Congxi Fang | Atmospheric Science | Best Researcher Award

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Dr Congxi Fang | Atmospheric Science | Best Researcher Award

Assistant Researcher, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, China.

Dr. Congxi Fang is an Assistant Researcher at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences. He specializes in paleoclimatology, dendroclimatology, and climate-induced disasters in high mountain regions. Holding a Ph.D. in Environmental Science from the University of Chinese Academy of Sciences, Dr. Fang has led and contributed to over 30 peer-reviewed studies, including publications in Nature Communications and PNAS. His research focuses on the historical and future dynamics of meteorological and geological disasters, particularly in the Asian monsoon region. Dr. Fang’s work has significantly advanced the understanding of the ENSO-monsoon relationship and its impact on extreme weather events. He collaborates with institutions like the Institute of Earth Environment and Xi’an Jiaotong University, contributing to the reconstruction of climate records spanning millennia. Dr. Fang’s dedication to climate science positions him as a leading figure in his field.

Profiles

Scopus

Orcid

Education

Dr. Congxi Fang earned his Ph.D. in Environmental Science from the University of Chinese Academy of Sciences, where he specialized in paleoclimatology and dendroclimatology. His doctoral research focused on reconstructing historical climate patterns using tree-ring data and other proxies, providing insights into the Asian monsoon system’s variability over centuries. During his academic tenure, Dr. Fang developed expertise in analyzing paleoclimate records, contributing to a deeper understanding of climate dynamics in high-altitude regions. His educational background laid the foundation for his current research endeavors, which involve interdisciplinary approaches to studying climate change and its associated hazards. Dr. Fang’s commitment to academic excellence is evident in his extensive publication record and ongoing collaborations with leading research institutions.

Experience

Dr. Congxi Fang serves as an Assistant Researcher at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences. In this role, he leads research projects focusing on historical meteorological disaster analysis, future disaster prediction, and the evolution of meteorological and geological disasters in high mountain regions of Asia. Dr. Fang has completed three major research projects and has published 37 SCI-indexed papers. His work involves reconstructing past climate events to understand current trends and predict future scenarios, particularly concerning the Asian monsoon and ENSO phenomena. Dr. Fang collaborates with institutions such as the Institute of Earth Environment and Xi’an Jiaotong University, contributing to multidisciplinary studies that inform disaster risk management and climate policy. His experience encompasses fieldwork, data analysis, and modeling, making him a valuable asset in the field of climate science.

Research Focus

Dr. Congxi Fang’s research centers on climate changes, paleoclimatology, and meteorological disasters, with a particular emphasis on high mountain regions in Asia. He investigates the historical patterns of climate variability, utilizing tree-ring data and other proxies to reconstruct past climate events. Dr. Fang’s work sheds light on the ENSO-monsoon relationship and its influence on extreme weather occurrences, such as heavy rainfall and droughts. His studies aim to understand the long-term evolution of meteorological and geological disasters, providing insights into future disaster prediction and risk assessment. By collaborating with various research institutions, Dr. Fang contributes to multidisciplinary approaches that enhance the understanding of climate dynamics and inform strategies for disaster mitigation and climate adaptation.

Publication Top Notes

  1. Climate Change in Southeast Tibet and Its Potential Impacts on Cryospheric Disasters
    Atmosphere, 2025-05-05
    DOI: 10.3390/atmos16050547
    Summary: This study examines the effects of climate change in Southeast Tibet, focusing on its implications for cryospheric disasters such as glacial lake outburst floods. The research highlights the increasing risks associated with warming temperatures and melting glaciers in the region.

  2. Recent Centennial Drought on the Tibetan Plateau is Outstanding Within the Past 3500 Years
    Nature Communications, 2025-02-03
    DOI: 10.1038/s41467-025-56687-z
    Summary: This paper presents a comprehensive analysis of drought patterns on the Tibetan Plateau, revealing that recent droughts are among the most severe in the past 3500 years. The findings suggest a link between these extreme events and anthropogenic climate change.Nature

  3. Historical Soil Moisture Variability in High‐Latitude Humid Regions: Insights From a Paleoclimate Data‐Model Comparison
    Earth’s Future, 2024-05
    DOI: 10.1029/2023EF004017
    Summary: This research combines paleoclimate data and modeling to investigate historical soil moisture variability in high-latitude humid regions, providing insights into past hydrological changes and their relevance to current climate trends.

  4. Enhanced Variability and Declining Trend of Soil Moisture Since the 1880s on the Southeastern Tibetan Plateau
    Water Resources Research, 2023-03
    DOI: 10.1029/2022WR033953
    Summary: The study analyzes soil moisture records from the southeastern Tibetan Plateau, identifying a significant decline and increased variability since the 1880s, which has implications for regional water resources and ecosystem stability.

  5. How is the El Niño–Southern Oscillation Signal Recorded by Tree‐Ring Oxygen Isotopes in Southeastern China?
    International Journal of Climatology, 2022-10
    DOI: 10.1002/joc.7601
    Summary: This paper explores the relationship between ENSO events and tree-ring oxygen isotope records in southeastern China, demonstrating the potential of dendroclimatology in reconstructing historical climate variability.

  6. Evolution of the Dry-Wet Variations Since 1834 CE in the Lüliang Mountains, North China and Its Relationship with the Asian Summer Monsoon
    Ecological Indicators, 2021
    DOI: 10.1016/j.ecolind.2020.107089
    Summary: The study reconstructs historical dry-wet variations in the Lüliang Mountains and examines their connection to the Asian summer monsoon, providing insights into regional climate dynamics over the past two centuries.

  7. Why Does Extreme Rainfall Occur in Central China During the Summer of 2020 After a Weak El Niño?
    Advances in Atmospheric Sciences, 2021-12
    DOI: 10.1007/s00376-021-1009-y
    Summary: This paper investigates the causes of extreme rainfall in Central China during the summer of 2020, analyzing the interplay between ENSO events and regional atmospheric conditions.

