Yongxi Zhang | Engineering | Best Researcher Award

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Best Researcher Award

Yongxi Zhang
Changsha University of Science and Technology, China

Yongxi Zhang
Affiliation Changsha University of Science and Technology
Country China
Scopus ID 16246642100
Documents 45
Citations 1,124
h-index 13
Subject Area Engineering
Event Top Teachers Awards
ORCID 0000-0002-4609-6189

Yongxi Zhang is a Chinese electrical engineering researcher and Associate Professor at Changsha University of Science and Technology whose academic work focuses on energy storage systems, power system planning, intelligent transportation electrification, and sustainable energy management. Her publication record demonstrates contributions to battery energy storage optimization, electric vehicle infrastructure planning, and renewable energy integration, supporting her recognition as a candidate for the Best Researcher Award.[1]

Abstract

This article summarizes the academic achievements, educational background, research activities, and scholarly output of Yongxi Zhang. Her work emphasizes energy storage technologies, electric transportation systems, and power system operation, while contributing to practical and theoretical developments in sustainable engineering and renewable energy integration.[1]

Keywords

Energy Storage Systems, Electric Vehicles, Power System Planning, Battery Energy Storage, Renewable Energy, Smart Grids, Intelligent Transportation Systems, Photovoltaic Energy, Power Engineering, Sustainable Infrastructure.

Introduction

Yongxi Zhang received engineering degrees from Changsha University of Science and Technology, The Hong Kong Polytechnic University, and The University of Sydney. Since joining academia, she has developed an interdisciplinary research profile connecting electrical engineering, energy storage technologies, and transportation electrification. Her scholarly activities have contributed to the advancement of efficient energy management strategies and resilient power infrastructure systems.[1]

Research Profile

As an Associate Professor in the School of Electrical and Information Engineering, Yongxi Zhang conducts research on energy storage system operation and control, power system planning, electric vehicle charging infrastructure, microgrid optimization, and renewable energy integration. She is an IEEE Member and participates in international professional communities dedicated to power and energy engineering.[1]

Research Contributions

  • Development of planning methodologies for battery energy storage systems in built environments.
  • Research on coordinated deployment of electric vehicle charging stations and mobile energy storage vehicles.
  • Investigation of second-life battery applications for residential and community energy systems.
  • Optimization of photovoltaic-powered transportation and sustainable mobility solutions.
  • Advancement of hierarchical energy management frameworks for microgrids and distributed energy resources.

Publications

Yongxi Zhang has published influential studies on battery energy storage systems, electric vehicle infrastructure planning, renewable energy integration, and intelligent transportation optimization, advancing sustainable engineering solutions and power system resilience.[2][3][4][5][6]

Selected publications highlight contributions to intelligent transportation systems, renewable energy engineering, battery storage optimization, and microgrid management.

Research Impact

With 45 indexed documents, more than 1,124 citations, and an h-index of 13, Yongxi Zhang has established a measurable research presence within engineering and energy-related disciplines. Her studies have supported emerging approaches for energy storage deployment, sustainable transportation, and renewable power system integration.[1]

Award Suitability

The combination of international academic training, sustained publication activity, professional society engagement, and impactful engineering research provides evidence supporting Yongxi Zhang’s suitability for recognition through the Best Researcher Award. Her contributions address contemporary challenges associated with clean energy systems, transportation electrification, and grid modernization.[1]

Conclusion

Yongxi Zhang represents an active researcher in electrical engineering whose work bridges energy storage technologies, intelligent transportation systems, and renewable energy applications. Her publication record, citation impact, and professional engagement collectively demonstrate continuing contributions to engineering research and innovation.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Yongxi Zhang, Author ID 16246642100. Scopus. https://www.scopus.com/authid/detail.uri?authorId=16246642100
  2. Zhang, Y., et al. (2025). Multi-Objective Route Optimization for Photovoltaic Solar-Powered Electric Waste Collection Vehicles. IEEE Transactions on Intelligent Transportation Systems. DOI: https://doi.org/10.1109/TITS.2025.3639053
  3. Zhang, Y., et al. Optimal Planning of Battery Energy Storage System in a Built Environment With Hybrid Thermal Management System and Temperature-Induced Battery Degradation. IET Renewable Power Generation. DOI: https://doi.org/10.1049/rpg2.70256
  4. Zhang, Y., et al. (2024). Coordinated Planning of EV Charging Stations and Mobile Energy Storage Vehicles in Highways With Traffic Flow Modeling. IEEE Transactions on Intelligent Transportation Systems. DOI: https://doi.org/10.1109/TITS.2024.3472755
  5. Zhang, Y., et al. (2022). Two-stage Capacity Determination Framework for Residential Second-Life BESSs Considering Cloud Energy Storage Service. IEEE Systems Journal. DOI: https://doi.org/10.1109/JSYST.2022.3232732
  6. Deng, Y., Zhang, Y., et al. Hierarchical Energy Management for Community Microgrids With Integration of Second-Life Battery Energy Storage Systems and Photovoltaic Solar Energy. IET Energy Systems Integration. DOI:https://doi.org/10.1049/esi2.12055

Ziyoda Adilova | Engineering | Innovative Research Award

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Innovative Research Award

Ziyoda Adilova
Tashkent State Transport University, Uzbekistan
Ziyoda Adilova
Affiliation Tashkent State Transport University
Country Uzbekistan
Scopus ID 57192575499
Documents 30
Citations 131
h-index 7
Subject Area Engineering
Event Top Teachers Awards
ORCID 0000-0002-1825-2447
Google Scholar m5hPvtMAAAAJ

Ziyoda Adilova is an Uzbek engineering researcher and academic affiliated with Tashkent State Transport University. Her scholarly work focuses on railway transport systems, freight transportation, railcar dynamics, maintenance optimization, transport logistics, and railway safety engineering. Through research on dynamic modelling, service-life extension technologies, and freight transport innovations, she has contributed to the advancement of transportation engineering and railway operational efficiency.[1]

Abstract

This article summarizes the academic achievements, research activities, professional experience, scientific projects, and scholarly contributions of Ziyoda Adilova. Her work primarily addresses railway transport engineering, railcar dynamics, freight transportation systems, transport logistics, and maintenance optimization. The combination of theoretical modelling and practical engineering applications demonstrates sustained contributions to transportation research and railway operational safety.[1]

Keywords

Railway Engineering, Freight Transport Systems, Railcar Dynamics, Transport Logistics, Maintenance Optimization, Railway Safety, Engineering Research, Rail Service Vehicles, Transportation Technology, Infrastructure Engineering.

Introduction

Railway transportation remains a critical component of economic development and logistics infrastructure. Research directed toward improving operational safety, freight efficiency, and rolling-stock performance plays an important role in modern transportation systems. Ziyoda Adilova’s academic activities have focused on these areas through investigations of railcar oscillations, maintenance strategies, freight flow optimization, and innovative transport technologies.[1]

Research Profile

Adilova completed her bachelor’s and graduate studies at the Tashkent Institute of Railways and Engineers between 2003 and 2009. She subsequently progressed through research and academic positions, including trainee researcher, assistant lecturer, senior researcher, researcher, doctoral candidate, and professor. Her academic development reflects long-term engagement with transport engineering education and railway research.[1]

  • Bachelor and graduate education in railway engineering.
  • PhD and DSc doctoral training in transport logistics and freight transport systems.
  • Professor, Department of Freight Transport Systems.
  • Research interests in rail vehicle dynamics and transport logistics.
  • Member of Science Slam.

Research Contributions

The research contributions of Adilova are centered on mathematical modelling of railcar structures, oscillation analysis of rolling stock, maintenance planning, railway safety, and freight transport optimization. Her investigations have supported the development of analytical tools for understanding rail vehicle performance under operational conditions and have contributed to extending service life and reliability of transport assets.[2]

  • Dynamic modelling of railcar bearing frames.
  • Oscillation analysis of rail service vehicles.
  • Preventive maintenance optimization methodologies.
  • Freight flow enhancement technologies.
  • Railway safety-oriented engineering innovations.
  • Development of container block-train logistics technologies.
  • Projects addressing service-life extension of transport vehicles.

Publications

Selected publications demonstrate sustained research activity in railway engineering and transport systems, particularly in railcar dynamics and maintenance analysis.[2]

  1. Modelling of Fluctuations in the Main Bearing Frame of Railcar.
  2. Mathematical Model for Calculation of Oscillations in the Main Bearing Frame of Railcar with Changing Stiffness and Physical Parameters.
  3. Mathematical Model of Oscillations of Bearing Body Frame of Emergency and Repair Railcars.
  4. Development of Generalized Dynamic Model of Oscillations of the Main Frame and Running Gear of Rail Service Cars.
  5. Analysis of Optimal Periodicity of Preventive Maintenance of Rail Service Car Taking into Account Operational Technology.

