Jihoon Jang | Engineering | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Jihoon Jang
Affiliation Korea Institute of Civil Engineering and Building Technology
Country South Korea
Scopus ID 57204915562
Documents 7
Citations 226
h-index 6
Subject Area Engineering
Event Global Innovation Technologist Awards

Jihoon Jang
Korea Institute of Civil Engineering and Building Technology, South Korea

Jihoon Jang is an engineering researcher whose work focuses on intelligent building systems, building energy prediction, indoor environmental quality, and data-driven optimization techniques. His published studies demonstrate the integration of artificial intelligence, machine learning, and building energy management systems to improve operational efficiency and sustainability in modern buildings. With a Scopus profile containing seven indexed publications, 226 citations, and an h-index of six, his research has contributed to practical advances in energy-efficient building technologies and predictive analytics.[1]

Abstract

Jihoon Jang’s scholarly work centers on predictive building analytics, energy optimization, and intelligent HVAC operation. His publications demonstrate the practical application of artificial neural networks and long short-term memory (LSTM) models for forecasting heating energy demand and optimizing building operation schedules. These contributions support sustainable infrastructure by improving energy efficiency while maintaining occupant comfort.[2]

Keywords

Building Energy Management, Artificial Intelligence, HVAC Systems, LSTM Networks, Sustainable Engineering, Indoor Environmental Quality, Machine Learning, Energy Prediction.

Introduction

Growing interest in sustainable buildings has accelerated the development of predictive analytical methods capable of reducing energy consumption while maintaining indoor environmental performance. Jihoon Jang’s research contributes to this objective by combining engineering knowledge with artificial intelligence, producing practical solutions applicable to smart buildings and energy management systems.[3]

Research Profile

The research profile reflects interdisciplinary expertise spanning building engineering, thermal performance modeling, data analytics, and intelligent control technologies. Publications appear in internationally recognized journals including Energy and Buildings, Journal of Building Engineering, Sustainability, and Energies. Citation metrics indicate sustained academic visibility within engineering research communities.[1]

Research Contributions

  • Developed LSTM-based prediction models for heating energy consumption in non-residential buildings.
  • Applied artificial neural networks for predicting optimum heating schedules using BEMS datasets.
  • Investigated HVAC cooling set-point optimization considering mean radiant temperature.
  • Improved thermal energy prediction through advanced feature selection methods.
  • Contributed to affordable image sensing technologies for indoor environmental quality monitoring.

Publications

  • Prediction of heating energy consumption with operation pattern variables using LSTM networks (2022) — 136 citations.
  • Prediction of optimum heating timing utilizing BEMS data (2019) — 54 citations.
  • Cooling set-point temperature considering mean radiant temperature (2019) — 35 citations.
  • Improved model for predicting building thermal energy consumption (2019) — 23 citations.
  • Collection and utilization of indoor environmental quality information using image sensing technology (2022) — 22 citations.

Research Impact

The citation performance of Jihoon Jang’s publications demonstrates consistent scholarly influence within engineering and building science. His studies provide methodological foundations for integrating machine learning into practical building operation, supporting energy conservation initiatives and digital transformation in infrastructure management. The combination of predictive modeling and environmental sensing has relevance for future smart-city applications.[4]

Award Suitability

Based on available scholarly indicators, publication quality, and demonstrated engineering contributions, Jihoon Jang’s work aligns with the objectives of the Global Innovation Technologist Awards. His research emphasizes innovation, measurable academic impact, and practical engineering applications, making the profile suitable for consideration within technology-focused academic recognition programs.[5]

Conclusion

Jihoon Jang has established a focused research portfolio addressing intelligent building operation, predictive analytics, and sustainable engineering. Through contributions to high-quality journals and meaningful citation impact, his work supports continued progress toward energy-efficient infrastructure and evidence-based building management technologies.

References

  1. Elsevier. (n.d.). Scopus author details: Jihoon Jang, Author ID 57204915562.
    https://www.scopus.com/authid/detail.uri?authorId=57204915562
  2. Jang J. et al. (2022). Prediction of heating energy consumption with operation pattern variables for non-residential buildings using LSTM networks.
    https://doi.org/10.1016/j.enbuild.2021.111647
  3. Journal of Building Engineering. (2019). Prediction of optimum heating timing based on artificial neural network.
    https://doi.org/10.1016/j.jobe.2018.12.010
  4. Sustainability. (2019). The derivation of cooling set-point temperature in an HVAC system.
    https://doi.org/10.3390/su11195417
  5. Global Innovation Technologist Awards. (n.d.). Official Award Website.
    innovationtechnologist.com

Merve Öztekin | Engineering | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Merve Öztekin
Karadeniz Technical University, Turkey
Merve Öztekin
Affiliation Karadeniz Technical University
Country Turkey
Scopus ID 57848993700
Documents 2
Citations 3
h-index 1
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0009-0007-0470-6229

The Innovative Research Award recognizes researchers whose scholarly activities contribute to technological advancement through high-quality engineering research and measurable scientific outputs. Merve Öztekin of Karadeniz Technical University has developed research focused on transformer differential protection, electrical machines, intelligent control systems, and electric vehicle drive technologies. Recent publications demonstrate continued engagement with modern power engineering challenges while emphasizing analytical methods and practical applications in electrical power systems.[1]

Abstract

Merve Öztekin’s research addresses transformer protection algorithms, wavelet-transform applications, nonlinear motor control, and energy-efficient electric vehicle drive systems. The published work combines theoretical modelling with engineering implementation, contributing to the reliability and efficiency of electrical power equipment. The research portfolio reflects interdisciplinary integration between protection engineering, control theory, and intelligent electrical systems.[2]

Keywords

Transformer Differential Protection, Wavelet Transform, Electric Vehicles, Interior Permanent Magnet Synchronous Motor, Engineering, Power Systems, Electrical Protection, Intelligent Control.

Introduction

Modern electrical engineering increasingly requires dependable protection techniques and efficient motor control strategies to improve system stability and sustainability. Research undertaken by Merve Öztekin contributes to these objectives through investigations into transformer fault detection and optimized electrical drive technologies. Publications appearing in international journals and conference proceedings demonstrate ongoing participation in engineering research.[3]

Research Profile

According to the supplied research profile, the author has published studies involving transformer differential protection algorithms, electric vehicle drive optimization, nonlinear control methods, and power electronics. The available bibliometric indicators include a Scopus Author ID of 57848993700 with documented scholarly output, citations, and an h-index reflecting the current stage of academic development.[1]

Research Contributions

  • Development of low-level inter-turn fault detection algorithms for transformer differential protection.
  • Application of wavelet transform techniques for reliable transformer protection.
  • Research on nonlinear optimal control for interior permanent magnet synchronous motors.
  • Studies supporting energy-efficient electric vehicle drive systems.

Publications

  • Low-Level Inter-Turn Fault Detection Algorithm for Transformer Differential Protection (Applied Sciences, 2026).
  • Transformer Differential Protection with Wavelet Transform and Difference Function (Engineering Science and Technology, 2025).
  • Energy Efficient and Transients Optimal IPMSM Drive for Electric Vehicles (SPEEDAM, 2022).
  • Nonlinear Optimal Control for Interior Permanent Magnet Synchronous Motor Drives (ECC, 2022).
  • Wavelet Transform Based Differential Protection Algorithm for Power Transformer (ELECO, 2016).