  8. A 210-Year Tree-Ring δ¹⁸O Record in North China and Its Relationship with Large-Scale Circulations
    Tellus B: Chemical and Physical Meteorology, 2020
    DOI: 10.1080/16000889.2020.1770509
    Summary: The research presents a 210-year tree-ring oxygen isotope record from North China, linking it to large-scale atmospheric circulation patterns and enhancing the understanding of historical climate variability.

  9. An Asian Summer Monsoon-Related Relative Humidity Record from Tree-Ring Δ¹⁸O in Gansu Province, North China
    Atmosphere, 2020
    DOI: 10.3390/atmos11090984
    Summary: This study reconstructs relative humidity variations associated with the Asian summer monsoon using tree-ring oxygen isotope data from Gansu Province, offering insights into past monsoon dynamics.

  10. Delayed Warming in Northeast China: Insights from an Annual Temperature Reconstruction Based on Tree-Ring δ¹⁸O
    Science of the Total Environment, 2020
    DOI: 10.1016/j.scitotenv.2020.141432
    Summary: The paper reconstructs annual temperature variations in Northeast China using tree-ring oxygen isotope data, revealing a delayed warming trend compared to global averages.

Conclusion

Dr. Congxi Fang is a highly qualified and deserving candidate for the Best Researcher Award. His prolific publication record, rigorous climate reconstructions, and contributions to understanding paleoclimate–monsoon dynamics in high-risk Asian regions exemplify scholarly excellence. Although his profile would benefit from expanded leadership visibility and formal professional affiliations, his scientific impact, thematic relevance, and quality of research clearly justify strong consideration for this award.

Satish Kabade | Computer Science and Artificial Intelligence | Best Industrial Research Award

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Mr Satish Kabade | Computer Science and Artificial Intelligence | Best Industrial Research Award

Product Technical Expert, Communication Experts, United States

Satish Kabade is a seasoned IT Consultant and Solutions Architect with over 17 years of experience in software development, enterprise architecture, and cloud computing. He is renowned for his expertise in Microsoft .NET and Azure technologies, leading cross-functional teams to deliver scalable, high-performing solutions. Satish has been instrumental in integrating AI and Machine Learning into pension management systems, enhancing automation, risk analysis, and predictive analytics. His work includes developing AI-driven fraud detection algorithms, personalized retirement benefit recommendations, and AI-based chatbots for member inquiries. He holds certifications as an Azure Solution Architect, TOGAF 9 Certified Architect, and Certified Scrum Master. Satish is also a mentor, conducting workshops on design patterns, best coding practices, cloud migration strategies, and AI/ML implementation.

Profile

Google Scholar

Education 

Satish Kabade’s educational background reflects a strong foundation in technology and cloud computing. He completed a Post Graduate Program in Cloud Computing from Great Learning in 2021, equipping him with advanced knowledge in cloud technologies. Prior to this, he earned a Post Graduate Diploma in Computer Applications from CDAC, Pune, in 2006, which provided him with a comprehensive understanding of software development and computer science principles. His academic journey began with a Bachelor of Engineering in Mechanical Engineering from Shivaji University, Solapur, in 2004, showcasing his analytical and problem-solving skills. This diverse educational background has enabled Satish to bridge the gap between traditional engineering and modern IT solutions, making significant contributions to the integration of AI and cloud technologies in various domains, particularly in pension management systems.

Experience 

With over 17 years in the IT industry, Satish Kabade has amassed extensive experience in software development, enterprise architecture, and cloud computing. He has designed and developed full-stack solutions using .NET Core, C#, ASP.NET, and AWS cloud technologies, ensuring seamless integration between front-end and back-end components. Satish has leveraged AWS Cloud services such as EC2, S3, Lambda, and RDS to deploy, scale, and manage cloud-based applications, ensuring high availability and fault tolerance. His expertise extends to integrating AI and Machine Learning solutions into pension management systems, enhancing automation, risk analysis, and predictive analytics. Notably, he has developed AI/ML-based predictive analytics for retirement planning and investment forecasting, improving decision-making for pension fund administrators and members. Additionally, Satish has implemented AI-driven fraud detection algorithms for pension disbursements and payroll processing, minimizing risks and ensuring regulatory compliance.

Research Focus

Satish Kabade’s research focus centers on the integration of Artificial Intelligence (AI) and Machine Learning (ML) into pension management systems to enhance automation, risk analysis, and predictive analytics. He has developed AI/ML-based predictive analytics for retirement planning and investment forecasting, enabling improved decision-making for pension fund administrators and members. His work includes implementing AI-driven fraud detection algorithms for pension disbursements and payroll processing, minimizing risks and ensuring regulatory compliance. Satish has also designed and implemented Machine Learning models for personalized retirement benefit recommendations, leveraging historical contribution data and economic trends. Additionally, he has developed AI-based chatbots and virtual assistants for member inquiries, streamlining benefits administration and customer support. His research aims to improve the efficiency, security, and personalization of pension systems, contributing to the broader field of AI applications in financial services.

Publication Top Notes

  1. “AI-Driven Financial Management: Optimizing Investment Portfolios through Machine Learning”

    • Authors: T.V. Ambuli, S. Venkatesan, K. Sampath, Kabirdoss Devi, S. Kumaran

    • Published: August 2024

    • Conference: 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT)

    • Summary: This paper explores the application of AI and ML in optimizing investment portfolios, focusing on enhancing financial management strategies through advanced computational techniques.

  2. “A Machine Learning Model for Algorithmic Optimization of Superannuation Schemes”

    • Authors: Winfred Katile Mukunzi, Brian Wesley Muganda, Bernard Shibwabo

    • Published: October 2024

    • Summary: The study develops a machine learning-based recommendation model for optimal asset portfolio selection and allocation in superannuation schemes, addressing challenges in financial market uncertainties.