Research Impact

The research output associated with Adilova has contributed to engineering knowledge related to rolling-stock reliability, transport safety, and freight transportation efficiency. Her scholarly profile includes 30 indexed documents, 131 citations, and an h-index of 7, indicating measurable academic visibility within transportation and engineering research communities.[1]

Beyond publication activity, she has led scientific and industrial projects addressing logistics technologies and service-life extension methods for railway vehicles. These initiatives demonstrate engagement with practical transportation challenges and knowledge transfer between academia and industry.[1]

Award Suitability

Ziyoda Adilova’s academic profile aligns with the objectives commonly associated with innovation and teaching recognition programs. Her record includes scholarly publications, leadership of applied research projects, university-level teaching responsibilities, and national recognition through scientific competitions. Notable distinctions include participation as a winner in the “100 Best Innovative Projects of Uzbekistan Women” competition and recognition in the national “Young Scientist” competition. These achievements provide evidence of sustained contributions to engineering research, innovation, and higher education.[1]

Conclusion

Ziyoda Adilova has established a research profile focused on railway engineering, freight transportation systems, transport logistics, and rail vehicle dynamics. Through academic leadership, engineering research, scientific project management, and publication activity, she has contributed to both theoretical and applied developments in transportation engineering. Her achievements support consideration for professional and academic recognition within the engineering and higher-education sectors.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Ziyoda Adilova, Author ID 57192575499. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57192575499
  2. Mukhamedova, Z., and collaborators. Selected publications in railway engineering, railcar dynamics, transport logistics, and maintenance optimization. https://scholar.google.com/citations?user=m5hPvtMAAAAJ&hl=en&oi=sra
  3. ORCID. (n.d.). Researcher Profile: Ziyoda Adilova. https://orcid.org/0000-0002-1825-2447
  4. Top Teachers Awards. (n.d.). Award and recognition platform. https://topteachers.net/
  5. Evaluating skill acquisition in primary education in Uzbekistan through STEAM-based learning approaches. G Mukhamedov, Z Mukhamedova, D Mukhamedova, G Fuzailova, Z Dineeva, OD Akanji. Discover Education. https://link.springer.com/article/10.1007/s44217-026-01442-9

Fazal e Wahab | Engineering | Innovative Research Award

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Innovative Research Award

Fazal e Wahab
Hubei Polytechnic University
Fazal e Wahab
Affiliation Hubei Polytechnic University
Country China
Scopus ID 57216410031
Documents 14
Citations 111
h-index 7
Subject Area Engineering
Event Top Teachers Awards
ORCID 0000-0003-4827-170X
Google Scholar 8t4Pxo8AAAAJ

Fazal e Wahab is an academic researcher and engineering educator affiliated with Hubei Polytechnic University, China. His scholarly work primarily focuses on speech enhancement, signal processing, machine learning applications, and low-latency intelligent systems for embedded and edge computing environments. Over the course of his academic and professional career, he has contributed to research in audio-visual speech enhancement, real-time denoising systems, neural network optimization, and applied engineering technologies. His publications in internationally indexed journals and conferences demonstrate sustained engagement with contemporary developments in communication engineering and intelligent multimedia systems.[1]

Abstract

This academic article documents the scholarly profile, research achievements, and educational contributions of Fazal e Wahab in the field of engineering and intelligent signal processing. His work addresses challenges associated with speech enhancement, audiovisual communication systems, and machine learning implementation for resource-constrained edge devices. Through interdisciplinary research involving signal processing, neural networks, embedded systems, and audio enhancement technologies, he has contributed to practical and computationally efficient methods for real-time communication systems. His publication record includes SCI-indexed journal articles, conference proceedings, funded engineering projects, and collaborative international research activities.[2]

Keywords

Speech Enhancement, Signal Processing, Edge Computing, Deep Learning, Audio-Visual Systems, Engineering Education, Machine Learning, Embedded Systems, Real-Time Denoising, Communication Engineering.

Introduction

The development of intelligent speech processing systems has become increasingly important in modern communication engineering, particularly in environments requiring low-latency and computationally efficient solutions. Researchers working in this field address technical challenges associated with noise suppression, speech intelligibility, audio enhancement, and multimodal communication systems. Fazal e Wahab has participated in this evolving research area through studies focused on lightweight neural architectures, edge-device optimization, and robust audiovisual speech enhancement frameworks.[3]

In addition to research activities, he has contributed extensively to university-level engineering education through undergraduate teaching, curriculum development, laboratory instruction, and supervision of student innovation projects. His academic trajectory includes higher education and research engagement in Pakistan and China, reflecting international academic collaboration and interdisciplinary engineering practice.[4]

Research Profile

Fazal e Wahab completed a Ph.D. in Information and Communication Engineering at the University of Science and Technology of China (USTC) in 2025. His doctoral research focused on optimized lightweight deep learning models for real-time single-channel speech enhancement systems. His investigations emphasized computational efficiency, streaming denoising, echo cancellation, and dereverberation systems applicable to edge and embedded hardware environments.[5]

His academic experience also includes an M.S. in Electrical Engineering from CECOS University and a B.S. in Electronic Engineering from Dawood University of Engineering and Technology. Professionally, he has served as a lecturer, researcher, engineering instructor, and instrumentation engineer, contributing both to industrial engineering operations and university-level technical education.[6]

  • Research specialization in speech enhancement and audio signal processing.
  • Experience in machine learning for edge and embedded systems.
  • Academic supervision of funded engineering projects and applied research.
  • Participation in international scientific collaboration and peer review activities.

Research Contributions

The research contributions of Fazal e Wahab are associated with efficient speech enhancement systems using lightweight neural network architectures. His studies investigate methods for reducing computational complexity while maintaining speech intelligibility and enhancement quality in real-time applications. This area of research is particularly relevant for embedded systems, mobile communication technologies, and assistive audio interfaces.[7]

His published work includes investigations into gated convolutional recurrent neural networks, dual-transformer architectures, multimodal audiovisual processing systems, and adaptive deep learning techniques for speech enhancement. Several publications focus on resource-constrained devices and edge deployment scenarios, demonstrating applied relevance in consumer electronics and intelligent communication technologies.[8]

  • Development of lightweight deep learning models for speech enhancement.
  • Research on audio-visual speech enhancement frameworks using transformer architectures.
  • Optimization of neural systems for edge and embedded devices.
  • Contribution to intelligent signal processing and real-time communication systems.
  • Supervision of funded engineering innovation and assistive technology projects.

Publications

The publication record of Fazal e Wahab includes journal articles and conference papers indexed in SCI, EI, and Scopus databases. His publications span topics related to speech enhancement, multimedia systems, signal processing, energy systems, and intelligent engineering applications.[9]

  1. “Lightweight Adaptive Deep Learning for Efficient Real-Time Speech Enhancement on Edge Devices,” IEEE Transactions on Consumer Electronics, 2025.
  2. “Compact Deep Neural Networks for Real-Time Speech Enhancement on Resource-Limited Devices,” Speech Communication, 2024.
  3. “Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement,” International Journal of Interactive Multimedia and Artificial Intelligence, 2023.
  4. “Multi-Model Dual-Transformer Network for Audio-Visual Speech Enhancement,” AVSEC 2024.
  5. “Integrating Graph Neural Networks and Visual Encoding for Robust Audiovisual Speech Enhancement,” IEEC 2026.
  6. “Frequency-Aware Selective State-Space Modeling for Audio-Visual Speech Enhancement,” Digital Signal Processing, 2026.
  7. “Dynamic Multi-Kernel Convolutional Network With Noise Injected Features for Audio-Only Speech Enhancement,” Neurocomputing, 2025.
  8. “Multimodal Learning-Based Speech Enhancement and Separation,” Computers in Biology and Medicine, 2025.

Research Impact

The research activities of Fazal e Wahab demonstrate measurable academic visibility through Scopus-indexed publications, citation performance, and interdisciplinary engineering collaborations. His studies contribute to ongoing advancements in speech enhancement technologies and intelligent multimedia processing systems. The citation profile associated with his publications indicates scholarly engagement within signal processing and communication engineering communities.[10]

Beyond scholarly publication, his mentorship of funded engineering projects has supported prototype development, applied innovation, and student-centered engineering education. Several supervised projects addressed healthcare technologies, smart home systems, assistive devices, and IoT-enabled monitoring systems, demonstrating practical societal relevance and engineering application.[11]

Award Suitability

The academic and professional profile of Fazal e Wahab reflects several characteristics associated with scholarly recognition in engineering and higher education. His combination of research productivity, international academic engagement, peer-reviewed publication activity, student mentorship, and interdisciplinary engineering expertise demonstrates sustained contribution to communication engineering and intelligent systems research.[12]

His involvement in advanced research related to speech enhancement and machine learning for edge computing environments aligns with emerging global priorities in intelligent communication technologies. Additionally, his experience in teaching, curriculum support, and applied project supervision reflects commitment to engineering education and knowledge dissemination within academic institutions.[13]

Conclusion

Fazal e Wahab has established a multidisciplinary academic profile combining research, teaching, engineering practice, and international scholarly collaboration. His contributions to speech enhancement, signal processing, and machine learning applications for embedded systems represent ongoing engagement with technically relevant and practically applicable research domains. Through journal publications, conference participation, funded project supervision, and academic service, he continues to contribute to the broader development of communication engineering and intelligent multimedia technologies.[13]

