Data Associate
Data Science · India · 2023-11-30
Proposed Endeavor
The petitioner proposes to develop machine-learning-based methodologies to accelerate diverse workflows supporting geological characterization, carbon capture and utilization, risk management, and reservoir management. Her work focuses on using ML to improve various workflows within the energy and data science sectors.
Framework Evaluation
3 of 3 criteria metThe research on ML for geological characterization and carbon capture was found to have clear national importance and substantial merit, supported by DOE funding.
The petitioner is well-positioned due to her Ph.D., record of 9 total publications, and 165 citations demonstrating her renown in the field.
On balance, her contributions are of such value that they benefit the United States overall even if other competent U.S. workers are available.
Why This Petition Was Approved
Evidence
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Case data sourced from publicly available petition decisions and case studies. Decision date: 2023-11-30.
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