Rajesh Kumar Samala | Engineering | Innovative Research Award

Published on by Forensic Scientist Awards

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

Published on by Forensic Scientist Awards

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

Published on by Forensic Scientist Awards

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

Guangzhen Si | Engineering | Innovative Research Award

Published on by Forensic Scientist Awards

Innovative Research Award

Guangzhen Si
Affiliation Zhejiang University of Technology
Country China
Scopus ID 57192688905
Documents 17
Citations 359
h-index 6
Subject Area Engineering
Event International Forensic Scientist Awards

Guangzhen Si
Zhejiang University of Technology, China

Guangzhen Si is a researcher affiliated with Zhejiang University of Technology, China, whose documented scholarly profile is associated with engineering research. The available bibliographic record lists 17 documents, 359 citations, and an h-index of 6 in Scopus. [1] These indicators provide a quantitative view of the researcher’s indexed publication and citation activity.

Abstract

This academic recognition profile presents the documented research record of Guangzhen Si in engineering. The available Scopus information identifies 17 indexed documents, 359 citations, and an h-index of 6. [1] A 2026 conference paper further records Si as a co-author of research on multi-scale dynamic adaptive attention mechanisms for cross-domain specific emitter identification, indicating engagement with computational and signal-processing research themes. [2]

Keywords

Engineering; adaptive attention mechanisms; specific emitter identification; cross-domain learning; computational research; research impact; bibliometrics.

Introduction

Guangzhen Si is affiliated with Zhejiang University of Technology and is represented in the Scopus database under author ID 57192688905. [1] The available record places the research profile within Engineering and provides bibliometric indicators that can be used to describe indexed scholarly activity.

Research Profile

The documented research profile combines engineering-oriented scholarly output with work involving computational methods. The reported Scopus indicators of 17 documents and 359 citations, together with an h-index of 6, provide measurable evidence of indexed research activity. [1]

Research Contributions

A recorded 2026 conference contribution titled MAAB: Multi-scale Dynamic Adaptive Attention Mechanisms for Cross-Domain Specific Emitter Identification lists Guangzhen Si among its authors. The work addresses adaptive attention mechanisms in the context of cross-domain specific emitter identification, illustrating an application of machine-learning approaches to an engineering research problem. [2]

Publications

The documented publication record includes the following 2026 conference paper:

  • MAAB: Multi-scale Dynamic Adaptive Attention Mechanisms for Cross-Domain Specific Emitter Identification. H. Zou, M. Wang, J. Wang, G. Si. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (LNICST), 2026. [2]

Research Impact

The Scopus record reports 359 citations across 17 documents, with an h-index of 6. [1] These figures describe citation activity within the indexed database and should be interpreted in relation to publication year, field-specific citation practices, and database coverage.

Award Suitability

For the International Forensic Scientist Awards, the available record provides identifiable evidence of engineering research activity, indexed publications, citation impact, and a recent contribution involving adaptive computational methods. [1] [2] Final award assessment should consider the complete nomination materials, verified publication record, originality, and the criteria established by the award organizers.

Conclusion

Guangzhen Si’s documented scholarly profile reflects engineering research activity supported by indexed publication and citation indicators. The 2026 conference contribution on adaptive attention mechanisms provides a specific example of current research involvement, while the reported Scopus metrics offer a quantitative description of the broader indexed record. [1] [2]

References

  1. Elsevier. (n.d.). Scopus author details: Guangzhen Si, Author ID 57192688905. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57192688905
  2. Zou, H., Wang, M., Wang, J., & Si, G. (2026). MAAB: Multi-scale Dynamic Adaptive Attention Mechanisms for Cross-Domain Specific Emitter Identification. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (LNICST).
  3. Zhejiang University of Technology. Institutional research and academic information concerning engineering research activities.
  4. International Forensic Scientist Awards. Award information and nomination resources.
    forensicscientist.org

Behzad Motallebi Azar | Engineering | Best Researcher Award

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Best Researcher Award

Behzad Motallebi Azar
Sahand University of Technology, Iran

Behzad Motallebi Azar
Affiliation Sahand University of Technology
Country Iran
Scopus ID 57221133046
Documents 7
Citations 45
h-index 4
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0002-7964-0507

Behzad Motallebi Azar is an engineering researcher whose documented scholarly work addresses contemporary energy-system challenges, including prosumer participation, peer-to-peer energy trading, renewable-energy integration, energy storage, hydrogen power systems, and intelligent forecasting. His publication record includes journal, conference, and book-chapter contributions spanning optimization, reinforcement learning, transactive energy, and hybrid energy systems. The available bibliometric information records 7 documents, 45 citations, and an h-index of 4 in Scopus. [1]

Abstract

The research profile of Behzad Motallebi Azar is characterized by work in energy-system engineering and computational approaches to decentralized electricity systems. His publications examine peer-to-peer energy trading, prosumer behavior, net-load forecasting, hydrogen-based power systems, transactive energy, and interconnected hybrid energy systems. Recent work combines deep reinforcement learning and blockchain-based settlement concepts for prosumer markets, reflecting the growing role of intelligent computational methods in energy-system coordination. [2] [3]

Keywords

  • Energy Systems
  • Peer-to-Peer Energy Trading
  • Deep Reinforcement Learning
  • Prosumer Markets
  • Renewable Energy

Introduction

Modern energy systems increasingly require methods capable of coordinating distributed generation, flexible demand, storage, and prosumer participation. Research in this area has consequently expanded toward decentralized markets, intelligent forecasting, and computational optimization. Motallebi Azar’s documented publications fit within this broader engineering context, addressing both market mechanisms and operational strategies for interconnected energy resources. [4]

Research Profile

The research portfolio demonstrates an interdisciplinary connection between energy engineering, artificial intelligence, optimization, and distributed energy management. The 2026 Journal of Cleaner Production article investigates optimal prosumer participation in dual peer-to-peer markets through multi-agent deep reinforcement learning, fuzzy satisfaction levels, and blockchain settlement. [2] A 2025 conference contribution examines household-prosumer net-load forecasting using deep reinforcement learning. [3] Earlier book chapters extend the profile into techno-economic hydrogen systems, transactive energy, and coalition operation of hybrid energy systems. [5] [6]

Research Contributions

  • Application of multi-agent deep reinforcement learning to prosumer participation and peer-to-peer energy markets.
  • Investigation of deep reinforcement learning for household net-load forecasting.
  • Analysis of techno-economic considerations in centralized green-hydrogen power systems.
  • Review and analysis of transactive energy and peer-to-peer trading applications.
  • Study of coalition-based operation in interconnected hybrid energy systems incorporating renewable resources, storage, and local conversion technologies.

Publications

  1. Optimal prosumer participation in dual peer-to-peer markets using multi-agent deep reinforcement learning, fuzzy satisfaction level, and blockchain settlement. Journal of Cleaner Production, 2026.
  2. Net Load Forecasting of Household Prosumers Considering Deep Reinforcement Learning. 2025 33rd International Conference on Electrical Engineering (ICEE), 2025.
  3. Techno-Economic Analysis for Centralized GH2 Power Systems. Book chapter, 2024.
  4. Transactive Energy and Peer-to-Peer Trading Applications in Energy Systems: An Overview. Book chapter, 2023.
  5. Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems. Book chapter, 2022.

Research Impact

The available Scopus indicators record 7 documents, 45 citations, and an h-index of 4 for the researcher identified by Scopus Author ID 57221133046. [1] These indicators provide a bibliometric snapshot of the documented research output and citation visibility. The publication portfolio also shows continuity across several related themes, progressing from hybrid-energy-system operation and transactive-energy applications toward data-driven forecasting and intelligent peer-to-peer market coordination.

Award Suitability

Based on the supplied publication record and bibliometric information, Behzad Motallebi Azar presents a research profile relevant to consideration for the Best Researcher Award at the International Forensic Scientist Awards. The suitability assessment can be grounded in documented scholarly output, multidisciplinary energy-system research, peer-reviewed and scholarly publications, and measurable citation indicators rather than unsupported claims of distinction. Final award decisions remain subject to the applicable evaluation criteria and review process.

Conclusion

Behzad Motallebi Azar’s documented research focuses on emerging methods for intelligent and decentralized energy systems. His work connects peer-to-peer electricity markets, prosumer participation, reinforcement learning, forecasting, hydrogen power systems, transactive energy, renewable resources, and energy storage. The combination of publication activity and recorded citation indicators provides a concise basis for recognizing his continuing contribution to engineering research. [1]

References

  1. Elsevier. (n.d.). Scopus author details: Behzad Motallebi Azar, Author ID 57221133046. Scopus.
    https://www.scopus.com/pages/authors/57221133046
  2. Motallebi Azar, B., et al. (2026). Optimal prosumer participation in dual peer-to-peer markets using multi-agent deep reinforcement learning, fuzzy satisfaction level, and blockchain settlement. Journal of Cleaner Production.
    https://doi.org/10.1016/j.jclepro.2026.149041
  3. Motallebi Azar, B., et al. (2025). Net Load Forecasting of Household Prosumers Considering Deep Reinforcement Learning. 2025 33rd International Conference on Electrical Engineering (ICEE).
    https://doi.org/10.1109/icee67339.2025.11213685
  4. Motallebi Azar, B., et al. (2023). Transactive Energy and Peer-to-Peer Trading Applications in Energy Systems: An Overview. Book chapter.
    https://doi.org/10.1007/978-3-031-35233-1_3
  5. Motallebi Azar, B., et al. (2024). Techno-Economic Analysis for Centralized GH2 Power Systems. Book chapter.
    https://doi.org/10.1007/978-3-031-52429-5_3
  6. Motallebi Azar, B., et al. (2022). Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems. Book chapter.
    https://doi.org/10.1007/978-3-030-87653-1_7

Andrii Hovorukha | Engineering | Best Researcher Award

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Mr. Andrii Hovorukha | Engineering | Best Researcher Award

M.S. Poliakov Institute of Geotechnical Mechanics of the National Academy of Sciences | Ukraine

Mr. Andrii Hovorukha is a researcher specializing in the mechanics, dynamics, and tribology of railway and industrial transport systems. His work focuses on the mathematical modeling of dynamic interactions, wear, and operational safety of track structures, rolling stock, and heavily loaded mining equipment. He has authored 36 scientific publications with 15 citations and a Google Scholar h-index of 3, contributing to international journals and conference proceedings. His research includes the development of innovative friction modifier technologies, particularly the “Ideal” repair and restoration mixture, which forms wear-resistant nanostructured layers, significantly extending equipment service life. Mr. Andrii Hovorukha’s contributions advance the reliability, safety, and efficiency of industrial and railway transport systems, bridging theoretical modeling with practical industrial applications.

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View Google Scholar Profile  View ORCID Profile

Featured Publications


Improvement of the service life of mining and industrial equipment by using friction modifiers

– V.V. Hovorukha, A.V. Hovorukha · Scientific Bulletin of National Mining University, 2023 · Cited by 3


Исследование динамики приводов стрелочных переводов горного транспорта

– A.V. Hovorukha, S.L. Ladik · Геотехнічна механіка, 2015 · Cited by 3


Method for studying spatial vibrations of a vehicle during its movement along the rail track on separate supports with elastic-dissipative and inertial properties

– L.P. Semyditna, V.V. Hovorukha, A.V. Hovorukha, T.P. Sobko · Геотехнічна механіка, 2022 · Cited by 2


Research of deformed state of railway track joint zones in complex operating conditions of rail transport

– V.V. Hovorukha, A.V. Hovorukha, Y.O. Makarov, T.P. Sobko, L.P. Semyditna · Геотехнічна механіка, 2023 · Cited by 1

Kirubakaran Annamalai | Engineering | Research Excellence Award

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Dr. Kirubakaran Annamalai | Engineering | Research Excellence Award

National Institute of Technology Warangal | India

Dr. Kirubakaran Annamalai, Associate Professor at the Department of Electrical Engineering, National Institute of Technology, Warangal, is a distinguished researcher in Power Electronics, Renewable Energy Systems, and Distributed Generation, with a primary focus on the design, analysis, and implementation of multilevel inverters, DC-DC and DC-AC converters, grid-tied photovoltaic systems, and power quality improvement techniques. He has made significant contributions to quasi-Z-source and switched-capacitor-based inverter topologies, emphasizing high efficiency, reduced device counts, leakage current minimization, and real-time control using DSP, FPGA, and dSPACE platforms. Dr. Kirubakaran Annamalai has published 70 peer-reviewed articles, accumulating 1,563 citations with an h-index of 14 (Scopus), in top international journals such as IEEE Transactions on Power Electronics, IEEE Journal of Emerging and Selected Topics in Power Electronics, and Springer’s Journal of Electrical Engineering, and has presented extensively at IEEE and global conferences. He has authored multiple book chapters on advanced power electronics for solar PV and hybrid renewable systems, demonstrating his expertise in sustainable energy technologies. He has successfully led and collaborated on research projects funded by SERB, DST-FIST, SPARC, and SIRE, with budgets ranging from Rs. 2.8 Lakhs to over Rs. 94 Lakhs, focusing on innovative converter designs, smart grid laboratories, and electric vehicle applications, and holds patents on transformer less multilevel inverters. Dr. Kirubakaran Annamalai has supervised numerous Ph.D. and M.Tech scholars, advancing frontier research in power electronics. Recognized for his research excellence through the SIRE Fellowship 2023, multiple IEEE Best Paper Awards, editorial contributions, conference chairing, and active membership in IEEE, ISTE, and other professional bodies, he continues to drive innovation in inverter topologies, grid integration strategies, and renewable energy systems, making a lasting impact on modern power conversion technologies.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

  • Palakurthi, R., & Kirubakaran, A. (2025). DSP controlled single-phase two-stage five-level inverter for high-efficiency grid-connected photovoltaic systems. Electrical Engineering, 108(1).

  • Palakurthi, R., & Kirubakaran, A. (2025). Rapid prototyping of FPGA controlled common ground single-phase transformerless five-level inverter using Xilinx System Generator. IEEE Latin America Transactions, 23(7), 609–618.

  • Kalyan Singh, K., & Kirubakaran, A. (2025). Single-phase five-level common ground transformerless switched capacitor inverters for PV applications with double gain. In 2025 Fourth International Conference on Power, Control and Computing Technologies (ICPC2T).

  • Barzegarkhoo, R., Kirubakaran, A., Pereira, T., Liserre, M., & Siwakoti, Y. P. (2024). Improved T-type and ANPC multilevel converters by means of GaN-based T-cell branch and bidirectional device. In IECON 2024 – 50th Annual Conference of the IEEE Industrial Electronics Society.

  • Kirubakaran, A., Barzegarkhoo, R., & Liserre, M. (2024). A new single-phase dual-mode active neutral point-clamped five-level inverter for renewable applications. In 2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T).

Abdelkader Slimane | Engineering | Editorial Board Member

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Assoc. Prof. Dr. Abdelkader Slimane | Engineering | Editorial Board Member

University of Science and Technology of Oran Mohamed Boudiaf | Algeria

Dr. Abdelkader Slimane is a highly accomplished mechanical engineering researcher whose work has made significant contributions to structural integrity, fracture mechanics, advanced manufacturing, and aerospace-related mechanical systems. His research expertise encompasses ductile damage modeling, fatigue crack growth prediction, welded structure assessment, rotary ultrasonic machining, vibration behavior, and the mechanical reliability of composite and metallic materials. With 20 scholarly publications, his work appears in leading international journals such as Journal of Materials Research and Technology, Mechanics of Advanced Materials and Structures, International Journal of Advanced Manufacturing Technology, Periodica Polytechnica Mechanical Engineering, Fracture and Structural Integrity, and Interactive Design and Manufacturing (IJIDeM). These publications collectively highlight his impactful contributions to areas including satellite structural design, hypervelocity impact simulation, cracked pipeline modeling, active power filtering using neural networks, and the optimization of machining and welding parameters through innovative computational and experimental approaches. Dr. Slimane’s Google Scholar metrics 464 citations, an h-index of 13, and an i10-index of 16—demonstrate the strong visibility and influence of his work across the mechanical engineering community. His extensive conference participation has further broadened the dissemination of his research in domains such as fracture mechanics, material behavior, aeronautical engineering, and mechanical system optimization. In addition to his research achievements, he contributes meaningfully to the scientific community through editorial service in reputable journals and active peer-review roles for numerous international publications. Dr. Slimane’s multidisciplinary research profile reflects a sustained commitment to advancing structural reliability, material innovation, computational mechanics, and engineering solutions that support modern industrial and aerospace applications.

Profile: Google Scholar

Featured Publications

1. Slimane, A., Bouchouicha, B., Benguediab, M., & Slimane, S. A. (2015). Parametric study of the ductile damage by the Gurson–Tvergaard–Needleman model of structures in carbon steel A48-AP. Journal of Materials Research and Technology, 4(2), 217–223.

2. Slimane, S. A., Slimane, A., Guelailia, A., Boudjemai, A., Kebdani, S., Smahat, A., … (2022). Hypervelocity impact on honeycomb structure reinforced with bi-layer ceramic/aluminum facesheets used for spacecraft shielding. Mechanics of Advanced Materials and Structures, 29(25), 4487–4505.

3. Slimane, S., Kebdani, S., Boudjemai, A., & Slimane, A. (2018). Effect of position of tension-loaded inserts on honeycomb panels used for space applications. International Journal on Interactive Design and Manufacturing (IJIDeM), 12(2),

4. Slimane, A., Bouchouicha, B., Benguediab, M., & Slimane, S. A. (2015). Contribution to the study of fatigue and rupture of welded structures in carbon steel A48-AP: Experimental and numerical study. Transactions of the Indian Institute of Metals, 68(3), 465–477.

5. Slimane, A., Slimane, S., Kebdani, S., Chaib, M., Dahmane, S., Bouchouicha, B., … (2019). Parameters effects analysis of rotary ultrasonic machining on carbon fiber reinforced plastic (CFRP) composite using an interactive RSM method. International Journal on Interactive Design and Manufacturing (IJIDeM), 13(2),

Surakasi Raviteja | Engineering | Excellence in Research Award

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Assist. Prof. Dr. Surakasi Raviteja | Engineering | Excellence in Research Award

Lendi Institute of Engineering and Technology | India

Dr. Surakasi Ravi Teja is a dedicated researcher whose work spans thermal engineering, nanofluids, biofuels, heat transfer augmentation, sustainable energy systems, and advanced materials science. His research expertise includes the experimental evaluation of thermophysical properties, development of nanomaterial-enhanced solar thermal fluids, ANN-based predictive modeling, biodiesel and pyrolysis-fuel combustion analysis, and CFD-driven optimization of thermal devices. With 77 Scopus-indexed publications, 960 citations, and an h-index of 17, he has established a strong scientific presence, contributing extensively to high-impact Scopus-, SCI-, and SCIE-indexed journals such as Frontiers in Heat and Mass Transfer, Journal of Nanomaterials, Materials Today: Proceedings, International Journal of Chemical Engineering, and Adsorption Science & Technology. His Q1–Q2 publications reflect significant advancements in areas including nanofluid stability, enhanced heat transfer, eco-friendly fuel blends with  , and nano-reinforced composite materials. His interdisciplinary works extend to solar water heating systems, cryogenic vessel design, adsorption-based separation technologies, and nanoparticle-assisted wastewater treatment. Several of his highly cited studies focus on waste-to-energy conversion, algae-oil biodiesel applications, and green-synthesized nanoparticles for environmental remediation, highlighting his contribution to sustainable and cleaner energy technologies. In addition to his research output, Dr. Teja serves as a reviewer for numerous national and international journals and holds editorial memberships, contributing to global scholarly communication and knowledge dissemination. His consistent research engagement, innovation-driven approach, and interdisciplinary collaborations underscore his impactful role in advancing thermal sciences, materials engineering, and renewable energy research.

Profiles: Scopus | Google Scholar | ORCID | Staff Profile

Featured Publications

  1. Sathish, T., Vijayalakshmi, A., Surakasi, R., Ahalya, N., Rajkumar, M., … (2024). DeepNNet 15 for the prediction of biological waste to energy conversion and nutrient level detection in treated sewage water. Process Safety and Environmental Protection, 189, 636–647.

