Data Manager
Machine Learning · China · 2024-11-24
Framework Evaluation
3 of 3 criteria metThe petitioner provided objective evidence of participating as a judge by conducting no fewer than 101 peer reviews for scientific journals.
The petitioner authored 14 peer-reviewed scientific articles in the field of machine learning and chemical engineering.
The petitioner developed a rapid tool to assess accidental CO2 dispersion, which was recognized for its significance to U.S. industrial safety and economic health.
Why This Petition Was Approved
Evidence
- 14 peer-reviewed scientific articles
- 101 peer reviews conducted for journals in the field
- Research funding from the Pipeline and Hazardous Materials Safety Administration (PHMSA)
- Research funding from the National Institutes of Health (NIH)
- Research funding from the National Science Foundation (NSF)
- Investigation of risk mitigation and resilience enhancement for CO2 pipelines
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Case data sourced from publicly available petition decisions and case studies. Decision date: 2024-11-24.
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