  3. AI-Driven Fraud Detection in Investment and Retirement Accounts
    Author: Ajay Benadict Antony Raju
    Published in: ESP International Journal of Advancements in Computational Technology, Volume 2, Issue 1, 2024

    Summary:
    This paper discusses the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in detecting fraudulent activities within investment and retirement accounts. It highlights the limitations of traditional fraud detection methods and emphasizes the advantages of AI and ML in analyzing large datasets to identify patterns indicative of fraudulent behavior. The study underscores the importance of integrating AI-driven approaches to enhance the security and integrity of financial systems.ESP Journals

  4.  Enhancing AI-Based Financial Fraud Detection with Blockchain
    Authors: Prof. Kumar Lui, Prof. Kusal Fisher, Prof. Shyam Raj
    Published in: International Journal of Holistic Management Perspectives, Volume 4, Issue 4, 2023

    Summary:
    This article explores the integration of Blockchain technology with AI-based financial fraud detection systems. It examines how blockchain’s decentralized and immutable nature can complement AI models to provide more robust and transparent fraud detection mechanisms. The paper discusses various use cases and the potential benefits of combining these technologies to combat financial fraud effectively.

Conclusion

Satish Kabade is a highly capable technologist and applied researcher, especially in AI/ML integration within legacy government and pension systems. His work shows clear innovation, enterprise-scale application, and practical relevance, which are key strengths for industrial research recognition. However, for a Best Industrial Research Award, the lack of formal research dissemination (papers, presentations, patents) may be a limiting factor unless the award heavily favors applied over academic research.

Nana Chang | Power System Protection | Best Researcher Award

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Dr. Nana Chang | Power System Protection | Best Researcher Award

Lecturer, School of Electrical Engineering, Xi’an University of Technology, China

Dr. Nana Chang is a distinguished researcher in electrical engineering, specializing in power system protection and renewable energy integration. She earned her Ph.D. in Electrical Engineering from Xi’an Jiaotong University in 2024, following a Master’s degree from North China Electric Power University and a Bachelor’s from Xi’an University of Technology. Currently serving as a Lecturer at Xi’an University of Technology, Dr. Chang bridges academia and industry through her involvement in several high-impact research projects. Her work addresses critical challenges in modern power systems, including fault protection in multi-voltage DC grids and resilience under extreme conditions. Dr. Chang has contributed to multiple national-level projects funded by the Ministry of Science and Technology and the National Natural Science Foundation of China. She also leads industry-sponsored research, focusing on innovative protection principles for renewable energy-dominated grids.

Profile

Orcid

Education

Dr. Nana Chang’s academic journey reflects a strong foundation in electrical engineering. She completed her Bachelor of Science in Electrical Engineering and Automation at Xi’an University of Technology in June 2012. Pursuing advanced studies, she obtained a Master of Science in Power System and Automation from North China Electric Power University (Beijing) in April 2015. Her academic pursuit culminated in a Doctor of Philosophy in Electrical Engineering from Xi’an Jiaotong University in September 2024. Her doctoral research focused on innovative protection methods for multi-voltage-level, multi-zone interconnected new energy DC distribution systems, addressing the evolving challenges in modern power systems. This progression showcases her commitment to advancing the field of electrical engineering through rigorous academic training and research.

Experience

Dr. Nana Chang’s professional experience spans both academia and industry, highlighting her expertise in electrical engineering. Since September 2024, she has been serving as a Lecturer at Xi’an University of Technology, where she contributes to the academic development of students and engages in cutting-edge research. Prior to her academic role, Dr. Chang worked at State Grid Xianyang Power Supply Company from August 2015 to June 2019, focusing on the secondary equipment maintenance of substations. This experience provided her with practical insights into power system operations and maintenance, enriching her research perspective. Her dual exposure to theoretical and practical aspects of electrical engineering enables her to bridge the gap between academic concepts and real-world applications effectively.

Research Focus 

Dr. Nana Chang’s research is centered on the protection and resilience of modern power systems, particularly in the context of renewable energy integration. Her doctoral research addressed fault characteristics and protection methods for multi-voltage-level, multi-zone interconnected new energy DC distribution systems, a critical area as the energy sector transitions toward decentralized and renewable sources. She is actively involved in projects funded by the Ministry of Science and Technology and the National Natural Science Foundation of China, focusing on protection strategies for flexible low-frequency transmission systems and resilience technologies for urban energy systems under extreme conditions. Additionally, Dr. Chang leads industry-sponsored research on innovative protection principles for renewable energy-dominated grids. Her work aims to enhance the reliability and stability of power systems amidst the challenges posed by renewable energy sources.

Publication Top Notes

📘1. Phase Current Based Fault Section Location for Single-Phase Grounding Fault in Non-Effectively Grounded Distribution Network

  • Journal: IEEE Transactions on Industry Applications

  • Year: 2025

  • Authors: Zhongxue Chang, Qingyu He, Nana Chang, Weibin Tan, Wei Zhang, Zhihua Zhang, Guobing Song

  • Summary:
    This paper proposes a novel phase current-based method to locate fault sections caused by single-phase grounding in non-effectively grounded distribution networks. The approach enhances fault localization accuracy in complex systems where conventional methods fall short. The solution reduces misjudgment rates and increases system reliability in medium-voltage power networks, especially relevant to regions with high renewable penetration.

📘 2. Adaptive Fault Identification for Multi-Level Relays Using Fault Tree and User-Defined Inverse-Time Characteristics Equation

  • Journal: Electric Power Systems Research

  • Year: September 2025

  • Authors: Nana Chang, Guobing Song, Jiaheng Jiang

  • Summary:
    This study introduces an adaptive method for fault identification in multi-level relay systems. By combining a fault tree analysis framework with user-defined inverse-time characteristics, the method provides more precise fault detection under variable grid configurations. The adaptive behavior supports more intelligent and flexible relay coordination, particularly important for evolving smart grid environments.

