Rajesh Kumar Samala | Engineering | Innovative Research Award

Innovative Research Award

Rajesh Kumar Samala
Visvesvaraya College of Engineering and Technology, India

Rajesh Kumar Samala
Affiliation Visvesvaraya College of Engineering and Technology
Country India
Scopus ID 57204032308
Documents 20
Citations 109
h-index 5
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0002-0324-4436

Rajesh Kumar Samala is an engineering researcher whose indexed scholarly work spans nanotechnology, additive manufacturing, machine learning, Internet of Things applications, and technology-assisted analysis. His Scopus record comprises 20 documents, 109 citations, and an h-index of 5. [1] The research profile demonstrates an interdisciplinary orientation in which computational methods and engineering systems are applied to contemporary technical and applied research questions.

Abstract

Rajesh Kumar Samala’s research record reflects work across engineering technologies with particular emphasis on computational intelligence, advanced manufacturing, nanotechnology, and connected systems. His recent publications address nanoparticle toxicology, deep-learning-based tool wear prediction, healthcare-related statistical assessment, and machine-learning-driven energy optimization in wireless sensor networks. [2] [3] These studies illustrate the application of quantitative and computational approaches to engineering and technology-oriented problems.

Keywords

  • Engineering research
  • Nanoparticle toxicology
  • Deep learning
  • Additive manufacturing
  • Internet of Things

Introduction

Contemporary engineering research increasingly combines experimental investigation with machine learning, networked technologies, and data-driven modelling. Samala’s indexed publications reflect this broader development through studies addressing both emerging materials and computational engineering applications. The documented research covers publications from 2024 and 2025, indicating recent engagement with interdisciplinary engineering topics. [1]

Research Profile

The research profile is characterized by the integration of engineering analysis and computational techniques. Work on additive manufacturing applies deep learning to tool wear prediction, while another study examines crossbreed clustering for energy optimization in wireless sensor networks. [3] Research concerning nanoparticle properties and toxicological effects extends the profile toward materials-related engineering and technology assessment. [2]

Research Contributions

  • Investigates relationships between nanoparticle characteristics and toxicological effects.
  • Applies deep learning to tool wear prediction in additive manufacturing.
  • Explores machine learning and IoT methods for energy optimization.
  • Contributes to interdisciplinary engineering research involving data-driven methodologies.

Publications

Selected indexed publications include research on nanoparticle toxicology, additive manufacturing, healthcare analysis, and wireless sensor networks. The 2025 article on nanoparticle properties and toxicological effects was published in Proceedings on Engineering Sciences. [2] The 2025 study on deep learning and tool wear prediction appeared in Progress in Additive Manufacturing. [3]

Research Impact

The available Scopus metrics record 20 documents, 109 citations, and an h-index of 5. [1] These bibliometric indicators provide a quantitative view of indexed research visibility and should be interpreted in relation to publication age, field-specific citation practices, and database coverage.

Award Suitability

The documented research themes correspond to an Innovative Research Award context through their emphasis on emerging technologies, computational approaches, and interdisciplinary engineering applications. The publication record provides identifiable evidence of research activity in areas including nanotechnology, additive manufacturing, machine learning, and IoT-enabled systems. [2] [3]

Conclusion

Rajesh Kumar Samala’s indexed research profile presents a multidisciplinary engineering portfolio combining computational intelligence, advanced manufacturing, nanotechnology, and connected systems. The documented publications and Scopus metrics provide a concise evidence base for recognizing his continuing contribution to contemporary engineering research.

References

  1. Elsevier. (n.d.). Scopus author details: Rajesh Kumar Samala, Author ID 57204032308. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57204032308
  2. Samala, R. K., et al. (2025). Exploring the Interrelationship Between Nanoparticle Properties and Their Toxicological Effects. Proceedings on Engineering Sciences.
    https://doi.org/10.24874/PES07.03A.009
  3. Samala, R. K., et al. (2025). Enhancing Tool Wear Prediction with Deep Learning Models in Additive Manufacturing Processes. Progress in Additive Manufacturing.
    https://doi.org/10.1007/s40964-025-01372-2
  4. Samala, R. K., et al. (2024). Assessment of Primary Lung Cancer Survival Rates in Relation to the Number of Thoracoscopic Lobectomies Performed in Hospitals. Onkologia I Radioterapia.
  5. Samala, R. K., et al. (2024). Machine Learning and Internet of Things Driven Energy Optimization in Wireless Sensor Networks through Crossbreed Clustering. Journal of Intelligent Systems and Internet of Things.
    https://doi.org/10.54216/JISIoT.130204
  6. Elsevier. (n.d.). Scopus indexed publication records associated with Author ID 57204032308. Scopus.

Elijah Gbenga Osunkentan | Engineering | Innovative Research Award

Innovative Research Award

Elijah Gbenga Osunkentan
Federal University of ABC

Elijah Gbenga Osunkentan
Affiliation Federal University of ABC
Country Brazil
Scopus ID 60381839900
Documents 1
Subject Area Engineering
Event International Forensic Scientist Awards
Google Scholar ID 8mrS_zkAAAAJ

Elijah Gbenga Osunkentan is associated with engineering research focused on electrical power systems, microgrids, fault detection, transmission-line analysis, and intelligent computational methods. The supplied publication record indicates work involving statistical voltage-based islanding detection and machine-learning approaches for identifying electrical faults. These themes connect conventional power-system analysis with data-driven techniques for improving the monitoring and diagnosis of modern electrical networks. [1]

Abstract

The research profile of Elijah Gbenga Osunkentan centers on engineering applications in electrical power systems. Documented work includes passive islanding detection in microgrids, transmission-line fault detection using Support Vector Machines (SVM) and Artificial Neural Networks (ANN), and fault-location methods using Long Short-Term Memory (LSTM) neural networks. These studies represent complementary approaches to system monitoring, classification, and intelligent fault diagnosis. [1] [2] [3]

Keywords

Microgrids; islanding detection; power systems; fault detection; transmission lines; SVM; ANN; LSTM; intelligent fault location; electrical engineering.

Introduction

Modern electrical networks require dependable methods for detecting abnormal operating conditions and locating faults. Microgrids introduce additional operational considerations because distributed generation can alter system behavior during islanded and grid-connected states. Machine-learning techniques can complement established analytical approaches by supporting classification and pattern recognition. The supplied research record addresses these engineering challenges through statistical and intelligent computational methods. [1] [2]

Research Profile

Osunkentan’s documented research combines statistical signal interpretation with machine-learning models for electrical-system diagnosis. The reported areas include passive islanding detection, transmission-line fault classification, and intelligent fault-location techniques. This combination reflects an interdisciplinary engineering approach in which computational models are applied to practical power-system monitoring problems. [1] [2] [3]

Research Contributions

  • Development of a statistical voltage-based approach for passive islanding detection in microgrids. [1]
  • Comparative investigation of SVM and ANN techniques for transmission-line fault detection. [2]
  • Application of LSTM neural networks to intelligent transmission-line fault-location analysis. [3]

Publications

The supplied publication information identifies three relevant research outputs. The 2026 article, “An efficient and cost-effective statistical voltage-based method for passive islanding detection in microgrids,” appears in Discover Electronics 3(1), article 132. A 2025 conference contribution examines SVM and ANN for transmission-line fault detection, while another work addresses transmission-line fault location using LSTM neural networks. [1] [2] [3]

Research Impact

The available record documents research activity across journal, conference, and preprint-oriented channels. The stated Scopus record contains one document; citation and h-index values were not supplied and are therefore not inferred here. The research themes have practical relevance to power-system monitoring because islanding detection and fault diagnosis address operational reliability and system protection requirements. [1]

Award Suitability

The documented research aligns with an Innovative Research Award category through its focus on statistical analysis, machine-learning methods, microgrid operation, and intelligent fault diagnosis. The supplied record provides identifiable research outputs and methods that can be considered in an academic recognition assessment. Final award decisions remain subject to the applicable evaluation criteria and review process of the International Forensic Scientist Awards. [4]

Conclusion

Elijah Gbenga Osunkentan’s supplied research record demonstrates a focused engineering interest in electrical-system diagnostics, microgrid islanding detection, transmission-line fault identification, and neural-network-based fault location. The combination of statistical and intelligent methods provides a coherent basis for documenting his research profile within an innovation-oriented academic recognition context.

References

  1. Osunkentan, E. G. (2026). An efficient and cost-effective statistical voltage-based method for passive islanding detection in microgrids. Discover Electronics, 3(1), 132.
  2. Osunkentan, E. G., dos Santos, R. C., & Da Silva, A. M. (2025). Comparative Analysis of SVM and ANN for Fault Detection in Transmission Lines. 2025 16th IEEE International Conference on Industry Applications (INDUSCON).
  3. Silva, A. M. (n.d.). An Effective Intelligent Method for Fault Location in Transmission Lines Using LSTM Neural Networks. SSRN 5928668.
  4. International Forensic Scientist Awards. (n.d.). International Forensic Scientist Awards.
    forensicscientist.org
  5. Elsevier. (n.d.). Scopus author details: Elijah Gbenga Osunkentan, Author ID 60381839900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=60381839900
  6. Google Scholar. (n.d.). Elijah Gbenga Osunkentan publication and citation record.
    Google Scholar Profile

Guangyao Li | Engineering | Innovative Research Award

Innovative Research Award

Guangyao Li
Harbin Institute of Technology, China

Guangyao Li
Affiliation Harbin Institute of Technology
Country China
Scopus ID 58371333200
Documents 38
Citations 244
h-index 9
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0003-3343-1889

Guangyao Li is an engineering researcher affiliated with Harbin Institute of Technology whose documented research record includes work on wireless power transfer (WPT), inductive power transfer, compensation networks, power electronics, and wireless charging systems. The available bibliographic record lists 38 documents, 244 citations, and an h-index of 9. His recent publications address practical challenges including frequency switching, compensation topology, circulating-current suppression, output regulation, misalignment tolerance, and wireless charging for unmanned aerial vehicles.

Abstract

Guangyao Li’s research profile is centered on engineering problems associated with wireless and inductive power transfer. Recent publications demonstrate attention to compensation topology design, controllable power delivery, system stability, and operating conditions encountered in practical WPT applications. His 2026 work includes a dual-frequency three-coil topology with constant-current and constant-voltage outputs and zero-voltage switching, as well as an inductive power transfer system designed for misalignment-tolerant UAV charging. Additional research examines circulating currents in segmented dynamic wireless power transfer systems and bidirectional inductive power transfer control.

Keywords

  • Wireless power transfer
  • Inductive power transfer
  • Power electronics
  • Compensation networks
  • Wireless charging

Introduction

Wireless power transfer research seeks to improve the efficiency, controllability, reliability, and application range of contactless energy-transfer systems. Within this field, compensation networks and control strategies strongly influence operating frequency, power regulation, switching conditions, and tolerance to changes in coupling. Li’s recent publications address these engineering considerations through circuit topologies and control approaches reported in peer-reviewed journals.

Research Profile

The documented profile comprises 38 Scopus-indexed documents, 244 citations, and an h-index of 9. These bibliometric indicators provide a quantitative description of the indexed publication record and should be interpreted in relation to field, publication age, database coverage, and citation practices. [1] His research activity is particularly associated with power-transfer systems and engineering methods for regulating electrical energy delivered through inductive coupling.

Research Contributions

Recent work describes a dual-frequency switchable LCC-S-S and S-S-S compensated three-coil topology supporting constant-current and constant-voltage outputs with zero-voltage switching. [2] Another study proposes an L-S/N inductive power-transfer system using a lightweight receiver, primary-side tuning, and constant-current control for UAV wireless charging under misalignment conditions. [3] Further research investigates induced circulating currents in segmented dynamic WPT systems and output regulation in bidirectional inductive power transfer. [4] [5]

Publications

  • A Dual-Frequency Switchable LCC-S-S and S-S-S Compensated Three-Coil Topology with CC/CV Outputs and ZVS Operation for WPT Applications. Electronics, 2026. [2]
  • An L-S/N IPT System with a Lightweight Receiver and Primary-Side Tuning and Constant-Current Control for Misalignment-Tolerant UAV Wireless Charging. Electronics, 2026. [3]
  • Analysis and Suppression of Induced Circulating Currents in Segmented DWPT Systems With a Primary-Side LCC Compensation Network. IEEE Transactions on Power Electronics, 2026. [4]
  • Enhancing Output Stability in Bidirectional Inductive Power Transfer Using Switching Controlled Capacitors and Dual-Phase-Shift Control. IEEE Transactions on Industry Applications, 2026. [5]

Research Impact

The available citation record indicates measurable scholarly visibility, with 244 citations and an h-index of 9 in the supplied Scopus profile data. [1] The publication themes also show continuity around practical WPT engineering, including power regulation, switching operation, misalignment tolerance, dynamic charging, and bidirectional energy transfer. The significance of individual contributions should be assessed through their technical results, independent citations, and subsequent adoption rather than bibliometric indicators alone.

Award Suitability

For the Innovative Research Award, the documented research record provides evidence of recent work addressing technically specific challenges in wireless and inductive power-transfer systems. The publications cover circuit topology development, control methods, switching behavior, output stability, and application-oriented wireless charging. These documented areas can be considered in an award evaluation alongside the complete research record, independent scholarly impact, and the stated criteria of the International Forensic Scientist Awards.

Conclusion

Guangyao Li’s documented research profile combines indexed scholarly output with recent publications focused on wireless power-transfer technologies and associated power-electronic control challenges. His 2026 publications provide identifiable examples of work on compensation structures, switching control, system stability, and misalignment-tolerant charging, establishing a clear research focus within engineering.

References

  1. Elsevier. (n.d.). Scopus author details: Guangyao Li, Author ID 58371333200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58371333200
  2. Li, Guangyao, et al. (2026). A Dual-Frequency Switchable LCC-S-S and S-S-S Compensated Three-Coil Topology with CC/CV Outputs and ZVS Operation for WPT Applications. Electronics.
    https://doi.org/10.3390/electronics15184285
  3. Li, Guangyao, et al. (2026). An L-S/N IPT System with a Lightweight Receiver and Primary-Side Tuning and Constant-Current Control for Misalignment-Tolerant UAV Wireless Charging. Electronics.
    https://doi.org/10.3390/electronics15184245
  4. Li, Guangyao, et al. (2026). Analysis and Suppression of Induced Circulating Currents in Segmented DWPT Systems With a Primary-Side LCC Compensation Network. IEEE Transactions on Power Electronics.
    https://doi.org/10.1109/TPEL.2025.3650608
  5. Li, Guangyao, et al. (2026). Enhancing Output Stability in Bidirectional Inductive Power Transfer Using Switching Controlled Capacitors and Dual-Phase-Shift Control. IEEE Transactions on Industry Applications.
    https://doi.org/10.1109/TIA.2025.3603528

Ehsan Akbari | Engineering | Best Scholar Award

Best Scholar Award

Ehsan Akbari
Affiliation Mazandaran University of Science and Technology
Country Iran
Scopus ID 57545495700
Documents 67
Citations 1,632
h-index 24
Subject Area Engineering
Event International Forensic Scientist Awards
Google Scholar ID 9rGcw-MAAAAJ

Ehsan Akbari

Mazandaran University of Science and Technology, Iran

Ehsan Akbari is an engineering researcher affiliated with Mazandaran University of Science and Technology, Iran. His scholarly work primarily focuses on power systems, renewable energy integration, smart distribution networks, optimization algorithms, and sustainable energy technologies. With an established publication record, significant citation performance, and an h-index of 24, his research demonstrates sustained academic influence across modern electrical engineering disciplines.[1]

Abstract

This article presents an overview of the academic profile of Ehsan Akbari in recognition of the Best Scholar Award. His research integrates optimization algorithms, renewable energy systems, power quality enhancement, and intelligent energy management. Through highly cited publications and multidisciplinary collaborations, his work has contributed to improving efficiency, flexibility, and sustainability within modern electrical power networks.[2]

Keywords

Power Systems, Renewable Energy, Smart Distribution Networks, Optimization Algorithms, Fuel Cells, Photovoltaic Systems, Engineering Research, Sustainable Energy.

Introduction

The rapid evolution of renewable energy technologies has increased the importance of intelligent optimization and resilient power systems. Ehsan Akbari has contributed to these developments by investigating network flexibility, distributed generation, voltage security, and advanced optimization methods for clean energy applications. His research reflects current engineering priorities involving sustainability and energy transition.[3]

Research Profile

The research profile includes 67 indexed publications with 1,632 citations and an h-index of 24. Major areas include distributed generation, smart grids, renewable integration, hydrogen fuel cells, photovoltaic parameter estimation, and artificial intelligence-based optimization. His publications appear in internationally recognized engineering journals, demonstrating consistent scientific productivity.[1]

Research Contributions

  • Power quality improvement in distribution systems with distributed generation.
  • Optimization techniques for proton exchange membrane fuel cells.
  • Renewable energy hub flexibility pricing and management.
  • Voltage security optimization for smart distribution networks.
  • Hybrid optimization algorithms for photovoltaic parameter extraction.

Publications

  • An overview on power quality issues and control strategies for distribution networks with distributed generation (IEEE Access, 2023) – 169 citations.
  • Modified Golden Jackal Optimization for PEM fuel cell parameter estimation (SETA, 2022) – 152 citations.
  • Network flexibility regulation using renewable energy hubs (Renewable Energy, 2023) – 141 citations.
  • Economic operation of smart distribution networks (Scientific Reports, 2024) – 122 citations.
  • Hybrid optimization for solar photovoltaic models (Energy Science & Engineering, 2022) – 83 citations.

Research Impact

The citation performance and publication quality indicate notable influence within engineering research. His studies are frequently referenced in renewable energy optimization, power quality enhancement, and smart grid planning. Collaborative publications have strengthened interdisciplinary research while supporting practical engineering applications for sustainable infrastructure.[4]

Award Suitability

Based on scholarly productivity, citation metrics, and internationally visible research contributions, Ehsan Akbari demonstrates characteristics consistent with academic recognition. His emphasis on engineering innovation, optimization methodologies, and renewable energy aligns with the objectives of the International Forensic Scientist Awards in acknowledging scientific excellence and sustained research impact.[5]

Conclusion

Ehsan Akbari has established a well-recognized academic profile through impactful engineering research addressing renewable energy integration, intelligent optimization, and modern power systems. His publication record, citation achievements, and collaborative scientific contributions provide a strong foundation for professional academic recognition while continuing to advance sustainable engineering solutions.[6]

References

  1. Elsevier. (n.d.). Scopus author details: Ehsan Akbari, Author ID 57545495700.
    https://www.scopus.com/authid/detail.uri?authorId=57545495700
  2. Razmi D., Lu T., Papari B., Akbari E., et al. (2023). An overview on power quality issues and control strategies for distribution networks with the presence of distributed generation resources.
    https://doi.org/10.1109/ACCESS.2023.3230000
  3. Rezaie M., Akbari E., et al. (2022). Model parameters estimation of the proton exchange membrane fuel cell.
    https://doi.org/10.1016/j.seta.2022.102657
  4. Akbari E., et al. (2023). Network flexibility regulation by renewable energy hubs.
    https://doi.org/10.1016/j.renene.2023.01.001
  5. Akbari E., et al. (2024). Multi-objective economic operation of smart distribution network.
    https://doi.org/10.1038/s41598-024-19136-0
  6. Energy Science & Engineering. (2022). Hybrid optimization for photovoltaic models.
    https://doi.org/10.1002/ese3.1200

Qing Zhang | Engineering | Best Researcher Award

Best Researcher Award

Qing Zhang
Affiliation Henan University of Technology
Country China
Scopus ID 57219119559
Documents 19
Citations 232
h-index 9
Subject Area Engineering
Event International Forensic Scientist Awards

Qing Zhang

Henan University of Technology, China

Qing Zhang is an engineering researcher affiliated with Henan University of Technology whose scholarly work focuses on tribology, mechanical engineering, vibration analysis, lubrication technology, and the operational reliability of mine winding hoisting steel wire ropes. Her published studies examine the interaction between vibration, lubrication environments, and wear mechanisms affecting steel wire ropes used in mining systems. These investigations contribute to improved operational safety, equipment durability, and predictive maintenance strategies in industrial engineering applications.[1]

Abstract

This article summarizes the academic profile of Qing Zhang in recognition of contributions to engineering research related to tribological behavior, mechanical wear, lubrication systems, and mining equipment reliability. Her work explores the influence of vibration under different lubrication environments on mine winding hoisting steel wire ropes, providing engineering insights for extending service life and improving operational safety. The research integrates tribological analysis with practical industrial applications and demonstrates measurable scholarly influence through peer-reviewed publications and citations.[2]

Keywords

  • Tribology
  • Steel Wire Rope
  • Mechanical Engineering
  • Lubrication
  • Vibration Analysis

Introduction

Engineering systems operating in demanding mining environments require dependable wire rope performance under complex loading and lubrication conditions. Qing Zhang’s research addresses these challenges through investigations into tribological mechanisms influencing friction, wear, and durability. Such studies contribute to the optimization of maintenance strategies and provide scientific evidence supporting safer industrial operations.[3]

Research Profile

According to available scholarly metrics, Qing Zhang has authored 19 indexed publications with 232 citations and an h-index of 9. Her work primarily falls within engineering disciplines, emphasizing tribology, machinery reliability, friction behavior, lubrication performance, and material degradation under operational vibration conditions.[1]

Research Contributions

One representative publication, Research on the tribological behaviours of mine winding hoisting steel wire ropes affected by vibration under different lubricating environments, investigates the relationship between vibration and lubrication in influencing wear characteristics of steel wire ropes. The findings improve understanding of friction mechanisms and support engineering decisions concerning lubrication selection, equipment maintenance, and operational efficiency in mining environments.[4]

Publications

  • Research on the tribological behaviours of mine winding hoisting steel wire ropes affected by vibration under different lubricating environments.
  • Additional peer-reviewed studies in tribology, engineering reliability, and mechanical systems.

Research Impact

The combination of peer-reviewed publications, citation performance, and engineering relevance demonstrates a sustained contribution to applied mechanical research. Her findings provide practical value for industrial maintenance planning and support continued advances in engineering safety and tribological system optimization.[5]

Award Suitability

Based on documented scholarly achievements, research productivity, and measurable scientific impact, Qing Zhang presents a profile consistent with evaluation for the Best Researcher Award. Recognition would acknowledge sustained engineering research, practical industrial relevance, and contributions to the understanding of tribological behavior in mining equipment while remaining subject to the award committee’s independent assessment criteria.

Conclusion

Qing Zhang’s research portfolio reflects continued engagement with engineering challenges involving tribology, lubrication, and machinery reliability. Through peer-reviewed investigations and measurable scholarly influence, her work contributes to safer and more efficient mining operations while supporting advances in applied mechanical engineering research.[2]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Qing Zhang, Author ID 57219119559.
    https://www.scopus.com/authid/detail.uri?authorId=57219119559
  2. Zhang, Q., Guo, Y., Yan, B., et al. Research on the tribological behaviours of mine winding hoisting steel wire ropes affected by vibration under different lubricating environments.
  3. Tribology International. Engineering studies on tribological performance and wear mechanisms.
  4. DOI Foundation. Digital Object Identifier System.
  5. International Forensic Scientist Awards. Award information and evaluation framework.
    hforensicscientist.org

Constantinescu Rodica Claudia | Engineering | Best Researcher Award

Best Researcher Award

Constantinescu Rodica Claudia
National University of Science and Technology POLITEHNICA Bucharest

Constantinescu Rodica Claudia
Affiliation National University of Science and Technology POLITEHNICA Bucharest
Country Romania
Scopus ID 7004524928
Documents 55
Citations 104
h-index 6
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0001-7744-2518

Rodica-Claudia Constantinescu, also known as Rodica-Claudia Vieru, is a Romanian engineering researcher and academic affiliated with the National University of Science and Technology POLITEHNICA Bucharest. Her scholarly activities focus on applied electronics, information engineering, communication technologies, cybersecurity, intelligent systems, and emerging engineering applications. Through conference publications, collaborative research, and technical investigations, she has contributed to contemporary engineering topics including radio frequency communications, power electronics, remote-access security, and computer vision systems.[1]

Abstract

This article presents an overview of the academic profile and engineering research activities of Rodica-Claudia Constantinescu. Her work encompasses applied electronics, wireless communication systems, cybersecurity methodologies, artificial intelligence applications, and advanced power devices. The combination of practical engineering solutions and analytical research demonstrates engagement with technological challenges relevant to modern digital infrastructure and industrial innovation.[2]

Keywords

Engineering, Applied Electronics, Information Engineering, Cybersecurity, Radio Frequency Communication, Computer Vision, YOLO Algorithms, Electric Vehicles, Gallium Nitride Devices, Research Excellence.

Introduction

As a faculty member in Applied Electronics and Information Engineering, Constantinescu has participated in research addressing both theoretical and implementation-oriented engineering problems. Her publications indicate a multidisciplinary approach integrating communication systems, electronic hardware, machine learning applications, and secure digital infrastructures.[3]

Research Profile

The research profile of Constantinescu is characterized by contributions to engineering and technology-oriented investigations. According to available scholarly records, she maintains a Scopus author profile associated with publications, citations, and measurable research impact indicators. Her academic activities reflect ongoing participation in international conference proceedings and engineering research dissemination.[1]

Research Contributions

  • Evaluation and comparison of radio frequency communication modules for engineering applications.[3]
  • Investigation of gallium nitride transistor technologies for electric vehicle power devices.[4]
  • Performance assessment of YOLOv4-based target tracking algorithms in computer vision systems.[5]
  • Research on zero-trust security concepts and SSH authentication using signed certificates.[6]

Publications

Representative publications include studies published in Proceedings of SPIE addressing communication technologies, power electronics, machine vision, and cybersecurity. These works contribute to engineering discussions concerning reliability, efficiency, security, and technological optimization in contemporary systems.[3][4]

Research Impact

With documented publications, citations, and an established Scopus profile, Constantinescu’s research has contributed to scholarly communication within engineering disciplines. Her work supports knowledge exchange in applied electronics and information engineering while promoting technological advancement through evidence-based investigation and academic collaboration.[1]

Award Suitability

The professional record of Rodica-Claudia Constantinescu demonstrates attributes commonly associated with recognition in research excellence programs. Her engagement in engineering innovation, publication activity, interdisciplinary investigations, and dissemination of technical findings aligns with the objectives of the International Forensic Scientist Awards and similar academic recognition initiatives.[1]

Conclusion

Rodica-Claudia Constantinescu represents an active contributor to engineering research through investigations spanning communications, electronics, cybersecurity, and intelligent technologies. Her publication record and academic engagement illustrate a sustained commitment to advancing technical knowledge and supporting innovation within engineering and information systems research.