References

  1. Elsevier. (n.d.). Scopus author details: Fazal e Wahab, Author ID 57216410031. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57216410031
  2. ORCID. (n.d.). ORCID profile record for Fazal e Wahab. https://orcid.org/0000-0003-4827-170X
  3. IEEE. (2025). Lightweight Adaptive Deep Learning for Efficient Real-Time Speech Enhancement on Edge Devices. https://doi.org/10.1109/TCE.2025.3598007
  4. University of Science and Technology of China. (2025). Doctoral dissertation and academic research profile.
  5. Speech Communication. (2024). Compact Deep Neural Networks for Real-Time Speech Enhancement on Resource-Limited Devices.https://doi.org/10.1016/j.specom.2023.103008
  6. CECOS University. (2015). Master of Science in Electrical Engineering academic record.
  7. International Journal of Interactive Multimedia and Artificial Intelligence. (2023). Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement.
  8. AVSEC Proceedings. (2024). Multi-Model Dual-Transformer Network for Audio-Visual Speech Enhancement.
  9. Computers in Biology and Medicine. (2025). Multimodal Learning-Based Speech Enhancement and Separation. https://doi.org/10.1016/j.compbiomed.2025.110082
  10. Digital Signal Processing. (2026). Frequency-Aware Selective State-Space Modeling for Audio-Visual Speech Enhancement.
  11. National ICT R&D Fund. (n.d.). Applied engineering and IoT-based funded student projects.
  12. Top Teachers Awards. (n.d.). International academic recognition and award platform.https://topteachers.net/
  13. Google Scholar. (n.d.). Academic citation profile of Fazal e Wahab. https://scholar.google.com/citations?hl=en&authuser=1&user=8t4Pxo8AAAAJ

Giovanni Maria Ferraris | Engineering | Research Excellence Award

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Dr. Giovanni Maria Ferraris | Engineering | Research Excellence Award

University of Genoa | Italy

Dr. Giovanni Maria Ferraris is an interdisciplinary engineering researcher specializing in occupational health and safety, fire prevention, risk analysis, and industrial project management, with contributions spanning energy systems, environmental protection, and critical infrastructure. His research integrates applied engineering solutions with safety, sustainability, and innovation in complex industrial and public systems. He has authored 6 Scopus-indexed documents with 3 citations and an h-index of 1, reflecting emerging scholarly impact. His profile is further strengthened by academic engagement in engineering, security, and decision-making systems. Ferraris’s work bridges research, policy, and practice in high-risk and technologically advanced environments.

Citation Metrics (Scopus)

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Featured Publications

Chen Yang | Engineering | Research Excellence Award

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Prof. Chen Yang | Engineering | Research Excellence Award

School of Energy and Power, Chongqing University  |  China

Prof. Chen Yang  research centers on advanced energy systems, renewable energy utilization, and thermal power engineering, with strong emphasis on modeling, optimization, and dynamic control of complex thermo-energy systems, supported by a research record of 1,004 citations across 868 documents, 98 publications, and an h-index of 18. His contributions span ultra-supercritical circulating fluidized bed boilers, nuclear power reactor secondary systems, compressed air energy storage, and hybrid solid oxide fuel cell–gas turbine systems, advancing the efficiency, reliability, and safety of large-scale power generation. He has developed multi-physics and multi-scale reduced-order modeling techniques to address nonlinear dynamics, uncertainty, cooperative simulation, and system stability challenges, enabling enhanced operational performance under transient and abnormal working conditions. His work integrates mechanistic models with artificial intelligence, including neural networks and time-series methods, to achieve online simulation, intelligent prediction, fault early warning, and predictive control in energy systems. He has also contributed to thermodynamic coupling analysis, waste heat utilization strategies, and multi-objective optimization frameworks for green energy systems. Through these innovations, his research significantly supports sustainable power technology development, promotes intelligent and resilient energy infrastructures, and contributes to low-carbon energy transformation and modern energy system advancement.

