Chanh Kieu
Earth and Planetary Sciences · Indiana University
Publications
114
Citations
1,369
Est. group size
—
Recurring co-author estimate
Active years
22
Publishing since 2004
Chanh Kieu studies tropical cyclones (hurricanes and typhoons), focusing on how these storms form, intensify, and change under different climate conditions. Recent work applies machine learning and deep-learning methods to predict cyclone formation and intensity, often using climate reanalysis and weather-model data. The research combines atmospheric science, forecasting, and computational modeling.
Publication activity has remained fairly steady over the past decade, averaging around six to ten papers per year with no clear slowdown.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Environmental controls on future projections of western North Pacific tropical cyclone maximum intensity
npj Climate and Atmospheric Science · 2025
- NWP-based deep learning for tropical cyclone intensity prediction
arXiv (Cornell University) · 2025
- A Deep-learning Framework for Retrieving Tropical Cyclone Intensity and Structure from Gridded Climate Data (TCNN V1.0)
2025
- Reply on RC2
2025
- Reply on RC1
2025
- Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific from Climate Reanalysis Dataset
arXiv (Cornell University) · 2025
- An Investigation into the Delayed Rapid Intensification of Hurricane Ida (2021) Using Environmental Assimilation Approaches
Weather and Forecasting · 2025
- From Reanalysis to Climatology: Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific
2025
- Reconstructing Pre-Satellite Tropical Cyclogenesis Climatology Using Deep Learning
arXiv (Cornell University) · 2025
- Reconstructing Pre-Satellite Tropical Cyclogenesis Climatology Using Deep Learning
arXiv (Cornell University) · 2025
- Binary dataset for machine learning applications to tropical cyclone formation prediction
Scientific Data · 2024
- Predictability of Global AI Weather Models
arXiv (Cornell University) · 2024
- Can Machine Learning Predict any Chaos in Tropical Cyclone Intensity?
2024
- Searching for Chaos in Tropical Cyclone Intensity: A Machine Learning Approach
Tellus A Dynamic Meteorology and Oceanography · 2024
- When Does a Typhoon Form? A Deep Learning Approach using Synthetic Images Constructed from Climate Reanalysis Data
2024
- Journal of the Atmospheric Sciences×6
- arXiv (Cornell University)×6
- Weather and Forecasting×4
- Quarterly Journal of the Royal Meteorological Society×4
- AGU Fall Meeting Abstracts×4
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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