Papers

2

Total Citations

15

H-Index

1

About

Chiara Alberti’s research sits at the intersection of surgical robotics and oncology, where she advances both the engineering of autonomous surgical systems and the clinical understanding of cancer outcomes. Her most cited work, a 2021 study on spatio-temporal U-Nets for tissue segmentation in surgical robotics (14 citations), tackles a fundamental barrier to surgical autonomy: enabling machines to interpret endoscopic video streams in real-time and identify soft tissue features. This contribution is critical for developing robots that can interact safely and intelligently with complex surgical scenes. In parallel, her 2025 systematic review and meta-analysis on resection margins in hypopharyngeal surgery addresses a pressing clinical challenge—how margin status affects local control and survival in an aggressive malignancy with poor prognosis. By bridging deep learning for real-time scene understanding with evidence-based surgical oncology, Alberti’s work exemplifies translational research that could reshape both how robots assist in the operating room and how surgeons plan cancer resections. Her dual focus on algorithmic innovation and clinical meta-analysis marks her as a rising voice in surgical data science.

Research Focus

Key Achievements

1
H-Index
2
Papers
15
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics
14 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Politecnico di Milano, University of Modena and Reggio Emilia

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago