Chengxun Yuan | Space and Astrophysics | Outstanding Scientist Award

Prof. Chengxun Yuan | Space and Astrophysics | Outstanding Scientist Award

Harbin Institute of Technology | China

Prof. Chengxun Yuan is a highly productive researcher in plasma physics, discharge physics, and electromagnetic wave–plasma interactions, with broad contributions spanning theoretical modeling, numerical simulation, and experimental analysis. His scholarly output comprises 235 research documents, which have received 1,597 citations from 1,016 citing publications, resulting in an h-index of 19, reflecting sustained academic impact and international recognition. His research addresses glow discharges, dusty plasmas, ionospheric physics, plasma–chemical processes, and photonic and electromagnetic phenomena, with applications ranging from atmospheric microdischarges to space and plasma optics. He has authored and co-authored influential books on glow discharge kinetics, dusty plasma physics, and electromagnetic wave–plasma interaction, which serve as key references in the field. His recent publications in leading journals such as Physical Review B, IEEE Transactions on Plasma Science, Optics Letters, and Physics of Plasmas demonstrate continued leadership in advancing plasma theory, modeling methodologies, and interdisciplinary plasma-based technologies.

 

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Chao Liu | Graph Neural Networks | Research Excellence Award

Mr. Chao Liu | Graph Neural Networks | Research Excellence Award

China University of Geosciences | China

Mr. Chao Liu is an active researcher in computer science with a strong focus on knowledge graphs, natural language processing, and big data analysis, particularly in the context of graph neural networks (GNNs). He has authored 33 scholarly documents that have attracted 492 citations across 488 citing publications, reflecting a high level of visibility and influence within the research community. With an h-index of 11, his work demonstrates consistent academic impact, especially in large-scale graph learning and data-driven intelligence. His recent contributions explore fundamental challenges in sampling-based large-scale GNNs, examining the relative roles of sampling strategies versus iterative computation for improving scalability and performance. Notably, his 2026 journal article in Neurocomputing, titled “Which plays a key role in sampling-based large-scale GNNs, sampling or iteration?”, provides important theoretical and empirical insights into efficient GNN design. Overall, his research advances scalable machine learning methods for complex, data-intensive systems.

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Bin Wang | Earth Sciences | Research Excellence Award

Dr. Bin Wang | Earth Sciences | Research Excellence Award

Shaanxi Normal University | China

Dr. Bin Wang is an established researcher in climatology, atmospheric modeling, and Earth system science, with a strong focus on mountain–climate interactions, precipitation dynamics, and paleoclimate evolution. His research integrates regional climate models, particularly WRF simulations, with geological and hydrological evidence to examine how major mountain systems such as the Qinling, Qinba, and Daba ranges influence precipitation patterns, vegetation processes, and water yield in Central China. He has published 18 scholarly documents, which have collectively received 430 citations across 382 citing publications, resulting in an h-index of 9, reflecting sustained academic influence. His work spans contemporary climate analysis and deep-time perspectives, including aeolian sediment formation and tectonic controls on loess deposition. Through interdisciplinary contributions linking climatology, hydrology, geomorphology, and paleoenvironments, his research advances understanding of regional climate variability and land–atmosphere interactions under changing environmental conditions.

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Qian Liu | Data-Driven Building Energy Management | Excellence in Research Award

Ms. Qian Liu | Data-Driven Building Energy Management | Excellence in Research Award

Shandong Jianzhu University | China

Ms. Qian Liu is an emerging researcher in building energy systems and data-driven energy analytics, with a focused scholarly contribution to electricity consumption forecasting and energy efficiency in the built environment. Her research emphasizes advanced machine learning methodologies, particularly multi-model ensemble learning and cross-domain robust stacking techniques, to improve the accuracy and reliability of heating-season electricity demand prediction. She has authored 3 research documents, which have collectively received 1 citation from 1 citing document, and she currently holds an h-index of 1, reflecting early but measurable academic impact. Her recent work published in Energy and Buildings (2026) demonstrates the integration of heterogeneous models to enhance predictive performance across varying climatic and operational conditions, offering practical insights for smart energy management and sustainable building operations. Overall, her research contributes to the growing intersection of energy engineering, artificial intelligence, and building performance optimization, supporting data-informed decision-making for future low-energy and resilient building systems.