Research Impact

The available publication record illustrates sustained interest in power system protection and electric drive optimization. Citation metrics indicate emerging scholarly recognition, while recent journal publications suggest continued research productivity. The work contributes to engineering literature by addressing practical reliability and efficiency challenges in electrical infrastructure.[4]

Award Suitability

Based on the documented publications, engineering specialization, and recent peer-reviewed contributions, Merve Öztekin demonstrates characteristics consistent with consideration for the Global Innovation Technologist Awards. The research portfolio emphasizes innovation in electrical engineering through analytical modelling, transformer protection, and sustainable transportation technologies while maintaining publication activity in recognized scientific venues.[5]

Conclusion

The academic profile presented here reflects an engineering researcher contributing to electrical power systems, intelligent protection methods, and advanced motor control. Through conference papers and peer-reviewed journal articles, the research demonstrates progressive development and continuing engagement with contemporary engineering challenges. The documented achievements provide an appropriate scholarly basis for recognition within an international innovation-focused award framework.

References

  1. Elsevier. (n.d.). Scopus author details: Merve Öztekin, Author ID 57848993700.
    https://www.scopus.com/authid/detail.uri?authorId=57848993700
  2. Öztekin, M. (2026). Low-Level Inter-Turn Fault Detection Algorithm for Transformer Differential Protection.
    https://doi.org/10.3390/app16147073
  3. Öztekin, M. (2025). Transformer Differential Protection with Wavelet Transform and Difference Function.
    https://doi.org/10.1016/j.jestch.2025.102144
  4. IEEE. (2022). Energy Efficient and Transients Optimal IPMSM Drive for Electric Vehicles.
    https://doi.org/10.1109/SPEEDAM53979.2022.9842114
  5. European Control Conference. (2022). Nonlinear Optimal Control for Interior Permanent Magnet Synchronous Motor Drives.
    https://doi.org/10.23919/ECC55457.2022.9838314

Wurod Mohamed | Engineering | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Wurod Mohamed
Affiliation University of Arkansas at Little Rock
Country United States
Scopus ID 57204874896
Documents 12
Citations 30
h-index 3
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0000-0003-2421-1534

Wurod Mohamed

University of Arkansas at Little Rock, United States

Wurod Mohamed is an engineering researcher whose scholarly work focuses on wireless communication systems, signal processing, antenna characterization, electromagnetic modeling, and intelligent communication technologies. Her publications demonstrate continued contributions to millimeter-wave communications, audio transmission enhancement, radar cross-section analysis, and image transmission techniques. The research portfolio reflects interdisciplinary engineering applications supported by computational methods and practical system evaluation, making it relevant to modern wireless infrastructure and emerging communication technologies.[1]

Abstract

The research activities of Wurod Mohamed emphasize engineering solutions for next-generation communication systems through analytical modeling, artificial intelligence, and electromagnetic simulation. Her work addresses practical challenges involving direction-of-arrival estimation, wireless propagation, radar characterization, multimedia transmission, and signal reliability. Publications appearing in recognized engineering journals and conference proceedings demonstrate a balanced combination of theoretical development and practical validation. Collectively, these studies contribute to the advancement of communication system efficiency and electromagnetic engineering while supporting innovation within modern wireless technologies.[2]

Keywords

Wireless Communications, Engineering, Deep Learning, Electromagnetic Modeling, Millimeter-Wave Systems, Signal Processing, Artificial Intelligence, Radar Cross Section.

Introduction

Engineering research increasingly relies on intelligent computational methods to improve communication performance under complex operating conditions. Wurod Mohamed’s scholarly work follows this direction by integrating signal processing algorithms, electromagnetic analysis, and deep learning techniques into communication system design. Her studies illustrate practical engineering approaches that improve estimation accuracy, transmission quality, and propagation modeling across multiple communication environments.[3]

Research Profile

According to the available scholarly profile, the researcher has authored 12 indexed publications with 30 citations and an h-index of 3. The publication record demonstrates sustained engagement in engineering research, particularly wireless communication, antenna systems, artificial intelligence applications, and computational electromagnetic analysis. These contributions indicate active participation in internationally indexed scientific literature.[1]

Research Contributions

  • Development of deep learning-based electromagnetic frameworks for millimeter-wave direction-of-arrival estimation.
  • Research on LMMSE-based enhancement of audio transmission performance.
  • Analysis of shadow path loss models considering antenna gain effects.
  • Image transmission optimization using advanced interleaving techniques.
  • Evaluation of bistatic and monostatic radar cross-section characteristics.

