Magata Mangatane | Satellite | Young Researcher Award

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Mr. Magata Mangatane | Satellite | Young Researcher Award

Magata Mangatane at University Of Cape Town, South Africa

Magata Jesaya Mangatane is a final-year PhD candidate in Ocean and Atmosphere Science at the University of Cape Town, specializing in satellite remote sensing and numerical ocean modeling. With a strong foundation in physical oceanography, he has built technical proficiency in Python, MATLAB, Fortran, and shell scripting, leveraging high-performance computing systems to investigate air-sea-ice interactions in the Southern Ocean. Jesaya is passionate about climate and ocean research and has experience in fieldwork, teaching, and collaborative international research.

Professional Profile:

Orcid

Google Scholar

Education Background

Jesaya earned his BSc in Ocean and Atmosphere Science and Archaeology from the University of Cape Town (UCT) in 2019, followed by a BSc Honours in Ocean and Atmosphere Science in 2020, awarded with first-class honors and a departmental medal. He began his MSc by dissertation at UCT in 2021, which was upgraded to a PhD in 2022. His current research focuses on the role of sea-ice type and thickness in vertical exchanges in the Southern Ocean, with a provisional submission date of December 2025.

Professional Development

Jesaya has served as a lecturer and practical demonstrator at UCT, contributing to courses such as SEA3004F (Ocean and Atmosphere Dynamics), where he teaches the application of MATLAB and Python for analyzing observational and model data. He has also held leadership roles including representing Early Career Researchers in the Marine and Antarctic Research center for innovation and sustainability (MARiS), and serving on the UCT Oceanography postgraduate committee. His international engagements include advanced NEMO modeling training and collaborative research with the Euro-Mediterranean Center on Climate Change in Italy.

Research Focus

His research interests include sea-ice modeling, satellite altimetry, high-resolution ocean circulation models, air-sea interactions, and climate variability in polar regions. Jesaya is particularly focused on improving the understanding of ocean-ice-atmosphere coupling using both observational data and model simulations, with an emphasis on the Southern Ocean.

Author Metrics:

Jesaya is the first author of a peer-reviewed publication in Remote Sensing titled “Intercomparison of Antarctic Sea-Ice Thickness Estimates from Satellite Altimetry and Assessment over the 2019 Data-Rich Year” (2025). He has also presented his work at several international conferences, including ICSHMO 2025 and the CRiceS annual meeting, showcasing his comparative analyses of satellite and model-derived sea-ice data.

Awards and Honors:

Jesaya was awarded first-class honors and the class medal for his BSc Honours in Oceanography in 2021. He was also named to the University of Cape Town Dean’s Merit List in 2019 for consistent academic excellence. These accolades reflect his dedication to academic and research excellence throughout his studies.

Publication Top Notes

1. Intercomparison of Antarctic Sea-Ice Thickness Estimates from Satellite Altimetry and Assessment over the 2019 Data-Rich Year

  • Authors: MJ Mangatane, M Vichi
  • Journal: Remote Sensing
  • Volume/Page: 1180
  • Year: 2025
  • DOI/Link: [Provide DOI or journal link if available]
  • Summary: This study compares Antarctic sea-ice thickness estimates derived from IceSat-2 and CryoSat-2 satellite altimetry during the data-rich year of 2019. The intercomparison provides insights into spatial-temporal variations and assesses the consistency and uncertainties in the satellite-derived estimates.

2. Antarctic Sea-Ice Thickness from IceSat-2 and CryoSat-2 Satellites

  • Authors: M Mangatane, M Vichi
  • Conference/Programme: South African National Antarctic Programme (SANAP)
  • Year: 2024
  • Event Type: Poster/Oral Presentation / Technical Report (specify if known)
  • Summary: This work presents a comprehensive dataset and analysis of Antarctic sea-ice thickness derived from the IceSat-2 and CryoSat-2 satellites under SANAP. The study aims to enhance regional understanding of polar sea-ice behavior using multi-mission satellite synergy.

Conclusion

Magata Jesaya Mangatane exemplifies the qualities of an emerging scientific leader in the field of satellite remote sensing and oceanography. His research is not only technically robust and methodologically innovative but also addresses key questions in climate science and polar processes. Jesaya’s dedication, scholarly achievements, and growing influence in the field make him a compelling and deserving candidate for the Research for Young Researcher Award.

With continued growth in publication, communication, and interdisciplinary outreach, he is well-positioned to become a pivotal figure in advancing satellite-based environmental research in the years to come.

