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Profile photo of Johann Yaw Sekyi-Baidoo

Johann Yaw Sekyi-Baidoo

English

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Research Summary

(inferred from publications by AI)

This researcher's work spans a broad range of geophysical and biological systems, employing computational modeling and machine learning to advance understanding across various fields. Their focus includes the interplay between physical processes in geology, biodynamics, and climate science, as well as the application of deep learning techniques for predictive modeling. They investigate phenomena like earthquakes, climate change, marine ecosystems, exoplanet formation, materials science applications such as peridynamics, hydrogeological systems, and carbon cycle dynamics. Their research emphasizes the complexity of natural systems and the challenges in modeling these with accuracy and scale, particularly in capturing uncertainty across large spatial and temporal scales.

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About This Profile

This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.