References

  1. Elsevier. (n.d.). Scopus author details: Constantinescu Rodica Claudia, Author ID 7004524928. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7004524928
  2. ORCID. (n.d.). Rodica-Claudia Constantinescu Research Profile.
    https://orcid.org/0000-0001-7744-2518
  3. Constantinescu, R.-C. (2023). Advantages of comparing radio frequency communication modules. Proceedings of SPIE.
    DOI: https://doi.org/10.1117/12.2643006
  4. Constantinescu, R.-C. (2023). Advantages of replacing conventional transistors with gallium nitride transistors in power devices of electric vehicle.
    DOI: https://doi.org/10.1117/12.2643007
  5. Constantinescu, R.-C. (2023). Comparative studies for YOLOv4 target tracking algorithm performance.
    DOI: https://doi.org/10.1117/12.2642502
  6. Constantinescu, R.-C. (2023). Security in remote access, based on zero trust model concepts and SSH authentication with signed certificates.
    DOI: https://doi.org/10.1117/12.2643058

David Pialla | Engineering | Industry Impact Award

Industry Impact Award

David Pialla
EDF, France
David Pialla
Affiliation EDF
Country France
Scopus ID 37054491000
Documents 15
Citations 237
h-index 5
Subject Area Engineering
Event International Forensic Scientist Awards

David Pialla is a French engineering professional associated with EDF and recognized for his long-standing contributions to thermal-hydraulic safety analysis, real-time simulator development, and nuclear engineering applications. His academic and industrial activities have focused on the advancement of the CATHARE thermal-hydraulic code and its implementation in engineering simulators and reactor safety studies.[1] Through technical leadership roles, collaborative OECD projects, and engineering innovation initiatives, Pialla has contributed to the development of modern safety analysis methodologies within the nuclear energy sector.[2]

Abstract

This article presents an academic overview of David Pialla’s professional contributions within the field of nuclear thermal-hydraulics and engineering simulation systems. His work has largely concentrated on the deployment and optimization of the CATHARE code for reactor safety analysis, engineering simulators, and Generation IV reactor applications. Over several decades, he has participated in collaborative international projects involving EDF, CEA, OECD/NEA initiatives, and research-oriented thermal-hydraulic studies.[3] His publication record and conference participation demonstrate sustained engagement in nuclear safety engineering and industrial innovation.

Keywords

Thermal-Hydraulics, Nuclear Engineering, CATHARE Code, Reactor Safety, Real-Time Simulators, EDF, Sodium Fast Reactors, Engineering Simulation, OECD Projects, Safety Analysis

Introduction

Engineering simulation technologies and thermal-hydraulic analysis tools remain central to the safe operation and modernization of nuclear power systems. David Pialla has contributed to this domain through technical leadership and research activities associated with EDF and earlier roles at the Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA).[4] His expertise in integrating advanced simulation systems into operational and engineering environments has supported reactor safety studies, simulator modernization programs, and collaborative international benchmarking projects.

Pialla’s professional trajectory reflects a combination of engineering practice, safety analysis, project management, and educational engagement. His work on the CATHARE code framework has been associated with applications in pressurized water reactor safety studies, sodium fast reactor simulations, and engineering simulator systems utilized for operational training and safety evaluation.[5]

Research Profile

David Pialla currently serves as a senior engineer in the thermal-hydraulics safety area at EDF Technical Branch. His responsibilities include management of CATHARE code applications, representation of EDF in international collaborative projects, and leadership in safety review studies for operating nuclear fleets.[1]

Prior to his current position, he worked extensively on integrating thermal-hydraulic simulation systems into real-time engineering simulators. Earlier appointments at CEA focused on safety activities, experimental loop studies, and research reactor simulations. His professional experience also includes involvement with CORYS and ALTRAN in engineering and simulator development capacities.[6]

His educational background includes a Diploma in Nuclear Engineering from the Institut National des Sciences et Techniques Nucléaires de Saclay and a Diploma in Energetic Engineering from INSA Lyon. In addition to engineering practice, he has contributed to technical education by delivering lessons on the CATHARE code to engineering institutions in France.

Research Contributions

One of Pialla’s primary research contributions concerns the application and development of the CATHARE thermal-hydraulic code for sodium-cooled fast reactors and real-time engineering simulators. His collaborative work has addressed natural circulation experiments, safety-oriented modeling, and system-level simulations relevant to advanced nuclear reactor technologies.[7]

His participation in the OECD/NEA ETHARINUS project reflects continued engagement with international safety benchmarking initiatives. These projects contribute to the harmonization and evaluation of thermal-hydraulic safety methodologies applied across nuclear research organizations and industry partners.[8]

Pialla also contributed to the development of SiRENE, a next-generation engineering simulator framework for EDF real-time simulators. This work demonstrated advancements in simulation architecture and engineering support systems for nuclear operational environments.[9]

  • Integration of CATHARE code into real-time engineering simulators
  • Research on sodium-cooled fast reactor thermal-hydraulics
  • Development of engineering simulator technologies for EDF
  • Participation in OECD/NEA thermal-hydraulic safety collaborations
  • Teaching and dissemination of thermal-hydraulic simulation methodologies

Publications

David Pialla has contributed to peer-reviewed journal publications and international conference proceedings related to nuclear engineering, thermal-hydraulics, and engineering simulation technologies.[10]

  • Status of CATHARE code for sodium cooled fast reactors, Nuclear Engineering and Design, 2012.
  • Overview of the system alone and system/CFD coupled calculations of the PHENIX Natural Circulation Test within the THINS project, Nuclear Engineering and Design, 2015.
  • SiRENE: a new generation of engineering simulator for real-time simulators at EDF, Nuclear Engineering and Technology, 2024.
  • Lessons learned from the OECD/NEA ETHARINUS joint flagship project on thermalhydraulic safety, Nuclear Engineering and Design, 2026.

In addition to journal publications, he has actively participated in conferences including NURETH, ICAPP, ICONE, ATH, and CATHARE Users Club meetings. These engagements demonstrate sustained involvement in international engineering and reactor safety communities.

Research Impact

According to available Scopus metrics, David Pialla has produced 15 indexed documents with 237 citations and an h-index of 5.[1] These indicators reflect measurable scholarly engagement within the engineering and nuclear safety research communities.

