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Andrew Panyin Vormawor

Obstetrics and Gynaecology

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Research Summary

(inferred from publications by AI)

The researcher has focused on advancing methodologies for dynamic traffic modeling and optimization, particularly in addressing real-world challenges such as congestion and driver behavior. Their work encompasses developing innovative models for multi-objective traffic flow control using machine learning, designing optimal strategies for vehicle-to-vehicle communication in dense networks, and exploring efficient solutions for real-time optimization through reinforcement learning and network congestion management. The overarching goal is to enhance traffic efficiency and reduce its negative impacts on urban mobility.

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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.