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Murielle Majiteu | Conservation Biology | Research Excellence Award

Dr. Murielle Majiteu | Conservation Biology  | Research Excellence Award

University of Dschang | Cameroon

Dr. Murielle Majiteu is a researcher in ecology and conservation science with a focus on wildlife trade, biodiversity conservation, and mammalian functional diversity in African ecosystems. Her scholarly record comprises 2 research documents, which have received 1 citation, resulting in an h-index of 1, reflecting emerging academic impact. Her work addresses critical conservation challenges through empirical analysis of species exploitation and ecological drivers shaping biodiversity patterns. Notably, her studies examine the dynamics and conservation implications of wild animal trade in Cameroon and investigate environmental and anthropogenic factors influencing mammalian functional diversity in protected areas such as Bénoué National Park. Through publication in reputable international journals, her research contributes evidence-based insights to conservation planning, sustainable wildlife management, and biodiversity policy development, particularly in the context of tropical ecosystems under increasing human pressure.

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Monika Gębara | Modelling of Hysteresis Loops | Women Researcher Award

Ms. Monika Gębara | Modelling of Hysteresis Loops | Women Researcher Award

Czestochowa University of Technology | Poland

Ms. Monika Gębara is an emerging researcher in applied physics whose work centers on magnetism, nonlinear dynamics, and complex behavior in electrical and physical systems. She has authored 6 research documents, accumulating 12 citations across 9 citing publications, with an h-index of 2, reflecting growing scholarly influence. Her research explores DC-bias effects on magnetization modeling, voltage- and frequency-dependent dynamics in RLD circuits, and chaotic and fractal phenomena in physical systems. She has also contributed to studies on critical behavior near the Curie temperature in magnetic alloys and the visualization of Lorentz forces using fractal structures. Her publications appear in reputable physics journals such as Physica B: Condensed Matter and Acta Physica Polonica A, highlighting her contributions to experimental and theoretical understanding of magnetic materials, nonlinear circuits, and complexity-driven phenomena in condensed matter and applied physics.

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Tong Wu | Conservation Biology | Young Scientist Award

Dr. Tong Wu | Conservation Biology | Young Scientist Award

Shaanxi Institute of Zoology | China

Dr. Tong Wu is a wildlife ecologist whose research focuses on conservation biology, behavioral ecology, ecological security patterns, and health risk assessment of endangered terrestrial wildlife, particularly large mammals and primates in China. With 5 scholarly documents, 18 citations, and an h-index of 2, his work demonstrates emerging academic impact in biodiversity conservation and applied ecology. His research portfolio spans long-term field investigations and interdisciplinary analyses involving population assessment, habitat suitability, contaminant exposure, and species adaptation to environmental change. Dr. Wu has led and contributed to multiple national and regional projects on takin, Tibetan antelope, golden snub-nosed monkeys, crested ibis, and reintroduced carnivores, integrating behavioral studies, GIS, and ecological modeling. His publications appear in reputable international journals such as Global Ecology and Conservation, Ecology and Evolution, Ecological Indicators, and Ecosystem Health and Sustainability, as well as authoritative Chinese journals, collectively advancing scientific understanding of wildlife conservation under anthropogenic and climatic pressures.

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Yufei Li | Technological Networks | Research Excellence Award

Prof. Yufei Li | Technological Networks | Research Excellence Award

Tongji University | China

Prof. Yufei Li is a Chief Physician and Associate Professor at Shanghai East Hospital Affiliated to Tongji University, a nationally recognized Grade III comprehensive hospital ranked among the top 5% of public hospitals in China. With extensive clinical and academic experience, Prof. Li specializes in surgical planning, high-quality operative care, and the training and supervision of junior physicians to ensure medical safety and excellence. He also serves as Chief Physician of the Medical Cosmetic Center and Head of the Medical Cosmetic Team at Tongji Hospital Affiliated to Tongji University, the only Grade 3A general hospital in Putuo District. In this role, he has led the establishment of a professional hair transplantation team and advanced a wide range of medical cosmetic procedures, including facial reconstruction, fat filling, and breast augmentation. Prof. Li holds a Doctorate in Clinical Medicine from Southern Medical University and advanced degrees in plastic surgery and clinical medicine from leading medical universities in China.

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