📘 3. An Adaptive Coordinated Wide-Area Backup Protection Algorithm for Network Topology Variability

  • Journal: IEEE Transactions on Power Delivery

  • Year: April 2024

  • Authors: Nana Chang, Guobing Song

  • Summary:
    This paper presents a wide-area backup protection algorithm that adapts to real-time changes in power system topology. The method dynamically adjusts coordination parameters based on topology recognition, improving fault response and ensuring system stability in large-scale and reconfigurable grids. It offers significant improvements in response speed and adaptability for modern interconnected systems.

📘 4. Fault Identification Method Based on Unified Inverse-Time Characteristic Equation for Distribution Network

  • Journal: International Journal of Electrical Power & Energy Systems

  • Year: March 2023

  • Authors: Nana Chang, Guobing Song, Junjie Hou, Zhongxue Chang

  • Summary:
    This article introduces a unified fault identification method for distribution networks using a standardized inverse-time characteristic equation. The technique enhances the coordination of protection devices across diverse protection zones. It is particularly suited for high-penetration renewable energy systems, where conventional settings may not provide reliable fault discrimination due to dynamic operating conditions.

Conclusion

Dr. Nana Chang demonstrates strong technical competence, relevance in research areas, and a well-rounded background in academic and industrial projects. Her work directly contributes to critical advancements in power system protection and renewable energy integration, areas vital to modern energy infrastructure.

Mohammad Mahdavian | Surface Coatings and Corrosion | Best Researcher Award

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Prof. Mohammad Mahdavian | Surface Coatings and Corrosion | Best Researcher Award

Professor, Institute for Color Science and Technology, Iran.

Dr. Mohammad Mahdavian is an esteemed Associate Professor at the Institute for Color Science and Technology (ICST) in Tehran, Iran, specializing in polymer engineering with a focus on surface coatings and corrosion protection. With over a decade of academic and industrial experience, he has significantly contributed to the development of advanced coating technologies, emphasizing sustainability and performance.

Profiles

Education

Dr. Mahdavian completed his Bachelor’s, Master’s, and Ph.D. degrees in Polymer Engineering at Amirkabir University of Technology (AUT), Tehran, Iran. His doctoral research, titled “Evaluation of corrosion inhibition of azole derivatives as alternatives to chromates,” earned him the distinction of top student with a GPA of 3.94. His academic journey reflects a deep commitment to advancing the field of polymer coatings and corrosion science.

Professional Experience

Dr. Mahdavian’s career spans both academia and industry. At ICST, he has held various positions, including Assistant Professor (2009–2011), Assistant Professor at Sahand University of Technology (2011–2013), and currently serves as Associate Professor since 2019. His industrial experience includes roles as Coating Scientist at Atlas Protecting Coating (APC) and Deputy of Paint Production Plant at Khosh Paint Company (KPC). Additionally, he has contributed to administrative services, such as Head of the International Scientific Cooperation Office at ICST and Secretary of the 6th International Color and Coating Congress in 2015.

Awards and Honors

Dr. Mahdavian’s exceptional contributions have been recognized internationally. He has been honored with the Distinguished Paper Award by the American Cleaning Institute in 2012. He was ranked among the top 1% in Materials Science & Cross-Field reviewers by Web of Science in 2019 and has been listed among the top 2% of scientists globally by Elsevier BV and Stanford University in 2020, 2021, and 2022. In 2023, he was selected as a Preeminent Scientist by the National Science Foundation of Iran and as an Outstanding Researcher by the Ministry of Science and Technology.

Research Focus

Dr. Mahdavian’s research encompasses the development of advanced polymer coatings, corrosion inhibitors, and nanocomposite materials. His work explores the synthesis and surface modification of nanoparticles, including graphene oxide, carbon nanotubes, and layered double hydroxides, for use in smart coatings with self-healing and anti-corrosion properties. He also investigates the application of metal-organic frameworks (MOFs) and clays in enhancing the performance of coatings. His interdisciplinary approach integrates electrochemistry, materials science, and nanotechnology to address challenges in corrosion protection.

Publication Top Notes

1. Enhancement of Barrier and Corrosion Protection Performance of an Epoxy Coating through Wet Transfer of Amino Functionalized Graphene Oxide

This study investigates the integration of amino-functionalized graphene oxide (GO) into epoxy coatings to enhance corrosion resistance. The modified coatings exhibited improved barrier properties and corrosion protection, demonstrating the potential of GO-based nanocomposites in protective coatings.

2. Glycyrrhiza Glabra Leaves Extract as a Green Corrosion Inhibitor for Mild Steel in 1 M Hydrochloric Acid Solution

The research explores the use of Glycyrrhiza glabra (licorice) leaf extract as a natural corrosion inhibitor for mild steel in acidic environments. The extract demonstrated significant corrosion inhibition, offering an eco-friendly alternative to traditional inhibitors.

3. Another Approach in Analysis of Paint Coatings with EIS Measurement: Phase Angle at High Frequencies

This paper presents an alternative method for analyzing paint coatings using Electrochemical Impedance Spectroscopy (EIS), focusing on phase angle measurements at high frequencies. The approach provides insights into the protective performance of coatings.

4. Covalently-Grafted Graphene Oxide Nanosheets to Improve Barrier and Corrosion Protection Properties of Polyurethane Coatings

The study examines the enhancement of polyurethane coatings by covalently grafting graphene oxide nanosheets. The modified coatings exhibited improved mechanical properties and corrosion resistance, highlighting the role of nanomaterials in coating performance.

5. Enhancement of the Corrosion Protection Performance and Cathodic Delamination Resistance of Epoxy Coating through Treatment of Steel Substrate by a Novel Nanometric Sol-Gel

This research investigates the application of a novel nanometric sol-gel treatment on steel substrates to enhance the corrosion protection and cathodic delamination resistance of epoxy coatings. The treatment led to significant improvements in coating performance.

6. Development of Metal-Organic Framework (MOF) Decorated Graphene Oxide Nanoplatforms for Anti-Corrosion Epoxy Coatings

The paper explores the development of metal-organic framework (MOF) decorated graphene oxide nanoplatforms for incorporation into epoxy coatings. The modified coatings demonstrated enhanced anti-corrosion properties, showcasing the potential of MOFs in protective coatings.

