Pinar Kocabey Ciftci | Decision Support System | Research Excellence Award

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Assist. Prof. Dr. Pinar Kocabey Ciftci | Decision Support System | Research Excellence Award

Gaziantep University | Turkey

Assist. Prof. Dr. Pınar Kocabey Çiftçi is an academic researcher specializing in decision support systems, sustainability assessment, and data-driven policy analysis for socio-technical systems. Her research integrates simulation modeling, fuzzy cognitive maps, and advanced decision-making frameworks to address corporate carbon footprint management, green supply chains, and sustainable development strategies. She has contributed impactful studies published in internationally recognized journals spanning sustainability science, climate policy, business process management, and computational intelligence. Her work bridges theory and practice by translating complex analytical models into actionable tools for industrial sustainability, green transformation, and evidence-based management. Her research profile reflects strong interdisciplinary impact across engineering, sustainability, and applied systems science.

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Dr. Yue Meng | Signal Processing | Research Excellence Award

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Dr. Yue Meng | Signal Processing | Research Excellence Award

Nanjing University of Information Science and Technology | China

Dr. Yue Meng is a wireless communication researcher specializing in massive MIMO technology, frequency synchronization, and RF impairment compensation. Their work focuses on developing advanced algorithms for OFDM systems to enhance signal integrity and energy efficiency, particularly under practical impairments such as I/Q imbalance and carrier frequency offsets. Meng has contributed to multiple high-impact publications in IEEE journals and conferences, demonstrating expertise in blind estimation techniques and cognitive radio-inspired nonorthogonal multiple access systems. Their research integrates theoretical analysis with practical implementation, advancing reliable and efficient wireless communication technologies. Meng’s contributions position them strongly for recognition in early-career research and wireless communication innovation.

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Analyzing the Effectiveness of Carbon Pricing Instruments in Reducing Carbon Emissions in Major Asian Economies
Sustainability, 2024

A Canonical Correlation Analysis on the Relation of ESG and Business Environment in South China
Sustainable Futures, 2025

Adaptive Fourier Decomposition Analysis of Different Pandemic Stages in South Korean Cities: Policies and Trends
Journal of Thoracic Disease, 2025

Cost-Effectiveness of Risk Model–Based Lung Cancer Screening in Smokers and Nonsmokers in China
BMC Medicine, 2025

Predicting COVID-19 Vaccination Timing Using the Theory of Planned Behavior and Diffusion of Innovations
Journal of Thoracic Disease, 2025

Sara Exojo Trujillo | Data Science | Research Excellence Award

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Mrs. Sara Exojo Trujillo | Data Science | Research Excellence Award

University of Valencia | Spain

Mrs. Sara Exojo Trujillo is a chemistry researcher specializing in analytical chemistry, polymer science, and environmental risk assessment, with a strong focus on microplastics and emerging contaminants in water and food-related systems. Her research addresses adsorption behavior of pollutants on polymeric materials, advanced analytical method development, and the toxicological impacts of microplastics in biological and ecological models. She combines chromatographic, spectroscopic, thermal, and microscopic techniques with data analysis and kinetic modeling to understand contaminant transport and exposure risks. Her work contributes to sustainable materials research, food safety, and environmental protection through interdisciplinary, application-driven scientific investigation.

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Yunlong Liu | Intelligent Control | Research Excellence Award

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Mr. Yunlong Liu | Intelligent Control | Research Excellence Award

Associate Professor | Qufu Normal University | China

Mr. Yunlong Liu is a researcher and academic specializing in advanced control theory and intelligent systems with strong contributions to engineering and applied computing. His scholarly work focuses on variable structure control, intelligent control strategies, singular and sampled systems, motor technology, and robotics. He has authored a substantial body of peer-reviewed research published in internationally recognized journals and conferences, alongside innovations protected through patented technologies. His research emphasizes theoretical modeling, system stability, and practical applications in automation and intelligent machines. Through interdisciplinary collaboration and academic leadership, his work contributes to the advancement of modern control systems and intelligent engineering solutions.

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842

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John Paulo Serwelas | Corrosion Engineering | Research Excellence Award

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Mr. John Paulo Serwelas | Corrosion Engineering | Research Excellence Award

Mapua University | Philippines

Mr. John Paulo Serwelas is an emerging engineering researcher specializing in corrosion science and materials durability, with a strong focus on reinforced concrete behavior under corrosive conditions. His research integrates experimental investigation with analytical modeling to improve the prediction of bonding performance in deteriorated structural systems. His work contributes to advancing non destructive evaluation approaches and supports more reliable, sustainable infrastructure design within corrosion engineering and materials degradation research domains.