  2. Senthil, T. S., Puviyarasan, M., Babu, S. R., Surakasi, R., & Sampath, B. (2023). Industrial robot-integrated fused deposition modelling for the 3D printing process. In Development, Properties, and Industrial Applications of 3D Printed Polymer Materials

  3. Lakshmaiya, N., Surakasi, R., Nadh, V. S., Srinivas, C., Kaliappan, S., … (2023). Tanning wastewater sterilization in the dark and sunlight using Psidium guajava leaf-derived copper oxide nanoparticles and their characteristics. ACS Omega, 8(42), 39680–39689.

  4. Nirmal Kumar, K., Dinesh Babu, P., Surakasi, R., Kumar, P. M., & Ashokkumar, P. (2022). Mechanical and thermal properties of bamboo fiber–reinforced PLA polymer composites: A critical study. International Journal of Polymer Science, 2022(1), 1332157.

  5. Vennila, T., Karuna, M. S., Srivastava, B. K., Venugopal, J., & Surakasi, R. (2023). New strategies in treatment and enzymatic processes: Ethanol production from sugarcane bagasse. In Human Agro-Energy Optimization for Business and Industry (pp. 219–240).

Volodymyr Hovorukha | Engineering | Best Researcher Award

Published on by Forensic Scientist Awards

Mr. Volodymyr Hovorukha | Engineering | Best Researcher Award

M.S. Poliakov Institute of Geotechnical Mechanics of the National Academy of Sciences of Ukraine | Ukraine

Mr. Volodymyr Hovorukha is a prominent Ukrainian scientist whose pioneering contributions have shaped the fields of railway engineering, transport mechanics, and structural dynamics. As a Senior Researcher at the M.S. Poliakov Institute of Geotechnical Mechanics of the National Academy of Sciences of Ukraine, he has made outstanding advancements in understanding the interaction between rail tracks and moving transport systems, the mechanics of deformation, and the reliability of rail infrastructure. His scientific achievements encompass the development of over ten mathematical models addressing dynamic rail–vehicle interaction, wear processes, and derailment safety, particularly under the influence of friction modifiers. He has authored more than 240 scientific papers, including publications indexed in international databases such as Scopus, and four monographs registered with ISBN. Mr. Volodymyr Hovorukha holds 32 patents, three of which have been officially recognized as international discoveries in railway transport. His innovative research has led to the creation of modernized track structures, high-speed rail fastening systems, and reinforced concrete components for both surface and underground transport systems. Under his scientific leadership, over 200 projects have been successfully developed and implemented, significantly contributing to the modernization of Ukraine’s rail infrastructure. His findings on the deformation mechanics of track elements and materials have become the foundation for optimizing the durability and safety of rail systems. An active member of ASME International and the International Academy of Scientific Discoveries and Inventions, Mr. Volodymyr Hovorukha’s research continues to influence railway engineering innovation and infrastructure development globally.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Hovorukha, V., Hovorukha, A., Sobko, T., & Semyditna, L. (2025). Reliability improvement of track infrastructure in open-pit rail transport. Geo-Technical Mechanics, (173), 38–48. https://doi.org/10.15407/geotm2025.173.038

  2. Hovorukha, V. V., & Hovorukha, A. V. (2023). Improvement of the service life of mining and industrial equipment by using friction modifiers. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (4), 74–82. https://doi.org/10.33271/nvngu/2023-4/074

  3. Hovorukha, V., Hovorukha, A., & Makarov, Y. (2022). Research on the dynamic processes of vehicles and an arbitrary configuration rail track, influencing the side wear of the rail head and wheel flange contact surfaces at different values of friction coefficient between them. IOP Conference Series: Earth and Environmental Science, 970(1), 012029. https://doi.org/10.1088/1755-1315/970/1/012029

  4. Hovorukha, V., Hovorukha, A., Sobko, T., & Semyditna, L. (2022). Method for studying spatial vibrations of a vehicle during its movement along the rail track on separate supports with elastic-dissipative and inertial properties. Geo-Technical Mechanics, (167), 52–60.

  5. Hovorukha, V., Hovorukha, A., Makarov, Y., Sobko, T., & Semyditna, L. (2023, November 14–16). Investigation of residual deformations in joint zones of track sections under curved track operation conditions. In Proceedings of the XXI International Conference of Young Scientists: Geotechnical Problems of Mineral Deposit Development (pp. 145–150). Dnipro, Ukraine.