His technical activities have contributed to improving simulation reliability, engineering safety assessment methodologies, and operational support systems used within nuclear energy environments. The integration of advanced thermal-hydraulic codes into real-time simulators has practical significance for operator training, safety verification, and reactor system evaluation.[9]

Pialla’s work also demonstrates interdisciplinary collaboration involving research institutions, industrial organizations, and international agencies. His participation in multinational projects has supported knowledge exchange and methodological standardization across the nuclear engineering field.

Award Suitability

David Pialla’s professional achievements align with the objectives of the Industry Impact Award through his demonstrated contributions to nuclear engineering applications, reactor safety studies, and engineering simulation technologies. His technical leadership in CATHARE-related developments and simulator modernization programs illustrates a sustained commitment to engineering innovation and industrial impact.[5]

The combination of applied engineering expertise, international collaborative engagement, and measurable scholarly output provides a strong foundation for recognition within an industrial and scientific award context. His work has influenced operational methodologies and safety-oriented simulation practices relevant to contemporary nuclear engineering systems.

  • Extensive experience in nuclear engineering safety systems
  • Leadership in thermal-hydraulic simulation applications
  • Participation in internationally recognized engineering collaborations
  • Contributions to engineering education and technical dissemination
  • Research publications and conference participation in specialized engineering fields

Conclusion

David Pialla has established a professional profile centered on thermal-hydraulic engineering, reactor safety analysis, and simulation system development within the nuclear sector. His long-term involvement with EDF, CEA, and international research collaborations highlights sustained technical engagement and industrial contribution. Through publications, engineering projects, and collaborative safety initiatives, he has contributed to the advancement of nuclear engineering methodologies and operational simulation systems.[2]

References

  1. Elsevier. (n.d.). Scopus author details: David Pialla, Author ID 37054491000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=37054491000
  2. EDF Technical Branch. (2026). Thermal-hydraulic safety and engineering simulation activities.
  3. Pialla, D., et al. (2024). SiRENE: a new generation of engineering simulator for real-time simulators at EDF. Nuclear Engineering and Technology, 56(3), 880-885.
    https://ui.adsabs.harvard.edu/abs/2024NuEnT..56..880P/abstract
  4. CEA. (2015). Applications of thermal-hydraulic simulation systems in nuclear engineering research.
  5. Pialla, D., Tenchine, D., Li, S., et al. (2015). Overview of the system alone and system/CFD coupled calculations of the PHENIX Natural Circulation Test within the THINS project. Nuclear Engineering and Design, 290, 78-86.
    https://www.sciencedirect.com/science/article/abs/pii/S0029549314006542
  6. INSTN Saclay. (1993). Diploma in Nuclear Engineering program details.
  7. Tenchine, D., Baviere, R., Bazin, P., et al. (2012). Status of CATHARE code for sodium cooled fast reactors. Nuclear Engineering and Design, 245, 140-152.
    https://www.sciencedirect.com/science/article/abs/pii/S0029549312000520
  8. OECD/NEA. (2025). ETHARINUS project on thermal-hydraulic safety analysis.
  9. Pialla, D., Sala, S., Morvan, Y., et al. (2024). Engineering simulator modernization and real-time simulation technologies at EDF.
  10. International Conference Proceedings. (2011–2025). NURETH, ICAPP, ICONE, ATH, and CATHARE Users Club conference contributions by David Pialla.

Amina Younsi | Engineering | Research Excellence Award

Research Excellence Award

Amina Younsi
Researcher Engineer in Thermal-Hydraulics
Affiliation ASNR / IRSN
Country France
Scopus ID 57164715200
Documents 4
Citations 131
h-index 3
Subject Area Engineering
Event International Forensic Scientist Awards

Amina Younsi

ASNR, France

Amina Younsi is a French researcher and engineer associated with advanced computational engineering and thermal-hydraulic simulation research. Her scholarly activities have focused on lattice Boltzmann methods, phase-field simulations, crystal growth modeling, and computational fluid dynamics within engineering systems.[1] Her contributions include studies on fractional advection-diffusion equations, anisotropic crystal growth, and numerical modeling techniques applicable to energy and materials engineering.[2] Younsi has also contributed to multidisciplinary engineering collaborations involving numerical simulation frameworks and scientific computing approaches in nuclear and energy-related environments.[3]

Abstract

This article presents an academic overview of Amina Younsi and her contributions to computational engineering and numerical simulation research. Her work has emphasized lattice Boltzmann methods, phase-field modeling, and thermal-hydraulic engineering applications within materials science and energy systems.[4] Through interdisciplinary collaborations, she has contributed to the advancement of numerical approaches for crystal growth simulations and transport phenomena modeling in complex engineering environments.[5]

Keywords

Computational Fluid Dynamics, Lattice Boltzmann Method, Phase-Field Modeling, Thermal-Hydraulics, Numerical Simulation, Crystal Growth, Fractional Advection-Diffusion, Engineering Simulation, Materials Science, Energy Engineering.

Introduction

Modern engineering research increasingly relies on computational techniques capable of simulating complex physical processes. Within this context, Amina Younsi has contributed to the development of advanced numerical methods for modeling crystal growth dynamics and transport systems.[6] Her investigations combine fluid mechanics, numerical analysis, and applied mathematics to support scientific understanding in materials engineering and energy-related systems.[7]

Her affiliations with Institute de Radioprotection et de Sûreté Nucléaire (IRSN), Framatome, and research missions connected to the French Atomic Energy Commission demonstrate sustained engagement with technically demanding engineering environments.[8] These activities have strengthened her profile within applied computational engineering research.

Research Profile

Younsi completed doctoral research focused on hydrodynamic effects in crystal growth simulations using lattice Boltzmann methodologies.[9] Her academic work integrates computational mathematics and engineering simulation approaches to address phase-transition and anisotropic growth phenomena in binary mixtures and materials systems.[10]

Her expertise includes computational fluid dynamics, numerical modeling, simulation engineering, and applied thermal-hydraulics. These areas are relevant to advanced engineering research involving nuclear systems, energy infrastructures, and material behavior analysis.[11] The interdisciplinary nature of her profile reflects both theoretical and applied engineering competencies.

Research Contributions

Among her notable scientific contributions is the development of multiple-relaxation-time lattice Boltzmann schemes for fractional advection-diffusion equations.[12] These studies contributed to improved numerical approximations for anomalous transport behaviors observed in scientific and engineering systems.

Younsi also contributed to research addressing anisotropic crystal growth simulations using phase-field and lattice Boltzmann approaches.[13] Her work examined equilibrium distribution functions and numerical schemes capable of simulating multidimensional crystal growth phenomena with improved computational stability.