Richard Usang | Environmental Monitoring | Best Researcher Award

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Dr. Richard Usang | Environmental Monitoring | Best Researcher Award

Senior Data Scientist at Heineken Uk, United Kingdom📖

Dr. Richard Usang is a distinguished Chemistry expert and Data Scientist with extensive experience in industrial and environmental chemistry, AI-driven analytics, and machine learning applications. His expertise spans advanced chemical research, data-driven decision-making, and AI model evaluation. With a Ph.D. in Industrial & Environmental Chemistry and an MSc in Data Science, he bridges the gap between scientific research and AI innovations. Dr. Usang has led impactful projects in predictive modeling, process optimization, and sustainability-driven solutions across various industries.

Profile

Orcid Profile

Education Background🎓

  • Ph.D. Industrial & Environmental Chemistry – University of Ibadan, Nigeria (2021)
  • MSc Data Science – University of Sussex, UK (2023)
  • MSc Industrial Chemistry (Top 1%) – University of Ibadan, Nigeria (2014)
  • BSc Chemistry (Ranked 1st) – Benue State University, Nigeria (2011)

Professional Experience🌱

Dr. Usang is currently a Senior Data Scientist at Heineken UK, where he applies AI and machine learning to optimize production processes and marketing strategies. He previously served as a Lead Data Analyst at EMCOR UK, significantly improving data processing efficiency. His earlier roles at The Heineken Company included Data Scientist and Brewing Process Specialist, where he spearheaded predictive modeling projects, optimized brewing parameters, and contributed to sustainability initiatives. He also held an academic position as a Research Assistant at the University of Ibadan, conducting groundbreaking research on chemical processes and environmental impact assessments.

Research Interests🔬

Her research interests include:

  1. AI-driven chemical data analysis and predictive modeling
  2. Sustainable industrial processes and environmental chemistry
  3. Machine learning applications in materials science
  4. AI content evaluation and Natural Language Processing in Chemistry

Author Metrics

Dr. Usang has authored several peer-reviewed publications on environmental chemistry, AI-driven water quality assessments, and sustainable waste management. Notable works include:

  1. “Integrating Principal Component Analysis, Fuzzy Inference Systems, and Advanced Neural Networks for Enhanced Estuarine Water Quality Assessment.”
  2. “Synthesis, Aqueous Solubility Studies, and Antifungal Activity Test of Some Tributyltin(IV) Carboxylates.”
  3. Conference presentations at TU Braunschweig, Germany, and the University of Ibadan, Nigeria.
Awards and Honors
  • Recognized among the Top 1% in MSc Industrial Chemistry
  • Best Graduate (1st Rank) in BSc Chemistry at Benue State University
  • Contributor to multiple industry-driven AI and sustainability initiatives
Publications Top Notes 📄
1.  Integrating Principal Component Analysis, Fuzzy Inference Systems, and Advanced Neural Networks for Enhanced Estuarine Water Quality Assessment
  • Authors: Richard O. Usang, Bamidele I. Olu-Owolabi, Kayode O. Adebowale
  • Journal: Journal of Hydrology: Regional Studies
  • Publication Date: January 2025
  • DOI: 10.1016/j.ejrh.2025.102182
  • ISSN: 2214-5818
Abstract:

This research integrates Principal Component Analysis (PCA), Fuzzy Inference Systems (FIS), and Advanced Neural Networks to develop a more robust and precise estuarine water quality assessment model. The study applies machine learning and statistical techniques to improve water quality monitoring, pollution prediction, and ecological sustainability. By leveraging fuzzy logic and artificial intelligence, the proposed framework enhances the decision-making process for environmental management.

Key Highlights:
  • PCA for Data Reduction: Identifies key water quality parameters affecting estuarine ecosystems.
  • Fuzzy Inference Systems: Enhances interpretability and decision-making in water quality assessment.
  • Advanced Neural Networks: Improves prediction accuracy for water pollution trends and environmental impact analysis.
  • Application in Environmental Sustainability: Provides insights into climate change effects on estuarine water systems.

Conclusion

Dr. Richard Usang is an outstanding researcher whose interdisciplinary expertise, AI-driven environmental innovations, and industry-academic contributions make him a top contender for the Best Researcher Award. Expanding his AI applications, increasing global collaborations, and enhancing industry-academia partnerships will further solidify his impact in environmental monitoring and AI-based sustainability solutions.