7. Effects of Highly Crystalline and Conductive Polyaniline/Graphene Oxide Composites on the Corrosion Protection Performance of a Zinc-Rich Epoxy Coating

This study investigates the incorporation of polyaniline/graphene oxide composites into zinc-rich epoxy coatings. The composites enhanced both cathodic protection and barrier properties, offering a dual mechanism for improved corrosion resistance.ADS

8. Corrosion Inhibition Performance of 2-Mercaptobenzimidazole and 2-Mercaptobenzoxazole Compounds for Protection of Mild Steel in Hydrochloric Acid Solution

The research evaluates the corrosion inhibition performance of 2-mercaptobenzimidazole and 2-mercaptobenzoxazole compounds for mild steel in hydrochloric acid. The study provides insights into the effectiveness of these compounds as corrosion inhibitors.

9. Persian Liquorice Extract as a Highly Efficient Sustainable Corrosion Inhibitor for Mild Steel in Sodium Chloride Solution

This paper examines the use of Persian liquorice extract as a sustainable corrosion inhibitor for mild steel in sodium chloride solution. The extract demonstrated high efficiency, offering an environmentally friendly alternative to traditional inhibitors.

10. Electrochemical Impedance Spectroscopy and Electrochemical Noise Measurements as Tools to Evaluate Corrosion Inhibition of Azole Compounds on Stainless Steel in Acidic Media

The study utilizes Electrochemical Impedance Spectroscopy (EIS) and Electrochemical Noise Measurements (ENM) to evaluate the corrosion inhibition of azole compounds on stainless steel in acidic media. The findings contribute to understanding the protective mechanisms of azole-based inhibitors.

Conclusion

Dr. Mohammad Mahdavian is a highly accomplished and internationally recognized researcher in the field of polymer coatings and corrosion protection. His robust publication record, impactful patents, academic leadership, and industrial collaborations form a compelling case for the Best Researcher Award. With continued expansion into international funding and science communication, he could further strengthen his candidacy for even broader global honors.

Providence Habumuremyi | Civil Engineering | Best Researcher Award

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Dr. Providence Habumuremyi | Civil Engineering | Best Researcher Award

Postdoctoral Fellow, Fuzhou University, China.

Dr. Providence Habumuremyi, born on January 1, 1988, in Rwanda, is a distinguished civil engineer specializing in tunnel stability and geotechnical engineering. Currently a postdoctoral fellow at Fuzhou University, China, he earned his Doctor of Engineering from Beijing Jiaotong University, focusing on three-dimensional analytical methods for tunnel face stability in undrained clay grounds. His academic journey includes a Master’s degree in Civil Engineering from the same university and a Bachelor’s degree from the University of Rwanda. Dr. Habumuremyi’s professional experience spans roles such as Civil Engineer at Beijing Jinghangan Airport Engineering Co., Ltd., contributing to international airport projects in the Maldives and Zambia. His multilingual abilities and cross-cultural experiences enhance his collaborative research endeavors. Recognized for his analytical skills and innovative approaches, Dr. Habumuremyi continues to impact the field through research, publications, and contributions to major engineering projects.

Profile

Orcid

🎓 Education

  • Doctor of Engineering in Civil Engineering
    Beijing Jiaotong University, China (09/2019 – 06/2024)
    Dissertation: Three-Dimensional Analytical Continuous Upper Bound Limit Analyses for Face Stability of Shallow Shield Tunneling in Undrained Clay Ground
    Supervisor: Prof. Yan-Yong Xiang

  • Master of Engineering in Civil Engineering
    Beijing Jiaotong University, China (09/2015 – 06/2017)
    Thesis: Friction Pendulum Systems for Seismic Isolation of Structures in Near-Fault Regions
    Supervisor: Prof. Lin LiuResearcher Discovery+1AGRIS+1

  • Bachelor of Science in Civil Engineering
    University of Rwanda (01/2011 – 08/2014)
    Supervisor: Prof. Park Ildong

🏗️ Experience

  • Postdoctoral Researcher
    Fuzhou University, China (11/2024 – Present)
    Research Focus: Tunnel stability, ground and structural dynamics, geotechnical engineering.

  • Inspector
    Beijing Jianyetong Engineering Testing Technology Co., Ltd. (07/2024 – 11/2024)
    Responsibilities: Preparation of construction drawings, on-site surveying, attending technical meetings.

  • Civil Engineer
    Beijing Jinghangan Airport Engineering Co., Ltd. (07/2017 – 09/2019)
    Projects: Expansion of Maldives Velana International Airport; Construction of Ndola Simon Mwansa Kapwepwe International Airport, Zambia.
    Responsibilities: Preparation of construction drawings, site supervision, technical meetings, translation of technical documents (Chinese to English).

  • Director of Studies
    Collegio Santo Antonio Maria Zaccaria (01/2015 – 09/2015)
    Responsibilities: Supervision of teachers, curriculum implementation follow-up, teaching Mathematics, Physics, Technical Drawing, Scaffolding.

🔬 Research Focus 

Dr. Habumuremyi’s research centers on the stability analysis of tunnel faces, particularly in undrained clay conditions. He employs analytical and computational methods, including three-dimensional upper bound limit analyses, to assess and enhance the safety of shallow shield tunneling operations. His work extends to geotechnical engineering, focusing on soil-structure interaction, and the dynamics of structures under seismic loading. By integrating tools like MATLAB, SAP2000, ABAQUS, and OPTUM G2 & G3, he develops models that predict structural responses to various geotechnical challenges. His interdisciplinary approach aims to improve construction practices and inform the design of resilient infrastructure.