Publications

  • Deep Learning-Based Rigorous Electromagnetic Framework for Direction of Arrival Estimation in Millimeter-Wave Communication Systems Based on Embedded Radiation Patterns, Electronics (2026).
  • Performance Enhancement of Audio Transmission Based on LMMSE Method, Indonesian Journal of Electrical Engineering and Computer Science (2021).
  • Factors Influencing the Shadow Path Loss Model with Different Antenna Gains over Large-Scale Fading Channel, AIMS 2021.
  • New 2-D Interleaving Grouping LBC Applied on Image Transmission, International Journal of Electrical and Computer Engineering (2021).
  • Evaluation of Bistatic and Monostatic RCS for Simple and Complex Targets in X-Band, International Journal of Microwave and Optical Technology (2020).

Research Impact

The research portfolio demonstrates measurable scholarly visibility through indexed publications and citations while addressing technically significant engineering topics. The combination of wireless communications, artificial intelligence, and electromagnetic analysis reflects emerging priorities within communication engineering. The work contributes to improving communication reliability, signal estimation, and computational modeling for practical engineering applications.[4]

Award Suitability

Considering the documented publication record, engineering specialization, and continuing research activity, Wurod Mohamed demonstrates characteristics consistent with recognition by the Global Innovation Technologist Awards. The portfolio illustrates innovation in communication engineering, interdisciplinary application of computational intelligence, and contributions that align with technological advancement and scientific dissemination. The evaluation is based upon publicly available scholarly information and indexed research outputs.[5]

Conclusion

Wurod Mohamed has established a research profile centered on engineering innovation in wireless communications, signal processing, and computational electromagnetics. Through peer-reviewed publications and conference contributions, the researcher has addressed practical communication challenges using analytical and artificial intelligence-based approaches. The documented scholarly record supports recognition within academic engineering communities while demonstrating continuing engagement in research relevant to future communication technologies.

References

  1. Elsevier. (n.d.). Scopus Author Details: Wurod Mohamed, Author ID 57204874896.
    https://www.scopus.com/authid/detail.uri?authorId=57204874896
  2. Mohamed, W. (2026). Deep Learning-Based Rigorous Electromagnetic Framework… Electronics.
    https://doi.org/10.3390/electronics15132934
  3. Mohamed, W. (2021). Performance Enhancement of Audio Transmission Based on LMMSE Method.
    https://doi.org/10.11591/ijeecs.v21.i2.pp903-910
  4. IEEE. (2021). Factors Influencing the Shadow Path Loss Model with Different Antenna Gains over Large-Scale Fading Channel.
    https://doi.org/10.1109/AIMS52415.2021.9466043
  5. Global Innovation Technologist Awards. (n.d.). Official Award Website.
    innovationtechnologist.com

Jakob Reinhardt | Engineering | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Jakob Reinhardt
Technical University of Munich
Jakob Reinhardt
Affiliation Technical University of Munich
Country Germany
Google Scholar aomsnFcAAAAJ
Documents 19
Citations 168
h-index 7
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0000-0002-7562-4104

Jakob Reinhardt is a researcher affiliated with the Technical University of Munich in Germany, recognized for contributions to engineering and human-robot interaction research. His scholarly work has explored robotic motion strategies, ergonomic evaluation in surgical robotics, and the development of socially aware robot behavior models within collaborative environments. Reinhardt’s publications demonstrate an interdisciplinary approach that integrates robotics, computer-assisted surgery, human factors engineering, and interaction design.[1] His academic profile includes peer-reviewed journal articles, conference contributions, and collaborative research outputs indexed within Scopus and Crossref databases.[2]

Abstract

This article presents a scholarly overview of Jakob Reinhardt and his research contributions in the field of engineering, with particular emphasis on human-robot interaction, robotic behavior analysis, and ergonomics in robotic-assisted procedures. His publications have contributed to understanding adaptive robot motion strategies and user-centered interaction mechanisms within collaborative technological systems. Through peer-reviewed studies and interdisciplinary research outputs, Reinhardt has participated in advancing applied robotics and interaction design methodologies within academic and engineering environments.[3]

Keywords

Human-Robot Interaction, Engineering Research, Robotic Motion Strategies, Surgical Robotics, Interaction Design, Human Factors Engineering, Ergonomic Analysis, Collaborative Robotics, Autonomous Systems, Technical University of Munich.