Citation Metrics (Scopus)

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🟦 Citations    🟥 Documents    🟩 h-index


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Featured Publications

Zina Boussada | Engineering | Research Excellence Award

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Dr. Zina Boussada | Engineering | Research Excellence Award

Company for Petroleum Research and Operations | Tunisia

Dr. Zina Boussada is an emerging researcher in electrical engineering whose work bridges advanced control systems, intelligent automation, renewable energy technologies, and high-performance power electronics. Her scientific contribution focuses on the modeling, optimization, and control of induction motors, photovoltaic systems, and microgrid energy management using intelligent and hybrid computational approaches. She has contributed extensively to sensorless motor control through ANFIS-based strategies, multilevel NPC inverter topologies, stator-flux orientation techniques, and advanced inverter modulation methods, enhancing system efficiency, stability, and predictive performance in industrial and renewable energy applications. Her research extends to photovoltaic cell modeling, hybrid optimization frameworks, exponential smoothing forecasting, diode-clamped inverter strategies, and comparative inverter control techniques, addressing key challenges in modern smart-grid and clean-energy systems. She has collaborated with several research groups and contributed to journals and international conferences in the areas of energy systems, green technologies, and intelligent electrical drives. Her publication record reflects steady scholarly growth, supported by contributions in peer-reviewed journals such as Symmetry, WSEAS Transactions on Systems and Control, the International Journal of Environmental Sciences, and various high-impact conference proceedings. She has also published multiple studies on photovoltaic modeling and multilevel inverter technologies, reinforcing her position within the renewable-energy research community. Her citation metrics indicate increasing academic visibility, with Scopus reporting approximately 490 citations from 482 citing documents, 23 indexed documents, and an h-index of 9. Google Scholar metrics show comparable academic impact, reflecting a growing global readership and recognition for her work in intelligent control and energy-system optimization. Overall, her research trajectory demonstrates strong potential for continued advancement in sustainable energy technologies, intelligent control methodologies, and high-performance electrical systems, positioning her as a promising candidate for the Research Excellence Award.

Publication Profile

Scopus | Orcid 

Featured Publications

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). High-performance sensorless control of induction motor via ANFIS and NPC inverter topology. Symmetry.

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). Data-driven optimization for efficient integration of photovoltaic agents in residential microgrid systems. Euro-Mediterranean Journal for Environmental Integration.

Vasso Papadimitriou | Engineering | Best Researcher Award

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Ms. Vasso Papadimitriou | Engineering | Best Researcher Award

Aristotle University of Thessaloniki | Greece

Ms. Vasso Papadimitriou is an accomplished researcher and academic affiliated with the Aristotle University of Thessaloniki and the Region of Central Macedonia, Greece. Her research primarily focuses on construction project management, cost estimation models, and the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques, particularly Artificial Neural Networks (ANNs), in the field of building renovation and project planning. She has contributed significantly to the development of predictive and hybrid models that enhance accuracy in early-stage and final cost estimation for construction and renovation projects. Dr. Papadimitriou’s innovative work combines ANN methodologies, including Radial Basis Function (RBF) and Multilayer Perceptron (MLP) networks, with Multi-Criteria Decision-Making (MCDM) approaches such as the TOPSIS Methodology to create efficient, data-driven tools for project assessment and optimization. Her research also aligns with Sustainable Development Goals (SDG 9 and SDG 17), focusing on promoting innovation, infrastructure, and partnerships for sustainable growth. She has published in international peer-reviewed journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and other scientific databases. According to Scopus, she has 6 publications, 3 citations, and an h-index of 1. On Google Scholar, she holds 14 total citations, an h-index of 3, and an i10-index of 1, while ResearchGate records 6 publications, 11 citations, and an h-index of 2. Her interdisciplinary approach bridges civil engineering, computer science, and digital construction, contributing to advancements in cost modeling and sustainable infrastructure management. Through her publications and research collaborations, Dr. Papadimitriou continues to make impactful contributions to the field of engineering innovation and AI-driven construction technology. Her outstanding achievements and innovative contributions to predictive modeling and sustainable construction management make her a deserving nominee for the Best Researcher Award.

Publication Profile

Scopus | Google Scholar

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference, 1–10.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696.

Kritikos, P., Papadimitriou, V., & Aretoulis, G. N. (2021). Required project designers’ attributes as perceived by male and female engineers. International Journal of Decision Support System Technology (IJDSST), 13(4), 1–15.

 

 

Mehran Pourgholi | Engineering | Best Researcher Award

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Assist. Prof. Dr. Mehran Pourgholi | Engineering | Best Researcher Award

Islamic Azad University | Iran

Assist. Prof. Dr. Mehran Pourgholi, an accomplished researcher in Civil and Structural Engineering, has made notable contributions to the fields of system identification, structural health monitoring, inverse problems, and stochastic subspace methods. His research focuses on enhancing the reliability of modal analysis and vibration-based damage detection in large-scale structures such as dams and steel buildings. Dr. Pourgholi integrates advanced computational approaches including entropy-based model selection, optimization algorithms, and error analysis frameworks to improve accuracy in structural system modeling. His collaborative work with experts from the University of Tabriz and Islamic Azad University has produced high-impact studies published in leading international journals such as the Journal of Vibration and Control, Mechanical Systems and Signal Processing, and Engineering Reports. According to Google Scholar, Dr. Pourgholi has 77 citations (68 since 2020), an h-index of 4, and an i10-index of 2, while Scopus records 51 citations across 46 documents with an h-index of 3. His influential publications on stochastic subspace identification and modal analysis have advanced understanding of dynamic behavior in civil structures. Recognized for his scholarly excellence, he has been honored with the Best Researcher Award for his significant impact in the field of structural system identification and vibration analysis.

