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Jiangtao Liu
Pennsylvania State University Main CampusMeeting roles in:
Improving Landslide Susceptibility Prediction with Terrain Patterns, High-Resolution Data, and Ensemble Models
Distributed Differentiable Routing on the CONUS Hydrofabric
When Stream Temperature Meets Streamflow: A Scalable Approach to Modeling Climate-Sensitive Groundwater Recharge
A Pretrained Foundation AI Model Reveals Global Landscape Dynamics and Human-driven Ecosystem Deviations
Frontier AI Models Transforming Water Science I Oral
Improved Multi-Domain Environmental Forecasting Through Landscape-Based AI Modeling
Leveraging Memory in Deep Learning to Improve Drought Impact and Legacy Predictions in Forest Ecosystems
Frontier AI Models Transforming Water Science II Poster
Structural Bias Should Be Addressed Before Effective Parameter Learning — Insights from SMAP Soil Moisture Simulations Using Differentiable Process-Based Models
Distinct Hydrologic Response Patterns and Trends Worldwide Revealed by Physics-embedded Learning
Unexpectedly Strong Landscape Interconnections Captured by Earth Foundation AI for Land
Differentiable Physics‐Informed Machine Learning Enhances High-resolution Hydrologic Modeling
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