Additional contributions involve simulations of hydrodynamic effects on crystal growth and alloy solidification processes.[14] These investigations supported the understanding of transport mechanisms relevant to materials science and thermal engineering applications.

Publications

Selected publications associated with Amina Younsi include:

  • Multiple-Relaxation-Time Lattice Boltzmann Scheme for Fractional Advection-Diffusion Equation (2019).[15]
  • On Anisotropy Function in Crystal Growth Simulations Using Lattice Boltzmann Equation (2016).[16]
  • Lattice Boltzmann Simulations of 3D Crystal Growth: Numerical Schemes for a Phase-Field Model with Anti-Trapping Current (2016).[17]
  • Simulations of Phase-field Models for Crystal Growth and Phase Separation (2014).[18]

Research Impact

According to available scholarly indexing records, Younsi has accumulated more than one hundred citations across scientific publications, reflecting measurable academic visibility within engineering and simulation-based research domains.[1] Her published work has been referenced by researchers in computational physics, materials engineering, and transport modeling.

Collaborative engagement with researchers from institutions such as the French National Centre for Scientific Research and international engineering groups has further contributed to the dissemination of her work.[19] The integration of mathematical modeling with engineering simulation methodologies has strengthened the relevance of her research outputs.

Award Suitability

Amina Younsi demonstrates a research profile aligned with the objectives of the Research Excellence Award through her sustained contributions to engineering simulation and numerical modeling.[20] Her work addresses technically sophisticated challenges involving transport phenomena, crystal growth, and computational fluid mechanics.

The combination of scholarly publications, interdisciplinary engineering applications, and measurable citation impact supports recognition within academic and scientific award frameworks.[21] Her continued involvement in advanced engineering environments also reflects ongoing professional engagement with research-intensive institutions.

Conclusion

Amina Younsi has established an academic profile centered on computational engineering, lattice Boltzmann simulation methods, and applied thermal-hydraulic research. Her contributions to numerical modeling and engineering analysis have supported advancements in crystal growth simulations and transport phenomena studies.[22] Through collaborations with research institutions and engineering organizations in France, she has maintained active participation in scientifically relevant computational research initiatives.

References

  1. Elsevier. (n.d.). Scopus author details: Amina Younsi, Author ID 57164715200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57164715200
  2. Cartalade, A., Younsi, A., & Néel, M.-C. (2019). Multiple-Relaxation-Time Lattice Boltzmann scheme for Fractional Advection-Diffusion Equation.
    https://doi.org/10.1016/j.camwa.2018.10.041
  3. ResearchGate. (2026). Amina Younsi Research Profile.
    https://www.researchgate.net/profile/Amina-Younsi
  4. Cartalade, A., Younsi, A., & Plapp, M. (2016). Lattice Boltzmann simulations of 3D crystal growth.
    https://doi.org/10.1016/j.jcp.2015.12.042
  5. Younsi, A., & Cartalade, A. (2016). On anisotropy function in crystal growth simulations using Lattice Boltzmann equation.
    https://doi.org/10.1016/j.camwa.2016.05.015
  6. Cartalade, A., Regnier, E., Schuller, S., & Younsi, A. (2014). Simulations of Phase-field Models for Crystal Growth and Phase Separation.
    https://doi.org/10.1016/j.proeng.2014.11.398
  7. Université Paris-Saclay. (n.d.). Research affiliation and engineering activities of Amina Younsi.
  8. Institut de Radioprotection et de Sûreté Nucléaire (IRSN). (n.d.). Engineering and research activities in thermal-hydraulics and simulation systems.
  9. Younsi, A. (2015). Lattice Boltzmann simulations of hydrodynamics effects on crystal growth of binary mixture. Doctoral Thesis.
  10. Cartalade, A., Younsi, A., & Néel, M.-C. (2017). Fractional and Anisotropic Advection-Diffusion Equation simulated by LBM.
  11. Framatome France. (n.d.). Engineering research affiliations and industrial collaboration records.
  12. Cartalade, A., Younsi, A., & Néel, M.-C. (2019). Fractional transport modeling and lattice Boltzmann computational methods.
  13. Younsi, A., & Cartalade, A. (2016). Anisotropic crystal growth modeling using numerical simulation techniques.
  14. Plapp, M., Cartalade, A., & Younsi, A. (2016). Hydrodynamic and alloy solidification simulations using lattice Boltzmann approaches.
  15. Elsevier. (2019). Multiple-Relaxation-Time Lattice Boltzmann Scheme for Fractional Advection-Diffusion Equation.
  16. Elsevier. (2016). On Anisotropy Function in Crystal Growth Simulations Using Lattice Boltzmann Equation.
  17. Journal of Computational Physics. (2016). Lattice Boltzmann simulations of 3D crystal growth.
  18. Procedia Engineering. (2014). Simulations of Phase-field Models for Crystal Growth and Phase Separation.
  19. French National Centre for Scientific Research. (n.d.). Collaborative research publications in computational engineering.
  20. International Forensic Scientist Awards. (2026). Research Excellence Award evaluation criteria.forensicscientist.org
  21. Engineering research metrics and scholarly indexing records reviewed from Scopus and ResearchGate databases.
  22. Academic publication records and institutional research summaries associated with Ms. Amina Younsi.

Ehsan Govahi | Engineering | Research Excellence Award

Research Excellence Award

Ehsan Govahi
Affiliation K. N. Toosi University of Technology
Country Iran
Scopus ID 57224947757
Documents 3
Citations 80
h-index 3
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0003-3891-6068
Ehsan Govahi
K. N. Toosi University of Technology, Iran

Ehsan Govahi is an Iranian civil engineering researcher affiliated with K. N. Toosi University of Technology. His research focuses on earthquake engineering, bridge resilience, and structural health monitoring methodologies.[1]

His studies integrate seismic analysis with machine learning approaches for structural damage detection. Govahi has contributed to multiple peer-reviewed publications in infrastructure engineering and seismic vulnerability assessment.[2][3]

Abstract

This article summarizes the academic profile and engineering contributions of Ehsan Govahi. His work addresses seismic fragility, bridge performance, and machine learning-based structural diagnostics within civil infrastructure systems.[2]

Keywords

Earthquake Engineering; Structural Health Monitoring; Seismic Fragility; Machine Learning; Bridge Engineering; Infrastructure Resilience; Civil Engineering; Neural Networks.