Introduction

Engineering research increasingly relies on interdisciplinary integration between robotics, cognitive systems, and human-centered design methodologies. Jakob Reinhardt’s work reflects these contemporary developments by focusing on socially adaptive robotic systems and the evaluation of robotic interactions within professional and medical contexts.[4] His research activities have addressed challenges associated with robot motion communication, task urgency perception, and ergonomic performance assessment in robotic-assisted surgical procedures.[5]

The broader significance of Reinhardt’s work lies in its applicability to collaborative robotics, healthcare technologies, and intelligent interaction systems. By integrating behavioral design principles with engineering methodologies, his publications contribute to the refinement of safer and more intuitive human-robot collaboration frameworks.[6]

Research Profile

Jakob Reinhardt has contributed to engineering research through publications focused on robotic systems, interaction strategies, and medical technology evaluation. His affiliation with the Technical University of Munich has provided a platform for interdisciplinary collaboration involving robotics, artificial intelligence, ergonomics, and human-computer interaction studies.[1]

  • Research specialization in human-robot interaction and collaborative robotic behavior.
  • Contributions to ergonomic evaluation methodologies in robotic-assisted surgical environments.
  • Development of motion communication strategies for autonomous mobile robots.
  • Participation in peer-reviewed journal and conference publications within engineering disciplines.

Research Contributions

One of Reinhardt’s recognized studies evaluated surgeon posture during simulated laparoscopic and robotic-assisted cholecystectomy procedures. The research contributed to understanding ergonomic challenges associated with robotic surgical systems and highlighted considerations relevant to occupational health and medical engineering design.[7]

His publication titled Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction investigated adaptive motion strategies that allow robots to communicate spatial awareness and collaborative intent more effectively. The findings supported the development of socially responsive robotic systems designed for shared environments.[8]

Reinhardt also contributed to research on hesitant movement gestures for mobile robots, examining how robotic motion influences user interpretation and interaction confidence. The study demonstrated the importance of nonverbal communication mechanisms in robotic navigation and collaborative settings.[9]

Publications

  1. Surgeon posture evaluation during simulated laparoscopic and robotic-assisted cholecystectomy, International Journal of Computer Assisted Radiology and Surgery, 2026.
  2. Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction, ACM Transactions on Human-Robot Interaction, 2021.
  3. Design of a hesitant movement gesture for mobile robots, PLOS ONE, 2021.
  4. Investigating Perceived Task Urgency as Justification for Dominant Robot Behaviour, 2020.

Research Impact

The research impact associated with Jakob Reinhardt’s academic profile is reflected through citation activity, interdisciplinary collaboration, and contributions to applied robotics research. His studies have addressed practical engineering problems associated with interaction safety, motion interpretation, and ergonomics in robotic systems.[2]

With a documented Scopus h-index and international publication record, Reinhardt’s work demonstrates scholarly engagement within engineering and robotic interaction communities. The integration of human-centered principles into robotic system design remains a notable characteristic of his research contributions.[3]

Award Suitability

Jakob Reinhardt’s research profile aligns with the objectives commonly associated with innovation and technology-focused academic recognition programs. His contributions to robotics, interaction design, and engineering evaluation methodologies support advancements in collaborative intelligent systems and applied technological research.[6]

