Rachel New

The University of Texas at Austin

Papers

1

Total Citations

3

H-Index

1

About

Dr. Rachel New is pioneering the integration of artificial intelligence and edge computing into hand tools, reshaping how human workers interact with technology. Her core research focuses on smart tool design, synthetic data generation, and edge intelligence, aiming to create responsive tools that enhance skill development and workplace safety. In her landmark 2024 paper, "Design, Development, and Testing of a Smart Hand Tool," she demonstrated a novel approach to work task recognition by training AI models on synthetic data—eliminating the need for costly real-world data collection. This work, already garnering 3 citations in its first year, lays the foundation for tools that can provide real-time feedback to novices, potentially broadening participation in skilled trades. Dr. New’s contributions stand out for their practical focus: she bridges cutting-edge machine learning with tangible human factors, making her research highly relevant to manufacturing, vocational training, and human-robot collaboration. Her achievements signal a future where everyday tools become intelligent partners, and her early citation impact underscores the excitement surrounding this emerging field.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Design, Development, and Testing of a Smart Hand Tool: Achieving Work Task Recognition Using Synthetic Data and Edge Intelligence
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: The University of Texas at Austin

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago