Michael | Geological Remote Sensing | Best Researcher Award

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Mr. Michael | Geological Remote Sensing | Best Researcher Award

University of Electronic Science and Technology of China,  China

Michael Appiah-Twum, a geoscientist, combines Artificial Intelligence and Machine Learning with advanced remote sensing to revolutionize natural resources and environmental management. He specializes in geospatial data analysis for geological surveys, mineral exploration, petroleum exploration, and environmental monitoring. With a solid foundation in geology, geophysics, and geochemistry, Michael integrates cutting-edge AI technologies for sustainable development. Currently pursuing a Ph.D. in Information and Communication Engineering at the University of Electronic Science and Technology of China, he excels in developing innovative AI-driven solutions for geological interpretation and resource management.

Profile

Orcid

Scholar

🎓 Education

Ph.D. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020-Present); GPA: 3.52/4.0. Thesis: Deep Learning-based Multisource Geological Interpretation. M.Sc. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020); GPA: 3.51/4.0. Thesis: Remote Sensing and Geological Survey of Gold Deposits. B.Sc. in Earth Science: University for Development Studies, Ghana (2014). Thesis: Atlas of Laterite and Exploration Implications.

🧑‍🏫 Experience

Researcher: Yangtze Delta Region Institute, UESTC (2022–Present) – Conducting AI/ML research for geological data analysis and mineral exploration. Course Instructor: UESTC (2023) – Designed curricula and taught Remote Sensing in Resources and Environment. Teaching Assistant: UESTC (2022–2023) – Conducted tutorials, guided projects, and mentored students in Remote Sensing. VIP Member: UESTC Green Club (2018–2020) – Advocated sustainable agriculture and environmental awareness. Electoral Official: Electoral Commission of Ghana (2015) – Managed polling operations during elections.

🏆 Awards and Honors

Top Ranked Ph.D. Student: University of Electronic Science and Technology of China (2020-Present). Graduate Student Member: IEEE Geoscience and Remote Sensing Society. Top Ranked M.Sc. Student: UESTC, Chengdu (2020). Research Excellence: Developed advanced geological interpretation models using AI/ML. Leadership Recognition: UESTC Green Club VIP for promoting sustainability and environmental stewardship.

🔬 Research Focus

Geological Surveys: Using remote sensing for mineral and petroleum exploration. AI/ML Applications: Implementing deep learning for geological and environmental data interpretation. Geospatial Analysis: Advanced modeling for resource exploration and sustainable development. Hydrology and Regolith: Focused on soil mechanics and hydrogeology for environmental management. Remote Sensing Integration: Leveraging UAVs and satellite imagery for accurate geoscientific data visualization.

Conclusion 

Michael Appiah-Twum is undoubtedly a strong contender for the Best Researcher Award, given his exceptional research in remote sensing, AI/ML applications, and resource management. His technical proficiency, leadership in academic settings, and dedication to sustainability make him a highly deserving candidate. With minor improvements in interdisciplinary collaboration and global outreach, his impact on the geoscience field could expand even further, contributing to more innovative and sustainable solutions in the industry.

📚Publications 

  1. Spatial distribution and trace element geochemistry of laterites in Kunche area: Implication for gold exploration targets in NW, Ghana
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Journal of African Earth Sciences, 158, 103519 (2019)
    Citations: 34

 

  1. Data Centric Blockchain-Based Evaluation Approach to Analyze E-Commerce Reviews Using Machine and Deep Learning Techniques
    Authors: E.M. Acheampong, S. Zhou, Y. Liao, P. Atandoh, D. Addo, E. Antwi-Boasiako, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Enhanced Word Embedding with CNN Using Word Order Information for Sentiment Analysis
    Authors: P. Atandoh, Z. Fengli, P.A. Hakeem, E.M. Acheampong, D. Addo, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Assessing Landsat-9 in Identifying Lithology Using a Hybrid Metric-Learning and SVM Method Against Baseline Algorithms: A Case Study of the West African Craton
    Authors: M. Appiah-Twum, H. Jia, W. Xu
    Conference: IGARSS 2023 – IEEE International Geoscience and Remote Sensing Symposium
    Citations: 1

 

  1. Using Laterite Geochemistry for Exploration of Orogenic Gold Deposits in the Wa-Lawra Belt, NW Ghana: Kunche in Perspective
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(3), 1137 (2018)
    Citations: 1

 

  1. DenseViT: A Hybrid CNN-Vision Transformer Model for an Improved Multisensor Lithological Classification
    Authors: M. Appiah-Twum, W. Xu, E.M. Acheampong
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. An Attention-Based LSTM Lithological Classification Using Multisensor Datasets
    Authors: M. Appiah-Twum, W. Xu
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. Lithological Classification Using Densely Connected Convolution Network on Landsat-9 and Aster Datasets in a Semi-Arid Environment
    Authors: M. Appiah-Twum, X. Wenbo, C.B. Mawuli, P. Atandoh
    Conference: 2023 20th International Computer Conference on Wavelet Active Media (2023