Scientist |
| ningliu@umich.edu | |
| Url | https://ningliu-iga.github.io/ |
| Summary | a machine learning scientist with over six years of experience developing and applying novel neural architectures and attention-based models to accelerate numerical simulation and discover next-generation design |
Work
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2025.04 - Present -
2024.10 - 2025.04 Principal Machine Learning Scientist
Global Engineering & Materials, Inc.
Lead the development and deployment of novel machine learning models to accelerate the prediction of multi-physics simulations, such as using neural operators and variational autoencoders to learn aircraft aerodynamics, process modeling of composite curing, and applying large language models (LLM) to discover optimal polymer/composite structures for defense applications. Another line of work is on building digital twins for additive manufacturing.
- Write small-business research proposals (e.g., SBIR/STTR) and develop teaming strategies with academic collaborators;
- Develop and implement novel numerical methods for computational mechanics modeling;
- Supervise team members and lead quarterly reviews with technical team and sponsors;
- Publish high-quality papers on top-tier journals/conferences.
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2023.01 - 2024.09 Subject Matter Expert in Machine Learning
Global Engineering & Materials, Inc.
Develop and deploy state-of-the-art ML architectures for reduced-order modeling of multi-physics simulations; Developed a large molecular language model for polymer property prediction.
- Developed supervised pretraining to align LLM to a physically consistent initial state via physics-based prior knowledge;
- Built an end-to-end LLM product with limited data from input chemical structures to polymer flammability prediction;
- Secured over 2M funding from sponsors.
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2021.04 - 2022.12 -
2020.01 - 2021.03 -
2018.09 - 2019.12 Research Scientist
Global Engineering & Materials, Inc.
Research and software development on machine learning and computational mechanics (isogeometric analysis, time- and frequency-domain metallic fatigue, etc.).
Education
Skills
| Programming | |
| Python | |
| C++ | |
| FORTRAN | |
| SQL | |
| LaTeX | |
| Git |