The interdisciplinary nature of his work, including applications in healthcare technology and human-robot collaboration, demonstrates relevance to contemporary engineering challenges and innovation-driven scientific initiatives. His publication history and citation record further support recognition within the context of the Global Innovation Technologist Awards.[4]

Conclusion

Jakob Reinhardt has contributed to engineering and robotics research through investigations into human-robot interaction, ergonomic assessment, and socially adaptive robotic systems. His scholarly publications demonstrate a sustained focus on improving collaborative robotic behavior and evaluating the practical implications of robotic technologies within professional and medical environments.[7] The combination of interdisciplinary methodology, peer-reviewed publication activity, and measurable research impact supports his recognition within international academic and technological award platforms.[8]

References

  1. ORCID. (n.d.). Jakob Reinhardt researcher profile. ORCID Registry.
    https://orcid.org/0000-0002-7562-4104
  2. Elsevier. (n.d.). Scopus author details: Jakob Reinhardt, Author ID 57201292569. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57201292569
  3. PLOS ONE. (2021). Design of a hesitant movement gesture for mobile robots.
    https://doi.org/10.1371/journal.pone.0249081
  4. ACM Transactions on Human-Robot Interaction. (2021). Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction.
    https://doi.org/10.1145/3418303
  5. Springer. (2020). Investigating Perceived Task Urgency as Justification for Dominant Robot Behaviour.
    https://doi.org/10.1007/978-3-030-50726-8_15
  6. Technical University of Munich. (n.d.). Research affiliation and academic activities.
  7. International Journal of Computer Assisted Radiology and Surgery. (2026). Surgeon posture evaluation during simulated laparoscopic and robotic-assisted cholecystectomy.
    https://doi.org/10.1007/s11548-026-03666-4
  8. Open Science Framework. (2020). Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction.
    https://doi.org/10.31234/osf.io/ws2ez
  9. Crossref. (n.d.). Publication indexing and DOI registry records for Jakob Reinhardt.

Gul Durak | Engineering | Best Research Article Award

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Ms. Gul Durak | Engineering | Best Research Article Award

Yildiz Technical University | Turkey

Ms. Gul Durak is an industrial engineering professional with strong applied expertise at the intersection of air cargo logistics, operations management, and cost optimization, developed through extensive practice in a global airline and manufacturing environments. Her professional focus centers on operational efficiency, air cargo logistics systems, cost analysis, and financial decision-support, combining analytical rigor with real-world logistics performance needs. She has built advanced competence in evaluating operation costs, managing logistics workflows, supporting strategic negotiations, and contributing to company-level management decisions within complex, large-scale organizations. Her experience spans air cargo operations, logistics specialization, and engineering roles that emphasize data-driven optimization and performance improvement, supported by quantitative tools and optimization software. In parallel, her research orientation reflects a growing interest in industrial engineering methodologies, logistics finance, and decision-making models that enhance efficiency and sustainability in transportation and supply chain systems. She has contributed to cost optimization initiatives recognized for their impact, demonstrating an ability to translate analytical research into actionable operational improvements. Alongside professional practice, she actively engages with academic and industry communities through invited talks and knowledge-sharing activities, highlighting her commitment to bridging theory and practice. Her skill set includes advanced logistics analytics, negotiation, financial analysis, and operations research tools, complemented by multilingual communication abilities that support international collaboration. Overall, her profile reflects a practitioner-researcher perspective, combining industrial engineering research interests with hands-on expertise in air cargo logistics and cost-focused operational strategy.

Profiles: Scopus | Orcid 

Featured Publication

Durak, G., & Çetin Demirel, N. (2025). Cargo aircraft capacity optimization: A hybrid approach comprising a genetic algorithm and large neighborhood search. Applied Sciences, 15(22), 11988.

