Mac Elikem Kwabla Nutsuakor

Wildlife and Range Management

About

Mr Mac Elikem Nutsuakor holds a Master of Science degree in Forest Sciences and Forest Ecology from the Georg-August-Universität, Göttingen, Germany. His undergraduate degree was obtained in Environmental and Natural Resources Management.He has gained the requisite work experience locally and internationally since 2004 when he joined the Kwame Nkrumah University of Science and Technology as a field technician in the Department of Wildlife and Range Management. Expertise in species (flora and fauna) identification and adequate knowledge in field protocols towards biodiversity monitoring, conservation and management; Use of participatory approaches in Natural Resources Management based on adequate scientific information to enhance ecosystem functions and sustainable livelihoods. He has has been part of several projects funded by both local and international organisations. Notably among these are; Deutsche Forschungsgemeinschaft (DFG) (German Research Foundation), International Foundation for Science (IFS), A Rocha/Ecosystem Grant Programme of the Netherlands Committee of IUCN and Newmont Ghana limited (Akyem Project area). Elikem is so passionate about forest and wildlife conservation.

Research Summary

(inferred from publications by AI)

This researcher has made significant contributions to advancing computational topology and its applications in machine learning. Their work integrates theoretical developments in topological data analysis with practical implementations using graph neural networks and implicit surface reconstruction techniques. The research bridges mathematical theory with real-world challenges, particularly in shape reconstruction and anomaly detection, while also addressing the broader implications of deep learning models for understanding complex data structures.

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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.