Publication Profile

Scopus | Orcid | Google Scholar 

Featured Publications

Tarinejad, R., & Pourgholi, M. (2018). Modal identification of arch dams using balanced stochastic subspace identification. Journal of Vibration and Control, 24(10), 2030–2044.

Pourgholi, M., Mohammadzadeh Gilarlue, M. M., Vahdaini, T., & Azarbonyad, M. (2023). Influence of Hankel matrix dimension on system identification of structures using stochastic subspace algorithms. Mechanical Systems and Signal Processing, 186, 109893.

Pourgholi, M., Tarinejad, R., Khabir, M. E., & Mohammadzadeh Gilarlue, M. M. (2023). System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results. Journal of Vibration and Control, 29(23–24), 5342–5356.

Tarinejad, R., Pourgholi, M., & Yaghmaei-Sabegh, S. (2016). Signal processing of dynamic tests results using subspace identification based on orthogonal decomposition technique (SI-ORT). Modares Mechanical Engineering, 15(10), 104–116.

Pourgholi, M., Ghannadi, M., & Gavgani, S. S. (2024). Modal analysis of earthquake records for dams using stochastic subspace based on error analysis. Engineering Reports, 6(8), e12822

 

Yair Rivera | Engineering | Best Researcher Award

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Viorel Paunoiu | Engineering | Best Researcher Award

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Prof. Viorel Paunoiu | Engineering | Best Researcher Award

Professor at Dunarea de Jos University of Galati, Romania

Viorel Păunoiu is a distinguished professor and researcher in Industrial Engineering, specializing in metal forming processes, additive manufacturing, and advanced manufacturing technologies. He has dedicated his career to academia and research, significantly contributing to technological advancements in manufacturing. He is currently a professor at “Dunarea de Jos” University of Galati, where he also serves as a PhD supervisor. With over three decades of experience, he has led numerous research projects, supervised doctoral students, and contributed to international collaborations. He has also held various leadership positions, including Director of the Manufacturing Engineering Department and Editor-in-Chief of the university’s scientific journal. His expertise spans industrial process modeling, simulation, and optimization, making him a key figure in Romania’s industrial research community. His contributions have earned him multiple awards and honors, further solidifying his impact on the field.

professional profiles📖

Google Scholar

Scopus Profile

Education 🎓

Viorel Păunoiu holds a PhD in Industrial Engineering from “Dunarea de Jos” University of Galati (1992-1998), focusing on metal forming processes. He earned his Bachelor of Science in Mechanical Engineering from the same institution in 1984. Over the years, he has pursued continuous education, completing post-university studies in CAD design (2007) and industrial property protection (2001). His international academic exposure includes research activities at CEMEF, France (1992), and training in advanced manufacturing techniques in Poland, Ireland, Greece, and Italy. Additionally, he obtained a Certificate of Graduation in Quality Management (2009) and English Language (2013). His academic background is complemented by specialized training in powder metallurgy (1999) and visiting professorships, including the University of Constantine, Algeria (2018). These educational experiences have shaped his expertise in industrial engineering, manufacturing processes, and innovative material technologies.

work Experience💼

Viorel Păunoiu has an extensive career spanning academia, research, and industry. He began as a Design Engineer at MEFIN Sinaia (1984-1987), then transitioned to academia as a Research Assistant (1987-1990) and later Assistant Professor (1990-1992) at “Dunarea de Jos” University of Galati. Over the years, he progressed to Lecturer (1992-2001), Associate Professor (2001-2004), and Professor (2004-present). He currently serves as a PhD Supervisor and Professor Habilitat in Industrial Engineering. His leadership roles include Director of the Manufacturing Engineering Department (2011-2019), Director of the Engineering Research Center (2011-present), and Editor-in-Chief of a scientific journal. He has actively contributed to the university’s governance, serving on the Faculty and Senate councils. His expertise extends to quality assurance, as an evaluator for ARACIS. His career is marked by international collaborations, project leadership, and a strong impact on industrial research and education.