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Dr. Jintao Ju | Electrical Machinery | Research Excellence Award

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Dr. Jintao Ju | Electrical Machinery | Research Excellence Award

Head of the Department of Electrical Engineering | Changzhou Institute of Technology | China

Dr. Jintao Ju is a researcher specializing in the design and control of magnetic bearing systems, with a strong focus on advanced control strategies for high-performance electromechanical applications. His research addresses system nonlinearities, disturbance rejection, and stability enhancement through adaptive and sliding mode control approaches. His work contributes to improving dynamic response, reducing control chattering, and enhancing reliability in magnetic bearing technologies, supporting innovation in modern power electronics and intelligent electromechanical systems.

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Decoupling Control of Neural Network Inverse System Based on Improved Online Learning Levenberg–Marquardt for 3-DOF Hybrid Magnetic Bearing
– Electrical Engineering, 2026

Speed Sensorless Control of Permanent Magnet-Assisted Bearingless Synchronous Reluctance Motor Based on Enhanced Linear Extended State Observer
– Electrical Engineering, 2025

Mr. Andi Chen | Deep Learning | Excellence in Research Award

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Mr. Andi Chen | Deep Learning | Excellence in Research Award

Nanjing University | China

Mr. Andi Chen is an interdisciplinary researcher specializing in quantum-inspired neural networks, tensorized deep learning, and artificial intelligence for pattern recognition and multimodal generation. His research integrates quantum computing concepts with modern neural architectures, including convolutional, residual, and diffusion-based models. He has contributed to high-impact journals and conferences in neural computation and applied physics, while actively engaging in innovation projects on large language models, reinforcement learning fine-tuning, and AI-driven scientific applications across mathematics, engineering, and economics.

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Dr. Alexandra Moshou | Seismological Data analysis | Research Excellence Award

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Dr. Alexandra Moshou | Seismological Data analysis | Research Excellence Award

Civil Engineering | Ηellenic Mediterranean University | Greece

Dr. Alexandra Moshou is a seismologist specializing in earthquake source characterization, waveform analysis, and advanced computational methods in seismology. Her research integrates mathematical modeling, signal processing, and geophysical data analysis to improve understanding of seismic sources and fault systems. She has contributed to software development for seismic parameter estimation and applies modern approaches such as machine learning and spatiotemporal modeling to large seismic datasets, supporting innovation in earthquake science, hazard assessment, and subsurface structural interpretation.

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Mr. Zeeshan Rasheed | Machine Learning | Research Excellence Award

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Mr. Zeeshan Rasheed | Machine Learning | Research Excellence Award

Lecturer Computer Science | Mir Chakar Khan Rind University Sibi Balochistan | Pakistan

Mr. Zeeshan Rasheed is a computer science researcher whose work spans machine learning, data intelligence, wireless networks, and AI-driven decision systems. His research focuses on optimizing network cooperation, developing neural models for sustainable wireless resource management, improving early disease prediction, and analyzing AI’s role in media and social systems. He has contributed to studies on sentiment analysis, intelligent network strategies, pandemic modelling, and crowdsourced data reliability. His scholarly output reflects a continuous commitment to advancing practical and socially relevant AI applications, supported by publications across multidisciplinary journals. His work also demonstrates growing academic impact with ongoing contributions to emerging technological challenges.

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Mr. Thyago Lima | Remote Sensing | Research Excellence Award

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Mr. Thyago Lima | Remote Sensing | Research Excellence Award

São Paulo State University | Brazil

Mr. Thyago Anthony Soares Lima is a geographer and disaster-risk analyst specializing in remote sensing, InSAR, and multi-hazard urban risk assessment. His research focuses on characterizing ground deformation, identifying subsidence typologies, and integrating geological, geomorphological, and geospatial data to strengthen urban resilience. He develops workflows that link land subsidence with flooding, erosion, and slope-instability risks, enabling evidence-based planning for hazard-prone regions. His work bridges geoscience and public decision-making by producing operational subsidence and hazard maps used by civil-defense agencies, planners, and environmental managers. His contributions advance sustainable territorial management and innovative methodologies in geoinformatics and environmental hazard analysis.

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Citations
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