📚 Publication Top Notes

1. A 3-D Analytical Continuous Upper Bound Limit Analysis for Face Stability of Shallow Shield Tunneling in Undrained Clays

Journal: Computers and Geotechnics, December 2023
DOI: 10.1016/j.compgeo.2023.105779
Authors: Providence Habumuremyi, Yanyong Xiang

Summary:
This paper introduces a three-dimensional (3D) analytical upper bound limit method to evaluate face stability in shallow shield tunneling through undrained clay. Unlike previous two-dimensional models, the authors developed a 3D continuous velocity field based on a logarithmic spiral failure mechanism, offering more accurate predictions. The method considers various tunnel depths, diameters, and face pressures.

Key Contributions:

  • Developed a new continuous 3D velocity field using upper bound limit analysis.

  • Applied to shield tunneling in undrained clay (e.g., soft cohesive soil in urban areas).

  • Validated against numerical simulations (ABAQUS), showing good agreement.

  • Provided design charts for practicing engineers.

Relevance:
This model improves the safety and efficiency of tunnel construction in soft ground by offering realistic estimations of the support pressure required to prevent face collapse.

2. Determining Trigger Factors of Soil Mass Failure in a Hollow: A Study Based in the Sichuan Province, China

Journal: CATENA, September 2022
DOI: 10.1016/j.catena.2022.106368
Authors: Jules Maurice Habumugisha, Ningsheng Chen, Mahfuzur Rahman, Providence Habumuremyi, Etienne Tuyishimire, et al.

Summary:
This study investigates the main triggering factors of soil mass failure (landslides) in a specific hollow area of Sichuan Province, China. It uses field data, geostatistics, and geotechnical analysis to assess slope failure causes. Key parameters include slope angle, rainfall, vegetation cover, and soil composition.

Key Contributions:

  • Combined field sampling, laboratory testing, and remote sensing.

  • Identified critical depth and shear strength thresholds for failure.

  • Proposed mitigation techniques, including improved land management and vegetative cover.

Relevance:
Essential for improving slope stability prediction and disaster risk reduction in landslide-prone mountainous regions.

3. Friction Pendulum Systems for Seismic Isolation of Structures in Near-Fault Regions

Type: Master’s Thesis
Date: May 20, 2017
DOI: 10.13140/RG.2.2.19943.15527
Author: Providence Habumuremyi

Summary:
This thesis evaluates the performance of Friction Pendulum Systems (FPS) for seismic isolation in buildings located in near-fault zones. Near-fault ground motions can be intense and impulsive, posing challenges to conventional structural designs. The study uses numerical simulations in SAP2000 to demonstrate how FPS can effectively decouple structures from strong ground motions.

Key Contributions:

  • Designed FPS models for medium-rise buildings.

  • Compared base-isolated structures with fixed-base ones under near-fault motion.

  • Showed significant reduction in base shear and inter-story drift with FPS.

Relevance:
Supports the use of FPS isolation technology in earthquake engineering, particularly for civil infrastructure near seismic faults.

4. Mitigation Measures for Wind Erosion and Sand Deposition in Desert Railways: A Geospatial Analysis of Sand Accumulation Risk

  • Journal: Sustainability, April 29, 2025

  • DOI: 10.3390/su17094016

  • Authors: Mahamat Nour Issa Abdallah, Tan Qulin, Mohamed Ramadan, Providence Habumuremyi

Summary:

This study presents a comprehensive geospatial analysis aimed at identifying and mitigating the risks associated with wind erosion and sand deposition along desert railway corridors. Utilizing advanced GIS tools and remote sensing data, the research identifies high-risk zones where sand accumulation poses significant threats to railway infrastructure. The authors evaluate various mitigation strategies, including the implementation of sand fences, vegetation barriers, and optimized track alignments, to reduce the impact of aeolian processes on railway operations.

Key Contributions:

  • Development of a geospatial risk assessment model for sand accumulation along railway lines.

  • Identification of critical zones susceptible to wind-induced sand deposition.

  • Evaluation of mitigation measures and their effectiveness in different environmental contexts.

  • Recommendations for integrating geospatial analysis into railway planning and maintenance strategies.

Relevance:

The findings offer valuable insights for railway engineers and planners working in arid regions, providing tools and strategies to enhance the resilience of railway infrastructure against wind erosion and sand deposition.

5. Atom Search Optimization: A Systematic Review of Current Variants and Applications

  • Journal: Knowledge and Information Systems, April 12, 2025

  • DOI: 10.1007/s10115-025-02389-3

  • Authors: Sylvère Mugemanyi, Zhaoyang Qu, François Xavier Rugema, Yunchang Dong, Lei Wang, Félicité Pacifique Mutuyimana, Emmanuel Mutabazi, Providence Habumuremyi, Rita Clémence Mutabazi, et al.

Summary:

This comprehensive review delves into the Atom Search Optimization (ASO) algorithm, a nature-inspired metaheuristic optimization technique. The paper systematically categorizes existing variants of ASO, analyzing their structural modifications, performance enhancements, and application domains. It also highlights the algorithm’s adaptability in solving complex optimization problems across various fields, including engineering design, machine learning, and operational research.

Key Contributions:

  • Classification and analysis of existing ASO variants and their respective enhancements.

  • Evaluation of ASO’s performance in comparison to other optimization algorithms.

  • Identification of application areas where ASO has been effectively employed.

  • Discussion on the challenges and future research directions in the development of ASO algorithms.

Relevance:

For researchers and practitioners in optimization and computational intelligence, this review serves as a valuable resource, offering a consolidated understanding of ASO’s capabilities and guiding future developments in the field.

Conclusion

Dr. Providence Habumuremyi presents a compelling case as a highly promising and accomplished early-career researcher in civil and geotechnical engineering. His strong academic foundation, international research contributions, publication record, and multilingual competence support his suitability for the Best Researcher Award. While there is room to grow in terms of independent research leadership and impact-driven dissemination, his trajectory indicates a strong upward path in academic and engineering research.

Mahamat Abdallah | Sustainability | Young Researcher Award

Published on by Popular Engineer

Mr. Mahamat Abdallah | Sustainability | Young Researcher Award

Civil Engineer, Beijing Jiaotong University, China

Mahamat Nour Issa Abdallah is an emerging civil engineer and researcher specializing in sustainable infrastructure in arid regions. He earned his BSc in Civil Engineering from Shenyang Jianzhu University, China, and is currently pursuing a Master’s degree at Beijing Jiaotong University. His professional journey includes roles as a Site Engineer and Engineering Department Supervisor in China and the UAE, where he managed diverse projects focusing on quality control, design coordination, and regulatory compliance. Fluent in English, Arabic, and Mandarin, Mahamat’s multicultural proficiency enhances his collaborative capabilities. His research, particularly on wind erosion and sand deposition in desert railways, reflects a commitment to addressing environmental challenges through geospatial analysis and innovative engineering solutions. Mahamat’s blend of academic rigor and practical experience positions him as a promising contributor to sustainable civil engineering practices.

Profile

Orcid

🎓 Education 

  • Bachelor of Science in Civil Engineering
    Shenyang Jianzhu University, China (2016–2020)
    Focused on structural analysis, construction materials, and project management, laying a strong foundation in civil engineering principles.

  • Master of Science in Civil Engineering
    Beijing Jiaotong University, China (2021–Present)
    Specializing in geospatial analysis and sustainable infrastructure, Mahamat’s research addresses mitigation strategies for wind erosion and sand deposition in desert railway systems. His interdisciplinary approach combines environmental science with civil engineering to develop resilient infrastructure solutions.

🏗️ Experience 

  • Intern, Shenyang ZhongHeng Construction Engineering L.L.C, China (2019–2020)
    Conducted daily site inspections, quality control, and manpower reporting. Assisted in reviewing and modifying fit-out drawings, coordinating with site supervisors and technicians.

  • Site Engineer, DHCN Construction L.L.C, Dubai, UAE (2021–2022)
    Oversaw daily site operations, ensured quality standards, coordinated with foremen, and managed progress reporting. Handled inspection approvals and rectification of non-conformance reports.

  • Engineering Department Supervisor, Origin International Management L.L.C & AL Qimma Engineering Consultancy L.L.C, Abu Dhabi, UAE (2022–Present)
    Managed coordination between consultants and contractors for shop drawing approvals, designed architectural and electrical drawings, and arranged fit-out quotations. Handled site inspections, obtained necessary NOCs, and ensured compliance with fire safety systems. Reported weekly progress and handed over completed projects to clients.

🔬 Research

Mahamat’s research centers on sustainable infrastructure development in arid regions, with a particular emphasis on mitigating wind erosion and sand deposition affecting desert railways. Utilizing geospatial analysis and computational modeling, his work aims to develop effective strategies for maintaining the integrity and safety of railway systems subjected to harsh desert conditions. His interdisciplinary approach integrates environmental science, civil engineering, and data analytics to address the challenges posed by sand accumulation on railway tracks. By focusing on the optimization of sand mitigation measures, Mahamat contributes to the advancement of resilient infrastructure solutions that are crucial for the sustainability of transportation networks in desert environments.MDPI

📚 Publication Top Notes

1. Mitigation Measures for Wind Erosion and Sand Deposition in Desert Railways: A Geospatial Analysis of Sand Accumulation Risk

  • Journal: Sustainability

  • Publication Date: April 29, 2025

  • DOI: 10.3390/su17094016

  • Contributors: Mahamat Nour Issa Abdallah, Tan Qulin, Mohamed Ramadan, Providence Habumuremyi

Summary:
This study presents a geospatial analysis of sand accumulation risks affecting desert railways. By integrating environmental data and computational modeling, the research identifies critical areas prone to wind erosion and sand deposition. The findings offer valuable insights into the development of targeted mitigation strategies to enhance the resilience and safety of railway infrastructure in arid regions.

Conclusion

Mahamat Nour Issa Abdallah is a promising early-career civil engineer with a strong combination of practical experience, multilingual ability, and emerging research in sustainable infrastructure. His work is especially relevant to Middle Eastern and desert environments, making him a good candidate for a Young Researcher Award, particularly if the award emphasizes applied civil engineering, resilience against climate challenges, or geospatial environmental research.

Kuniaki Mihara | Thermal comfort | Best Researcher Award

Published on by Popular Engineer

Dr. Kuniaki Mihara | Thermal comfort | Best Researcher Award

Chief researcher, Kajima corporation, Japan

Dr. Kuniaki Mihara is a distinguished Chief Researcher at Kajima Technical Research Institute (KaTRI), with over two decades of expertise in human-built environmental interaction. His work focuses on thermal comfort, occupant-centric control systems, intellectual productivity, and biophilic design. Holding a Ph.D. in Building from the National University of Singapore, Dr. Mihara is also a LEED Accredited Professional (BD+C) and an ASHRAE Certified HVAC Designer. His contributions have significantly advanced sustainable and occupant-friendly building solutions, particularly in Southeast Asia.

Profiles

Orcid

Google Scholar

Education 

Dr. Mihara earned his Bachelor and Master of Engineering degrees in Architecture from Tohoku University, Japan, in 2004 and 2006, respectively. His early research focused on passive ventilation measurement methods in residences. He later pursued a Ph.D. in Building at the National University of Singapore, completing it in 2020. His doctoral thesis, titled “Human Response Studies of a Dedicated Outdoor Air System with Ceiling Fans in the Tropics,” explored the integration of ceiling fans with dedicated outdoor air systems to enhance thermal comfort in tropical climates. This research has been instrumental in developing energy-efficient cooling strategies suitable for hot and humid environments.

Experience 

Since joining Kajima Technical Research Institute in 2006, Dr. Mihara has progressed from Research Engineer to Chief Researcher. His career spans over 20 years, during which he has led numerous projects focusing on thermal comfort, energy efficiency, and sustainable building design. Notably, he has been involved in the development of hybrid cooling systems and occupant-centric control strategies. His work has been pivotal in promoting energy-efficient practices in building design across Southeast Asia. Dr. Mihara’s expertise has also been recognized through his participation in technical reference groups and collaborations with academic institutions.

Awards and Honors

Dr. Mihara’s contributions to building science have been recognized with several awards. In 2019, he received the SHASE Academic Paper Award for his work on evaluating the compatibility of renewable energy with thermal loads in district heating and cooling systems. His research has been widely cited, reflecting its impact on the field. Additionally, his involvement in developing energy-efficient cooling technologies has garnered attention from both industry and academia, further solidifying his reputation as a leader in sustainable building research.

Research Focus 

Dr. Mihara’s research centers on enhancing thermal comfort and energy efficiency in buildings. He specializes in integrating ceiling fans with dedicated outdoor air systems, developing occupant-centric control strategies, and exploring the psychological impacts of indoor environments. His work often involves interdisciplinary approaches, combining engineering, architecture, and human factors to create sustainable and comfortable living and working spaces. Through extensive field studies and collaborations, Dr. Mihara aims to develop practical solutions that address the challenges of building design in tropical climates.

Publication Top Notes

1. How Does Green Coverage Ratio and Spaciousness Affect Self-Reported Performance and Mood?

  • Publication: Building and Environment, November 2023

  • DOI: 10.1016/j.buildenv.2023.110939

  • Summary: This study investigates the impact of green coverage and spatial openness on individuals’ self-reported performance and mood. The findings suggest that higher green coverage and increased spaciousness positively influence occupants’ mood and perceived performance, emphasizing the importance of biophilic design in urban environments.

2. A Semi-Automatic Data Management Framework for Studying Thermal Comfort, Cognitive Performance, Physiological Performance, and Environmental Parameters in Semi-Outdoor Spaces

  • Publication: Sustainability, December 2022

  • DOI: 10.3390/su15010183

  • Summary: This paper presents a semi-automatic framework designed to manage and analyze multidimensional data related to thermal comfort, cognitive performance, physiological responses, and environmental parameters in semi-outdoor spaces. The framework aims to streamline data processing, reducing errors and improving efficiency in environmental studies.

3. Transient Thermal and Physiological Responses from Air-Conditioned Room to Semi-Outdoor Space in the Tropics

  • Publication: Building and Environment, November 2022

  • DOI: 10.1016/j.buildenv.2022.109611

  • Summary: This study examines the immediate thermal and physiological responses of individuals transitioning from air-conditioned indoor environments to semi-outdoor spaces in tropical climates. Results indicate that occupants quickly adapt to the new environment, with minimal discomfort, highlighting the potential for integrating semi-outdoor spaces in building designs.

4. Environmental Satisfaction, Mood, and Cognitive Performance in Semi-Outdoor Space in the Tropics

  • Publication: Building and Environment, May 2022

  • DOI: 10.1016/j.buildenv.2022.109051

  • Summary: This research explores the effects of semi-outdoor environments on environmental satisfaction, mood, and cognitive performance. Findings suggest that semi-outdoor spaces can support short-term work activities without compromising performance, provided certain environmental conditions are met.

5. Assessment of Airflow and Heat Transfer Around a Thermal Manikin in a Premise Served by DOAS and Ceiling Fans

  • Publication: Building and Environment, April 2022

  • DOI: 10.1016/j.buildenv.2022.108902

  • Summary: This paper investigates the airflow patterns and heat transfer characteristics around a thermal manikin in environments utilizing Dedicated Outdoor Air Systems (DOAS) combined with ceiling fans. The study provides insights into optimizing thermal comfort through strategic airflow management.

6. Physiological and Psychological Responses and Cognitive Performance with Window View

  • Publication: Science and Technology for the Built Environment, March 2022

  • DOI: 10.1080/23744731.2022.2049639

  • Summary: This study examines the impact of window views on occupants’ physiological and psychological responses, as well as cognitive performance. Results indicate that views of nature can reduce stress and enhance cognitive functions, underscoring the value of incorporating natural elements in building design.

7. Thermal and Perceived Air Quality Responses Between a Dedicated Outdoor Air System with Ceiling Fans and Conventional Air-Conditioning System

  • Publication: Building and Environment, March 2021

  • DOI: 10.1016/j.buildenv.2020.107574

  • Summary: This research compares thermal comfort and perceived air quality between spaces using DOAS with ceiling fans and those with conventional air-conditioning systems. Findings suggest that DOAS with ceiling fans can achieve comparable comfort levels while reducing energy consumption.

8. Thermal Comfort and Energy Performance of a Dedicated Outdoor Air System with Ceiling Fans in Hot and Humid Climate

  • Publication: Energy and Buildings, November 2019

  • DOI: 10.1016/j.enbuild.2019.109448

  • Summary: This study evaluates the thermal comfort and energy performance of integrating ceiling fans with DOAS in hot and humid climates. The results demonstrate significant energy savings without compromising occupant comfort.

9. Effects of Temperature, Air Movement, and Initial Metabolic Rate on Thermal Sensation During Transient State in the Tropics

  • Publication: Building and Environment, May 2019

  • DOI: 10.1016/j.buildenv.2019.03.030

  • Summary: This paper investigates how temperature, air movement, and initial metabolic rate affect thermal sensation during transitional periods in tropical climates. The study provides insights into designing HVAC systems that accommodate transient thermal conditions.

10. Time Series Prediction of CO₂, TVOC, and HCHO Based on Machine Learning at Different Sampling Points

  • Publication: Building and Environment, December 2018

  • DOI: 10.1016/j.buildenv.2018.09.054

  • Summary: This study applies machine learning techniques to predict indoor air pollutants like CO₂, TVOC, and HCHO. The predictive models aim to enhance indoor air quality monitoring and management.

Conclusion

Dr. Kuniaki Mihara exemplifies a modern, impactful researcher whose work bridges academic excellence and practical innovation in sustainable building design and human-environment interaction. His technical expertise, project leadership, and real-world application of research outcomes make him highly deserving of the Best Researcher Award.