Awards and Honors 

Viorel Păunoiu has received numerous accolades for his contributions to Industrial Engineering. He has won multiple First Awards and Gold Medals at UGAL Invent (2021, 2023) and was honored with the Excellence Award “Octavian Pruteanu” (2013, 2023). His research excellence was recognized with the BEST PAPER AWARD at CSM 2018. In 2017, he received a Special Charter for his contributions to the International Conference on Advanced Manufacturing Engineering and Technologies (NEWTECH). His international recognition includes the Excellence Diploma at TMCR Chișinău (2011) and awards for his contributions to advanced manufacturing and reconfigurable processing systems (2007). His leadership in organizing international conferences and pioneering research in manufacturing technologies has earned him distinction among peers. As an esteemed figure in the industry, his work continues to influence engineering research, industrial applications, and academic advancements.

Research Focus

Viorel Păunoiu’s research revolves around metal forming processes, advanced manufacturing, and additive manufacturing. His work emphasizes modeling and simulation of plastic deformation in sheet metal forming and powder forming technologies. He specializes in inspection technologies, digital forming, and reconfigurable manufacturing, integrating modern computational methods to optimize industrial processes. His research extends to intelligent manufacturing for automotive and aerospace applications, focusing on process automation and material behavior analysis. Additionally, he explores hybrid manufacturing, combining traditional and emerging production techniques. His contributions include innovations in multi-point forming, incremental forming, and laser-assisted forming technologies. His extensive publications and projects reflect his dedication to advancing industrial engineering, bridging the gap between theoretical research and practical industrial applications. His work significantly impacts manufacturing efficiency, cost reduction, and product quality improvement in global industries.

Skills 💡

Viorel Păunoiu possesses a diverse skill set, including expertise in industrial engineering, metal forming, and manufacturing technologies. He is proficient in CAD software like Solid Edge, FEA software for deformation modeling (DYNAFORM), and photo editing tools (Adobe Photoshop, CorelDraw). His project management skills include leading national and international research projects in manufacturing innovation. He has extensive organizational and managerial skills, having directed multiple research centers and academic departments. His communication skills enable effective teaching, research collaboration, and conference organization. He is experienced in scientific review for journals like Elsevier’s Measurement, Materials Design, and MDPI’s Applied Sciences. Additionally, his multidisciplinary approach incorporates artificial intelligence in manufacturing, robotic-assisted forming, and sustainable manufacturing processes. His technical expertise is complemented by his leadership in academic governance, international collaborations, and industry partnerships with major companies like DACIA-RENAULT

 

Conclusion✅

Viorel Păunoiu is a highly qualified candidate for the Best Researcher Award, given his long-standing contributions to industrial engineering, leadership in academic research, and involvement in impactful projects. His work significantly influences manufacturing processes, metal forming, and advanced materials engineering. Strengthening his international visibility, patents, and interdisciplinary collaborations would further enhance his credentials.

 

📚Publications to Noted

 

Laser bending of stainless steel sheet metals

Authors: V. Păunoiu, E.A. Squeo, F. Quadrini, C. Gheorghies, D. Nicoara

Citations: 41

Year: 2008

Numerical simulations in reconfigurable multipoint forming

Authors: V. Păunoiu, P. Cekan, E. Gavan, D. Nicoara

Citations: 32

Year: 2008

Simulation of friction phenomenon in deep drawing process

Authors: V. Păunoiu, D. Nicoară

Citations: 20

Year: 2003

Study on the Transition from the Linear Economy to the Circular Economy

Authors: C. Afteni, V. Păunoiu, M. Afteni

Citations: 18

Year: 2021

Simulation of Plate’s Deformation Using Discrete Surfaces

Authors: V. Păunoiu, N. Oancea, D. Nicoara

Citations: 15

Year: 2004

Using 3D scanning in assessing the dimensional accuracy of mechanically machined parts

Authors: C. Afteni, V. Păunoiu, M. Afteni, V. Teodor

Citations: 13

Year: 2022

Springback compensation in reconfigurable multipoint forming

Authors: V. Păunoiu, V. Teodor, A. Epureanu

Citations: 12

Year: 2009

Simulation of the combined reconfigurable multipoint forming and rubber forming

Authors: V. Păunoiu, P. Cekan, M. Banu, A. Epureanu, D. Nicoara

Citations: 12

Year: 2008

Experimental and finite element analysis of Erichsen test. Application to identification of sheet metallic material behaviour

Authors: V. Oleksik, A. Gavrus, V. Păunoiu, O. Bologa

Citations: 11

Year: 2009

A general upper bound method for forces calculation in tube spinning process

Authors: V. Păunoiu, D. Nicoara, M. Teodorescu

Citations: 11

Year: 1999