Chia Yen Pao | Environmental Forecasting | Best Researcher Award

Best Researcher Award

Chia Yen Pao — National Dong Hwa University, Taiwan

Chia Yen Pao
Affiliation National Dong Hwa University
Country Taiwan
Documents 1
Subject Area Environmental Forecasting
Event International Environmental Scientists Award
ORCID 0009-0007-6916-2234

Chia Yen Pao is a researcher affiliated with National Dong Hwa University in Taiwan whose research profile is associated with environmental forecasting and data-driven environmental monitoring. Available publication records identify work involving multimodal sensing, edge computing, predictive modelling, and environmental change forecasting. [1]

Abstract

The Best Researcher Award profile recognizes Chia Yen Pao for research activity within Environmental Forecasting at National Dong Hwa University. Recent scholarly work associated with Chia-Yen Pao examines edge artificial intelligence, multimodal sensor fusion, and predictive environmental monitoring, demonstrating an interdisciplinary connection between computing and environmental applications. [1]

Keywords

Environmental forecasting; edge artificial intelligence; multimodal sensor fusion; environmental monitoring; predictive modelling; smart aquaculture; National Dong Hwa University.

Introduction

Environmental forecasting increasingly combines sensing technologies, computational intelligence, and predictive analytics to support timely interpretation of changing environmental conditions. Pao’s documented research applies these approaches to environmental monitoring and forecasting, particularly through edge-based computational architectures. [2]

Research Profile

The supplied academic profile identifies Environmental Forecasting as the principal subject area and records one document. The ORCID identifier 0009-0007-6916-2234 provides a persistent researcher identifier for distinguishing scholarly activity and publications. [3]

Research Contributions

A documented contribution describes an IoT environmental prediction framework using multimodal water-quality data and a 1D-CNN-LSTM model deployed on ESP32 edge-computing nodes. The study addresses environmental change prediction using water level, temperature, and turbidity information. [1]

Publications

A recent publication by Chia-Yen Pao and Po-Hao Chang, published in Electronics in 2026, presents an edge AI-driven multimodal sensor-fusion approach for environmental forecasting in smart aquaculture monitoring. The article is identified by DOI 10.3390/electronics15194426. [1]

Research Impact

The research demonstrates how low-latency edge computing and predictive models can be integrated into environmental monitoring systems. Its reported forecasting framework illustrates potential value for early identification of environmental anomalies and responsive management of monitored conditions. [1]

Award Suitability

The profile is relevant to the Best Researcher Award because the documented work connects computational methods with environmental forecasting and applied monitoring. The combination of environmental applications, predictive analytics, and emerging edge technologies provides an identifiable basis for scholarly recognition in the stated subject area.

Conclusion

Chia Yen Pao’s documented research profile reflects an interdisciplinary approach to Environmental Forecasting, with emphasis on predictive environmental monitoring and edge-based computational methods. The available publication record provides a scholarly basis for consideration within the Best Researcher Award category.

References

  1. Pao, C.-Y., & Chang, P.-H. (2026). Edge AI-Driven Multimodal Sensor Fusion for Environmental Forecasting in Smart Aquaculture Monitoring. Electronics, 15(19), 4426.
    https://doi.org/10.3390/electronics15194426
  2. National Dong Hwa University. Institutional and academic information.
  3. ORCID. ORCID record for Chia Yen Pao, ORCID iD 0009-0007-6916-2234.
    https://orcid.org/0009-0007-6916-2234
  4. Pao, C.-Y., Chang, P.-H., & related research records. Environmental forecasting and edge-computing research publication record.
  5. International Environmental Scientists Award. Official award website and nomination information.
    https://environmentalscientists.org/

Muhammad Rashid | Environmental Science | Research Excellence Award

Dr. Muhammad Rashid | Environmental Science | Research Excellence Award

Researcher | The University of University of Bari Aldo Moro | Italy

Dr. Muhammad Rashid is an emerging researcher in Environmental Science with expertise in hydrological modeling, groundwater surface water interaction, and climate change impact assessment. His research combines advanced tools such as GIS, remote sensing, and machine learning to evaluate flood risks, groundwater sustainability, and land-use dynamics. He has contributed to interdisciplinary studies focusing on environmental resilience, water resource optimization, and predictive modeling for hydrological extremes. With 5 research documents, 17 citations, and an h-index of 3, his work highlights the integration of data-driven methodologies to address complex environmental challenges. His research supports sustainable development goals by improving water management strategies and enhancing understanding of climate-driven hydrological processes, contributing to innovative and scalable solutions in environmental science.

                            Citation Metrics ( Scopus )

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15

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17
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Featured Publications

Richard Usang | Environmental Monitoring and Management | Best Researcher Award

Dr Richard Usang | Environmental Monitoring and Management | Best Researcher Award

Senior Data Scientist, Heineken UK, United Kingdom  📘

Dr. Richard Usang is a distinguished Chemistry expert and Data Scientist based in Southampton, United Kingdom. With a Ph.D. in Industrial & Environmental Chemistry and an MSc in Data Science, he has seamlessly integrated scientific research with advanced data analytics. His expertise spans industrial chemistry, environmental sustainability, artificial intelligence, and machine learning. Dr. Usang has a strong background in academic research, technical writing, and data-driven decision-making. His passion for innovation and problem-solving has led him to work on projects that bridge the gap between chemistry and AI, optimizing industrial processes and contributing to cutting-edge technological advancements.

Profile

Orcid

Education 🎓

Dr. Usang holds an MSc in Data Science from the University of Sussex, United Kingdom, which he completed in September 2023. Prior to this, he earned a Ph.D. in Industrial & Environmental Chemistry from the University of Ibadan, Nigeria, in August 2021. His academic journey also includes an MSc in Industrial Chemistry, which he completed in November 2014, ranking in the top 1% of his class. His foundation in chemistry was established with a BSc in Chemistry from Benue State University, Nigeria, where he graduated as the top-ranking student in July 2011. His strong academic background reflects his commitment to excellence in scientific research and technological advancements.

Professional Experience 💼

Dr. Usang currently serves as a Senior Data Scientist at Heineken UK, where he leads the development of Structural Equation Modelling frameworks to evaluate brand power and guide strategic marketing decisions. He has successfully implemented predictive models to optimize brewing parameters, reducing production variability and improving product quality. Previously, as a Lead Data Analyst at EMCOR UK, he significantly improved operational efficiency by reducing maintenance reporting time from three weeks to just four hours.

His tenure as a Data Scientist at The Heineken Company (2020–2022) saw him analyzing water chemistry across brewery sites, optimizing treatment processes, and reducing water treatment costs by 15%. He also developed forecasting models using machine learning, which led to a 10% reduction in overstock and a 5% increase in customer satisfaction. Prior to this, he worked as a Brewing Process Specialist at Heineken, overseeing production processes, training staff, and managing the installation of an anaerobic wastewater treatment plant in line with sustainability goals.

Dr. Usang’s academic career includes his role as a Research Assistant at the University of Ibadan, where he conducted extensive research on chemical processes and environmental impact. He contributed to multiple peer-reviewed publications and played a key role in mentoring undergraduate students in laboratory techniques and scientific analysis.

Research Interests 🔬

Dr. Usang’s research interests lie at the intersection of chemistry, data science, and artificial intelligence. His expertise in Industrial and Environmental Chemistry drives his passion for sustainable solutions in manufacturing and waste management. He is highly skilled in machine learning, AI model evaluation, and natural language processing, which he applies to scientific data interpretation and optimization. His work in statistical and quantitative analysis supports his research in predictive modeling and AI-driven decision-making for industrial applications. His interdisciplinary approach ensures that his research contributes both to scientific knowledge and practical industrial solutions.

Awards and Recognitions 🏆

Dr. Usang has earned numerous accolades throughout his academic and professional journey. He ranked first in his class during his BSc in Chemistry at Benue State University, a testament to his academic excellence. During his MSc in Industrial Chemistry at the University of Ibadan, he was among the top 1% of his cohort. His contributions to research and innovation have been recognized through international conferences and symposiums, where he has presented groundbreaking studies on chemical modifications and sustainability. His achievements in the corporate sector, particularly in data science applications in the brewing industry, further highlight his commitment to excellence and innovation.

Publications 📚

Integrating Principal Component Analysis, Fuzzy Inference Systems, and Advanced Neural Networks for Enhanced Estuarine Water Quality Assessment (2025). Published in Journal of Hydrology: Regional Studies. Link

Effect of Chemical Modification on the Functional and Physicochemical Properties of Some Underutilized Starches. Presented at the 2nd International Conference on Scientific Research and Innovation, University of Ibadan, Nigeria.

Synthesis, Aqueous Solubility Studies, and Antifungal Activity Test of Some Tributyltin(IV) Carboxylates.

Conclusion ✅

Dr. Richard Usang is a highly qualified candidate for the Best Researcher Award, bringing a unique blend of Chemistry and Data Science expertise. His contributions to industrial chemistry, environmental sustainability, and AI applications in research make him a strong contender. Strengthening his publication record and expanding academic leadership roles could further solidify his standing in the field. 🚀