Pazit Ziv

University of Leeds

Papers

1

Total Citations

7

H-Index

1

About

Pazit Ziv is a leading researcher at the intersection of aquatic biogeochemistry, sensor technology, and machine learning, whose work is transforming how we monitor and manage river carbon emissions. Her most-cited paper, "Integrating sensor data and machine learning to advance the science and management of river carbon emissions" (2024, 7 citations), addresses a critical global challenge: the high uncertainty in greenhouse gas estimates from river networks. By pioneering the integration of in-situ sensor advances with mobile sensors on robotic deployment platforms, Ziv has developed novel frameworks that enable high-resolution, real-time data collection in previously inaccessible waterways. Her major contribution lies in bridging the gap between sparse manual sampling and the need for continuous, accurate emissions inventories—directly informing climate policy and river management. Though early in her citation trajectory, Ziv’s work is already recognized for its potential to close major gaps in global carbon budgets. Her innovative fusion of field robotics and data science positions her as a rising leader in environmental sensing, with implications for both fundamental science and actionable climate solutions.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Integrating sensor data and machine learning to advance the science and management of river carbon emissions
7 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: University of Leeds

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago