Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

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Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award | Dr | Nizhegorodskiy Gosudarstvennyy Tekhnicheskiy University | Research Excellence Award

Dr. Anton Loskutov is an accomplished researcher, Associate Professor, and senior scientist whose work spans electric power systems, relay protection, digital substations, smart distribution networks, and machine-learning-driven automation technologies. Dr. Anton Loskutov completed his engineering education at Nizhny Novgorod State Technical University and earned his Ph.D. from Samara State Technical University, where his research centered on developing and studying novel topologies for medium-voltage smart urban distribution networks. His professional experience includes serving as an Associate Professor in the Department of Electric Power, Electricity Supply, and Power Electronics, as well as working as a senior researcher in the laboratory for autonomous hybrid electric power systems. Throughout his role, Dr. Anton Loskutov has actively contributed to relay protection algorithms, overhead line fault-location methods, intelligent network automation, distributed generation integration, and the application of sequential statistical methods to power system decision-making. His research interests encompass electrical network simulation, data-driven energy analytics, high-voltage system protection, artificial intelligence tools for fault recognition, and the development of advanced emergency mode detection frameworks. Dr. Anton Loskutov’s research skills include computational modeling, machine learning for energy diagnostics, development of protection schemes, system optimization, sequential probability testing, and applied algorithm design for electrical networks. His work is widely published in reputed international journals such as Energies, Algorithms, Information, and Technologies, and he has coauthored multiple papers presented in IEEE conferences and Scopus-indexed proceedings. In recognition of his contribution to the field, Dr. Anton Loskutov is an active member of CIGRE, participating in the B5 subcommittee working group on relay automation modeling technologies and representing young researchers in major international sessions. His honors include selection to the youth section of CIGRE and involvement in significant collaborative power engineering projects. Dr. Anton Loskutov continues to contribute to the academic and engineering community through mentoring, interdisciplinary teamwork, and innovative applied research that enhances the safety, efficiency, and resilience of modern electrical networks. With a strong background in intelligent grid development, a robust publication record, and ongoing participation in international technical communities, Dr. Anton Loskutov stands out as a dedicated scholar whose work significantly advances the modernization of power system protection, automation, and distributed energy technologies.

Profile: Scopus | ORCID

Featured Publications 

  1. Kulikov, A., Loskutov, A., Ilyushin, P., Kurkin, A., & Sluzova, A. (2025). High-voltage overhead power line fault location through sequential determination of faulted section. Technologies.

  2. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Fault location method for overhead power line based on a multi-hypothetical sequential analysis using the Armitage algorithm. Inventions.

  3. Kulikov, A., Loskutov, A., Bezdushniy, D., & Petrov, I. (2023). Decision tree models and machine learning algorithms in the fault recognition on power lines with branches. Energies.

  4. Kulikov, A., Ilyushin, P., & Loskutov, A. (2023). Enhanced readability of electrical network complex emergency modes provided by data compression methods. Information.

  5. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Application of search algorithms in determining fault location on overhead power lines according to the emergency mode parameters. Algorithms.

  6. Kulikov, A., Ilyushin, P., Loskutov, A., Suslov, K., & Filippov, S. (2022). WSPRT methods for improving power system automation devices in the conditions of distributed generation sources operation. Energies.

  7. Kulikov, A., & Loskutov, A. (2022). Relay protection and automation algorithms of electrical networks based on simulation and machine learning methods. Energies.

 

Amir Hossein Nafez | Environmental Science | Environmental Impact Award

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Dr. Amir Hossein Nafez | Environmental Science | Environmental Impact Award

Academic Member | Isfahan University of medical Sciences | Iran

Dr. Amir Hossein Nafez is a distinguished environmental health engineer whose academic and research career reflects a deep commitment to sustainability, environmental biotechnology, and waste management innovation. He earned his Ph.D. in Environmental Health Engineering from Isfahan University of Medical Sciences, where his doctoral research focused on evaluating sewage sludge composting using biological and environmental parameters to enhance compost maturity and stability. Dr. Nafez also holds a Master’s degree from Tehran University of Medical Sciences and a Bachelor’s degree from Shahid Beheshti University of Medical Sciences, which together built a strong foundation in water, wastewater, and solid waste management. Currently serving as an Assistant Professor at the Department of Environmental Health Engineering, Isfahan University of Medical Sciences, he leads pioneering research projects on solid waste treatment, biosolids management, composting, and microbial risk assessment. His research interests encompass solid waste management, hazardous waste handling, biological waste treatment, composting and vermicomposting, biosolids recycling, and microbial quality assessment. Dr. Nafez has co-authored more than 35 peer-reviewed articles in globally recognized journals, including Waste Management, Environmental Research, Environmental Technology & Innovation, and Air Quality, Atmosphere & Health, where his work on microbial stability, heavy metal assessment, and biochar application in composting has been widely cited. His research skills include advanced laboratory analysis, microbial examinations, leachate treatment, bioremediation, and environmental monitoring. As a proactive academic, Dr. Nafez collaborates with interdisciplinary teams to address complex environmental and public health challenges while mentoring students in environmental sustainability and waste recovery methods. His professional engagements extend to collaborative research on microbial risk mitigation, pollution control, and the development of safe waste disposal practices in healthcare and industrial sectors. Dr. Nafez’s notable contributions have earned him recognition within the scientific community, highlighting his commitment to promoting eco-efficient waste management systems and innovative recycling strategies. He has also contributed to national and international research initiatives aimed at reducing environmental contamination and improving urban health outcomes. Through his extensive research, teaching, and scientific collaborations, Dr. Amir Hossein Nafez continues to influence the advancement of environmental engineering practices globally. His scholarly dedication, technical expertise, and vision for sustainable development underscore his significant role in shaping future environmental health strategies, making him a deserving candidate for recognition and professional distinction in the global research community.

Profile:  Google scholar | Scopus 

Featured Publications

  1. Nikaeen, M., Nafez, A. H., Bina, B., Nabavi, B. F., & Hassanzadeh, A. (2015). Respiration and enzymatic activities as indicators of stabilization of sewage sludge composting. Waste Management, 39, 104–110. (Citations: 112)

  2. Nafez, A. H., Nikaeen, M., Bina, B., & Hassanzadeh, A. (2015). Composting of sewage sludge in different strategies of aeration with a mixture of green plant wastes as bulking agent. Fresenius Environmental Bulletin, 24(6), 2406–2414. (Citations: 58)

  3. Nafez, A. H., Nikaeen, M., Kadkhodaie, S., & Hatamzadeh, M. (2015). Sewage sludge composting: Quality assessment for agricultural application. Environmental Monitoring & Assessment, 187(709), 1–9. (Citations: 85)

  4. Sadeghi, S., Nafez, A. H., Nikaeen, M., Mohammadi, F., & Hadi, M. (2022). Microbial characteristics of municipal solid waste compost: Occupational and public health risks from surface-applied compost. Waste Management, 144, 98–105. (Citations: 47)

  5. Nafez, A. H., Nikaeen, M., Hassanzadeh, A., & Kadkhodaei, S. (2020). Changes in microbial populations during co-composting of dewatered sewage sludge with pruning wastes in windrow piles. Biodiversitas, 21(10), 4655–4662. (Citations: 22)

  6. Sharafi, S. M., Ebrahimpour, K., & Nafez, A. H. (2021). Environmental disinfection against COVID-19 in different areas of health care facilities: A review. Reviews on Environmental Health, 36(2), 193–198. (Citations: 95)

  7. Yavari, A., Nazar, M. M., Sharafi, S. M., & Nafez, A. H. (2022). Evaluation of stability and maturity indices during composting process from a mixture of poultry waste and sawdust by windrow method. Iranian Journal of Health and Environment, 15(4), fa1–fa16. (Citations: 19)

 

 

Keigo Hisadome | Environmental Science | Best Researcher Award

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Dr. Keigo Hisadome | Environmental Science | Best Researcher Award

Dr. Keigo Hisadome | Environmental Science | Section Manager | Asia Air Survey Co., Ltd | Japan 

Dr. Keigo Hisadome is a highly respected Section Manager at Asia Air Survey Co., Ltd., with extensive expertise in geological survey, groundwater monitoring, soil contamination assessment, and large-scale environmental remediation projects. He has played a key role in advancing the understanding and management of environmental radioactivity, particularly in areas impacted by nuclear incidents. His professional journey is marked by a commitment to integrating scientific research with practical field operations, resulting in measurable improvements in environmental health and safety. Dr. Keigo Hisadome is recognized for his ability to translate complex data into actionable strategies that protect communities and ecosystems.

Professional Profile 

Education

Dr. Keigo Hisadome holds a doctoral degree in Environmental Science with a focus on environmental radioactivity and contamination remediation. His academic journey provided a robust foundation in geology, hydrology, and soil science, enabling him to approach environmental challenges with a multidisciplinary perspective. During his doctoral studies, he concentrated on innovative methodologies for monitoring and mitigating radioactive material transfer, contributing to the development of improved remediation techniques. His education has empowered him to take leadership roles in projects that require technical precision, scientific rigor, and strategic planning.

Experience

Dr. Keigo Hisadome has accumulated significant experience in managing field surveys, contamination assessments, and decontamination operations. As Section Manager, he oversees critical projects related to the remediation of radioactive contamination and the restoration of affected environments. His experience includes designing and implementing survey frameworks, coordinating multidisciplinary teams, and ensuring compliance with international safety standards. He has collaborated with government agencies, research institutes, and local stakeholders to develop solutions for long-term environmental recovery. His ability to combine technical expertise with management skills has positioned him as a trusted leader in environmental remediation initiatives.

Research Interest

Dr. Keigo Hisadome’s research interests revolve around environmental radioactivity, soil contamination dynamics, and groundwater monitoring systems. He is particularly interested in the transfer mechanisms of radioactive materials through forest ecosystems, with an emphasis on leaf litter decomposition and radionuclide migration. His work supports the creation of predictive models that inform decontamination strategies and land use planning. He also explores sustainable remediation techniques that balance ecological restoration with public safety. Dr. Hisadome’s research contributes to scientific understanding as well as to policy frameworks that address post-disaster recovery and long-term radiation risk management.

Award

Dr. Keigo Hisadome is being nominated for the Best Researcher Award in recognition of his exceptional contributions to environmental radioactivity research and his leadership in contamination remediation projects. His work has had a direct impact on the rehabilitation of areas affected by radioactive pollution, making a significant difference in community safety and environmental sustainability. This award would acknowledge his dedication to advancing science, his role in translating research into practical applications, and his commitment to mentoring future professionals in the field.

Selected Publication

“Assessment of Radioactive Material Transfer through Forest Leaf Litter” published in 2021 with 15 citations.

“Groundwater Monitoring Framework for Contaminated Sites” published in 2020 with 12 citations.

“Long-Term Behavior of Soil Contamination in Post-Disaster Areas” published in 2019 with 18 citations.

“Innovative Techniques for Large-Scale Decontamination Projects” published in 2021 with 10 citations.

Conclusion

Dr. Keigo Hisadome is a distinguished researcher whose expertise in environmental radioactivity has made a measurable difference in both scientific knowledge and public health outcomes. His dedication to research, field implementation, and knowledge dissemination has positioned him as a leader in the field of contamination remediation. With his extensive publication record, collaborative approach, and commitment to mentoring, he continues to advance scientific understanding and practical solutions for environmental challenges. This nomination highlights his substantial contributions to research and his potential to drive future innovations in environmental safety and sustainability.

Zhongjun Yan | Energy and Sustainability | Best Researcher Award

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Dr. Zhongjun Yan | Energy and Sustainability | Best Researcher Award

Dr. Zhongjun Yan | Energy and Sustainability | Associate Professor | Hunan University of Humanities Science and Technology | China

Dr. Zhongjun Yan is a distinguished scholar and lecturer at the School of Energy and Electrical Engineering, Hunan University of Humanities, Science and Technology. His professional journey reflects an enduring commitment to advancing renewable energy systems, sustainable heating and cooling technologies, and innovative energy storage methods. With strong academic credentials and a growing body of impactful research, Dr. Zhongjun Yan has established himself as an emerging leader in energy engineering. His work bridges theoretical modeling, computational methods, and experimental studies, enabling both scientific innovation and practical applications. He has become a significant contributor to the field of energy storage and solar-based systems, earning recognition through quality publications and participation in national-level and institutional research projects.

Professional Profile 

Education

Dr. Zhongjun Yan earned his doctoral degree in Heating, Ventilation, and Air-Conditioning Engineering from Hunan University, where his research was focused on the unconstrained melting process of phase change materials and the enhancement of heat transfer in thermal storage systems. His education combined advanced computational modeling, simulation techniques, and experimental validation, shaping a comprehensive expertise in sustainable energy. The doctoral thesis he completed contributed directly to the understanding of thermal storage efficiency and optimization methods in hot water tanks, providing new directions for future energy system development. This academic foundation has been critical to his current research on solar heating, air-conditioning, and the performance of energy storage units.

Experience

In his role as a lecturer, Dr. Zhongjun Yan has undertaken responsibilities that extend across teaching, mentoring, and research. His involvement in the Outstanding Youth Program of the Hunan Provincial Department of Education reflects his growing leadership in energy-related projects. He has contributed to the design and execution of research focusing on computational fluid dynamics (CFD), unconstrained melting phenomena, and heat transfer enhancement. His academic service also includes guiding students in advanced research methodologies and promoting innovation in energy storage and renewable systems. Moreover, Dr. Zhongjun Yan has presented his work at respected international conferences, where he has shared novel findings on the performance of phase change materials. Through these engagements, he has built professional connections that have broadened his collaborative network in the global energy research community.

Research Interest

Dr. Zhongjun Yan’s research interests lie at the intersection of renewable energy systems, thermal engineering, and phase change materials. His primary focus is on the heat transfer performance and optimization of phase change materials to improve the efficiency of thermal energy storage. He has dedicated extensive work to developing new approaches for enhancing the functionality of solar heating water systems and solar air-conditioning systems. Additionally, his research explores innovative modeling techniques to simulate unconstrained melting behaviors, allowing for more accurate predictions of system performance. His long-term vision is to create energy storage and distribution methods that can significantly reduce reliance on non-renewable resources and address the growing global demand for sustainable solutions.

Award

Dr. Zhongjun Yan has been actively involved in award-nominated research programs, most notably recognized through the Outstanding Youth Program by the Hunan Provincial Department of Education. This recognition highlights his innovative contributions to the study of energy storage systems and his leadership potential in advancing renewable technologies. His dedication to pushing the boundaries of engineering solutions in energy efficiency positions him as a strong candidate for international recognition and professional excellence awards.

Selected Publications

  • Performance enhancement of cylindrical latent heat storage units in hot water tanks via wavy design, Renewable Energy, published 2023, 55 citations.

  • A hybrid method for modeling the unconstrained melting of phase change material in hot water tanks, Energy and Buildings, published 2022, 38 citations.

  • Unconstrained melting of phase change material in cylindrical containers inside hot water tanks: Numerical investigation and effect of aspect ratios, Journal of Energy Storage, published 2022, 42 citations.

  • Impact of ultrasound on the melting process and heat transfer of phase change material, presented at International Conference on Applied Energy, published 2018, 27 citations.

Conclusion

Dr. Zhongjun Yan has made meaningful contributions to the field of renewable energy and thermal systems engineering. His work has advanced the knowledge of phase change materials, enhanced the performance of energy storage units, and contributed to the improvement of solar-based heating and cooling technologies. His consistent research output in respected journals, combined with his active role in academic projects and presentations at international conferences, highlights his professional dedication and scientific influence. Dr. Zhongjun Yan is not only a promising researcher but also a mentor and contributor to the broader academic and energy community. With a strong trajectory of impactful research and leadership potential, he represents the qualities of innovation, academic excellence, and societal contribution that make him highly deserving of recognition through this award nomination.

 

saeid shabani | Environmental Science | Best Researcher Award

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saeid shabani | Environmental Science | Best Researcher Award

Assist. Prof. Dr saeid shabani, AREEO, Iran

Assist. Prof. Dr. Saeid Shabani is a distinguished forestry researcher specializing in forest monitoring, natural hazards, and sustainable ecosystem development 🌳🌍. He holds a Ph.D. in Forestry from Tarbiat Modares University, Iran (2015), where he developed models for predicting soil and forest stand disturbances caused by logging 🏗️🌲. His research integrates GIS, machine learning, and statistical modeling to assess forest fragmentation, carbon stock monitoring, and climate change impacts 📊🛰️. Dr. Shabani has led numerous projects on afforestation, ecosystem assessments, and genetic variations in tree species 🌱🔬. His publications in high-impact journals, along with his role as a reviewer for esteemed scientific outlets, solidify his reputation as a leading expert in forestry research 📖🌿. With expertise in ArcGIS, R, and SPSS, he bridges the gap between technology and environmental conservation 💻🍃. His dedication to sustainable forest management makes him an outstanding candidate for the Best Researcher Award 🏅👏.

Publication Profile

Google Scholar

Education

Dr. Saeid Shabani earned his Bachelor of Science in Forestry from the University of Guilan, Iran (2005) 🌲, where he developed a strong foundation in forest management and conservation. He pursued his Master of Science in Forestry at Tarbiat Modares University (2009) 📊, focusing on the relationship between forest gaps, physiographic factors, and vegetation in Lalis Forest, Nowshahr 🌳🗺️. He further advanced his expertise with a Ph.D. in Forestry from the same institution (2015) 🏗️, specializing in modeling soil and forest stand disturbance caused by logging operations 🏞️🔍. Dr. Shabani’s academic journey emphasizes sustainable forest ecosystem development, leveraging GIS, machine learning, and data-driven modeling 📈🌍. His interdisciplinary research bridges ecological conservation and technological advancements to enhance forestry management strategies 💡🌱.

Experience

Dr. Saeid Shabani has extensive experience in forestry research, specializing in forest monitoring, sustainable development, and climate impact assessments 🌍🌿. He has led and collaborated on multiple projects across the Hyrcanian and Arasbaran forests, focusing on afforestation, forest road monitoring, and carbon stock assessment 🏞️📊. His expertise in GIS, R, and machine learning has enabled him to develop predictive models for forest stand disturbances and susceptibility to environmental threats like snowstorms and windthrow 🌪️🛰️. As a scientific reviewer, he contributes to journals such as Scientific Reports, Turkish Journal of Forestry, and Ecology of Iranian Forests 📖📝. He has also been involved in standardizing forestry job competencies and ecosystem differentiation. His impactful work in forest conservation and ecosystem modeling positions him as a leading researcher in environmental sustainability and forestry science

Awards & Honors

Dr. Saeid Shabani has received multiple recognitions for his groundbreaking contributions to forestry research 🌿🏆. His work on forest sustainability, ecosystem monitoring, and climate resilience has earned him prestigious awards and funding. He was a recipient of the Chinese Government Scholarship 🎓🇨🇳 and has won Best Paper Awards for high-impact forestry research in journals like the European Journal of Forest Research 📜🏅. His expertise as a reviewer has been acknowledged with Reviewer Recognition Awards from Scientific Reports, South African Geographical Journal, and Journal of Forest Research & Development 🔍📖. He has secured project grants from environmental organizations for studies on afforestation, soil health, and carbon stock modeling 🌲💰. His Excellence in Forestry Research Award highlights his innovative use of GIS and machine learning in forest monitoring 🏗️🛰️. Through his dedication to sustainable forestry and advanced modeling techniques, he has cemented his reputation as an award-winning researcher in environmental science.

Research Focus

Dr. Saeid Shabani is a distinguished researcher specializing in forest monitoring, ecosystem sustainability, and climate impact assessment 🌲🌎. His expertise lies in applying GIS, machine learning, and statistical modeling to predict forest disturbances caused by natural hazards and human activities 🛰️📊. His research focuses on forest fragmentation and logging impact modeling 🏗️🌳, assessing the effects of snowstorms, windthrow, and climate change on forest ecosystems ❄️🌪️, and evaluating carbon stock in Hyrcanian and Arasbaran forests 🌱📈. Additionally, he contributes to afforestation efforts and sustainable forest management strategies 🌿♻️ while analyzing soil health and biodiversity conservation in forest stands 🔬🍂. Through cutting-edge methodologies, he develops innovative solutions to preserve global forest ecosystems and mitigate environmental risks 🌍💡. His work plays a vital role in policy-making and sustainable forestry development, ensuring the long-term health of natural resources.

Publication Top Notes

  • 📜 Spatial Prediction of Soil Disturbance Caused by Forest Logging Using Generalized Additive Models and GIS – European Journal of Forest Research 🏗️🌲

  • 🌍 Forest Stand Susceptibility Mapping During Harvesting Using Logistic Regression and Boosted Regression Tree Models – Global Ecology and Conservation 📊🛰️

  • 📏 Spatial Modeling of Forest Stand Susceptibility to Logging Operations – Environmental Impact Assessment Review 🏞️📉

  • ❄️ Modeling the Susceptibility of Uneven‑Aged Broad‑Leaved Forests to Snowstorm Damage – Environmental Science and Pollution Research 🌨️🌲

  • 🌡️ How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo? – Sustainability 🏡🌞

  • 🌱 Soil Health Reduction Following Conversion of Primary Vegetation Covers in Semi-Arid Environments – Science of the Total Environment 🏜️🌾

  • 🗺️ Modeling and Mapping of Soil Damage Caused by Harvesting in Caspian Forests Using CART and RF Techniques – Journal of Forest Science 📈📊

  • 🌪️ Prediction of Windthrow Phenomenon in Deciduous Temperate Forests Using Logistic Regression & Random Forest – Cerne Journal 🌳💨