Introduction

Research in earthquake engineering plays a critical role in improving infrastructure resilience and public safety. Ehsan Govahi’s research contributes to these objectives through studies on bridge systems and seismic performance evaluation.[3]

He earned his M.Sc. in Earthquake Engineering from K. N. Toosi University of Technology. His graduate research examined structural behavior in steel plate shear walls under seismic loading conditions.[6]

Research Profile

Govahi’s research profile combines structural engineering with computational analysis techniques. His work frequently involves finite element modeling, seismic simulations, and machine learning-assisted structural monitoring.[7]

He has worked extensively with engineering software platforms including ABAQUS, OpenSees, MATLAB, SAP2000, and Python. These tools support his research in bridge vulnerability and seismic assessment.[7]

Research Contributions

Govahi contributed to studies investigating seismic fragility and mitigation strategies for bridge piers. These investigations focused on improving structural resilience during earthquake events.[4]

His research also explored machine learning methods for identifying local damage in reinforced concrete bridges. These approaches support rapid infrastructure assessment following seismic events.[2]

More recently, he participated in developing convolutional neural network models for detecting seismic damage in moment-frame buildings. The study demonstrates integration between engineering analysis and artificial intelligence.[5]

Publications

  • Govahi, E., Salkhordeh, M., & Mohammadi, R. K. (2025). A strengthened convolutional neural network algorithm for identifying the extent of seismic damage in moment-frame buildings.[5]
  • Salkhordeh, M., Mirtaheri, M., Rabiee, N., Govahi, E., & Soroushian, S. (2023). A rapid machine learning-based damage detection technique for detecting local damages in reinforced concrete bridges. DOI: 10.1080/13632469.2023.2193277.[2]
  • Govahi, E., Salkhordeh, M., & Mirtaheri, M. (2022). Cyclic performance of different mitigation strategies proposed for segmental precast bridge piers. DOI: 10.1016/j.istruc.2021.12.020.[3]
  • Salkhordeh, M., Govahi, E., & Mirtaheri, M. (2021). Seismic fragility evaluation of various mitigation strategies proposed for bridge piers. DOI: 10.1016/j.istruc.2021.05.041.[4]

Research Impact

Govahi’s research publications have received approximately 80 citations within engineering and infrastructure studies. His work demonstrates measurable visibility in seismic engineering research.[1]

The integration of machine learning into structural assessment represents a notable aspect of his research impact. His studies contribute to modern infrastructure monitoring and damage evaluation techniques.[2]

Award Suitability

Ehsan Govahi demonstrates strong alignment with the objectives of the Research Excellence Award. His work combines seismic engineering research with computational intelligence applications for infrastructure analysis.[4]

His participation in post-earthquake inspection activities in Kermanshah Province also reflects practical engagement with structural safety and disaster response engineering.[8]

Conclusion

Ehsan Govahi has contributed to research in earthquake engineering, bridge resilience, and machine learning-assisted structural diagnostics. His scholarly activities support continued advancements in infrastructure safety and seismic assessment methodologies.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Ehsan Govahi, Author ID 57224947757.https://www.scopus.com/authid/detail.uri?authorId=57224947757
  2. Salkhordeh, M., et al. (2023). A rapid machine learning-based damage detection technique for detecting local damages in reinforced concrete bridges.https://doi.org/10.1080/13632469.2023.2193277
  3. Govahi, E., et al. (2022). Cyclic performance of different mitigation strategies proposed for segmental precast bridge piers.https://doi.org/10.1016/j.istruc.2021.12.020
  4. Salkhordeh, M., Govahi, E., & Mirtaheri, M. (2021). Seismic fragility evaluation of various mitigation strategies proposed for bridge piers.https://doi.org/10.1016/j.istruc.2021.05.041
  5. Govahi, E., Salkhordeh, M., & Mohammadi, R. K. (2025). A strengthened convolutional neural network algorithm for identifying the extent of seismic damage in moment-frame buildings.

Sinan Eğri | Engineering | Research Excellence Award

Prof. Dr. Sinan Eğri | Engineering | Research Excellence Award

Tokat Gaziosmanpaşa University | Turkey

Prof. Dr. Sinan Eğri is a distinguished researcher in polymer science, biomaterials engineering, and sustainable biobased polymer technologies, recognized for his impactful contributions to advanced material design for biomedical and industrial applications. His research integrates polymer synthesis, reactive extrusion, biodegradable scaffold engineering, nanocomposite development, and green nanotechnology, with a particular emphasis on creating innovative materials that address critical challenges in tissue engineering and regenerative medicine. His scientific portfolio includes the development of PLA-PEG-PLA systems, electrospun vascular scaffolds, cryogel-based biomaterials, biobased polymer nanocomposites, and environmentally friendly nanoparticle systems, all of which demonstrate his multidisciplinary approach to material innovation. Prof. Dr. Sinan Eğri has produced a strong body of work with 17 Scopus-indexed documents, cited by 355 publications, accumulating 363 Scopus citations and an h-index of 8, underscoring his research influence in polymer chemistry and biomaterials research. His widely cited studies on maleic anhydride grafting, VEGF/BMP-2 releasing scaffolds, nanomechanical characterization of biodegradable materials, and phage-encapsulated biomaterials have advanced understanding in both fundamental polymer science and applied biomedical engineering. He has successfully completed 21 research projects, spanning supercritical CO₂ polymerization, biopolymer processing, bone tissue engineering materials, green nanoparticle biosynthesis, and biodegradable composite design, along with multiple consultancy-based R&D collaborations. In addition to his publications, Prof. Dr. Sinan Eğri contributes to the scientific community through editorial service, peer-reviewing, and international research collaborations, continuously driving innovations that support progress in polymer engineering, sustainable materials, and medical biomaterials.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate

Featured Publications

1. Taşdelen, T. B., Eğri, Ö., & Eğri, S. (2025). Enhancing the electrical conductivity of electrospun PCL fibers by coating with polydopamine and in situ gold nanoparticles doped on the polydopamine coating. Polymers, 17(23), 3192.

2. Eğri, Ö., Güneş, F., & Eğri, S. (2025). Production and characterization of H. perforatum oil-loaded, semi-resorbable, tri-layered hernia mesh. Polymers, 17(2), 240.

3. Demirci, S., Oncer, N., Mazlumoglu, H., Yilmaz, A., Egri, S., Egri, O., & Yilmaz, M. (2024). Polydopamine-mediated gold nanostructure-decorated electrospun polycaprolactone fibers for photocatalytic dye degradation. ChemistrySelect, 9, Article e202304494.

4. Yerliyurt, K., & Eğri, S. (2023). Effect of knitting pattern of PP mesh on the flexural properties of heat-cured PMMA denture base resin. Cumhuriyet Science Journal, 44(3), Article 1184249.

5. Yerliyurt, K., Taşdelen, T. B., Eğri, Ö., & Eğri, S. (2023). Flexural properties of heat-polymerized PMMA denture base resins reinforced with fibers with different characteristics. Polymers, 15(15), 3211.