Sucheta Pradhan | Data Analysis | Best Researcher Award

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Ms. Sucheta Pradhan | Data Analysis | Best Researcher Award

Melbourne University | Australia

Sucheta Pradhan is a dedicated researcher currently pursuing her Doctor of Philosophy (PhD) in Engineering and IT at the University of Melbourne, Australia, under the Department of Infrastructure Engineering, where her thesis focuses on “An investigation into Atmospheric Rivers and their potential impact on extreme rainfall and flooding in Australia.” She holds a Master of Technology in Land and Water Resource Engineering from the Indian Institute of Technology (IIT) Kharagpur, with an impressive CGPA of 9.34/10, and a Bachelor of Technology in Agricultural Engineering from Odisha University of Agriculture and Technology, Bhubaneswar, where she graduated as a Gold Medalist with a CGPA of 8.76/10. Her research explores climate extremes, hydrology, and atmospheric science, with publications in reputed journals such as the Journal of Hydrology, and manuscripts under review in Weather and Climate Extremes and Communications Earth & Environment. She has presented her work at international forums including the EGU General Assembly (2022, 2025) and AGU Fall Meeting (2021). Alongside her research, she has served as a tutor for several environmental and engineering courses at the University of Melbourne. Sucheta is a national rank holder in the 2020 GATE Examination (AIR 106) and recipient of multiple academic honors, including OUAT Merit Scholarship and postgraduate stipends. She has also completed professional training in Data Analytics with Python (IIT Roorkee), Remote Sensing and GIS, and industrial internships in solar systems and agricultural machinery. Her academic journey reflects a strong commitment to advancing research on climate-induced hydrological risks and sustainable environmental solutions.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

"Atmospheric rivers and Australian precipitation: Impact of detection algorithm choice," S Pradhan, C Wasko, MC Peel, Journal of Hydrology, 2025

"Atmospheric Rivers intensify extreme precipitation and flooding across Australia," S Pradhan, C Wasko, MC Peel, Weather and Climate Extremes, 2025

"Global scale impact of atmospheric rivers on the severity of flooding", MP Sucheta Pradhan, Conrad Wasko EGU General Assembly Conference Abstracts, 2025

"Multivariate Approach Reveals a Higher Likelihood of Compound Heat Stress-Pluvial Floods in Urban India", P Ganguli, S Pradhan, Authorea Preprints, 2022

"Multivariate Approach Reveals a Higher Likelihood of Compound Warm-wet Spells in Urban India" S Pradhan, P Ganguli, EGU General Assembly Conference Abstracts, 2022

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.