Adel Asheri | Semiconductor Devices | Best Researcher Award

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Prof. Adel Asheri | Semiconductor Devices | Best Researcher Award

Full Time Professor at National research centre | Egypt

Adel Ashery Saleh Khalil is a distinguished physicist and full professor at the National Research Center, where he leads the Department of Solid State Physics. His expertise spans the preparation and characterization of single crystal devices and thin films, employing advanced techniques such as liquid phase epitaxial growth, electrochemical ionization, diffusion furnace processes, photolithography, chemical vapor deposition, spin coating, and sol-gel methods. He has manually developed and optimized these methodologies, demonstrating deep hands-on proficiency in experimental physics and materials science. His research focuses on the development of novel heterostructures and composite materials with enhanced electrical, dielectric, and optoelectronic properties, contributing significantly to resistive memory devices, high-k electronics, and advanced electronic components. Among his recent publications, he has explored Ag/Al/SiO2/n-Si/Ag heterostructures for dielectric tunability, Ag/MWCNTs-PVA composites exhibiting high electrical conductance and tunable capacitance, polypyrrole-multi-well carbon nanotube/titanium oxide/aluminum oxide/p-silicon heterojunctions for optoelectronic applications, dielectric properties of lattice-mismatched GaAs/p-Si heterojunction diodes, and gel-based PVA/SiO2/p-Si heterojunctions for electronic devices. With a total of 996 citations across 617 documents, 89 publications, and an h-index of 17, his work demonstrates both the impact and recognition of his contributions in the field. Combining theoretical understanding with practical implementation, he has established himself as a leading researcher in solid-state physics, particularly in the synthesis and characterization of advanced materials, devices, and heterostructures that address contemporary challenges in electronic and optoelectronic applications.

Profile: Scopus

Featured Publications

  • Ashery, A. (2025). Interfacial engineering and dielectric tunability in Ag/Al/SiO2/n-Si/Ag heterostructures: Novel insights for resistive memory and high-κ electronics. Physica B: Condensed Matter, 417758.

  • Ashery, A. (2025). Ag/MWCNTs-PVA composite/n-Si/Ag exhibits a novel combination of high electrical conductance and tunable capacitance in magnitude and sign. ECS Journal of Solid State Science and Technology.

  • Ashery, A., Gaballah, A. E. H., Elmoghazy, E., & Kabatas, M. A. B. M. (2025). Investigation of the optoelectronic properties of a novel polypyrrole-multi-well carbon nanotubes/titanium oxide/aluminum oxide/p-silicon heterojunction. Nanotechnology Reviews, 14(1), 20250174.

  • Ashery, A., Gaballah, A. E. H., Elnasharty, M. M. M., & Kabatas, M. A. B. M. (2024). Dielectric properties of epitaxially grown lattice-mismatched GaAs/p-Si heterojunction diode. iScience, 27(9).

  • Ashery, A., Gaballah, A. E. H., Turky, G. M., & Basyooni-Murat Kabatas, M. A. (2024). Gel-based PVA/SiO2/p-Si heterojunction for electronic device applications. Gels, 10(8), 537.

 

 

 

Ashish Ranjan Dash | Engineering | Best Researcher Award

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Dr. Ashish Ranjan Dash | Engineering | Best Researcher Award

Associate Professor at Centurion University of Technology and Management | India

Dr. Ashish Ranjan Dash is a highly accomplished academic and researcher in the field of electrical engineering, specializing in power electronics, multilevel inverters, and power quality improvement. With a proven track record in research, teaching, and project leadership, he has significantly contributed to advancements in smart infrastructure, renewable energy systems, and IoT-enabled agricultural automation. He has also played a pivotal role in supervising doctoral students, developing innovative solutions for industrial applications, and leading consultancy projects for technology-driven agriculture and smart systems.

Publication Profile 

Scopus

Google Scholar

Educational Background 

Dr. Dash earned his Ph.D. in Power Electronics from the National Institute of Technology (NIT) Rourkela, focusing on cascaded multilevel inverter-based shunt active filters under varying grid voltage conditions. He also holds an M.Tech. in Power Control and Drives from NIT Rourkela, where his dissertation explored control strategies for grid-connected inverter systems during fault conditions. His academic foundation is further strengthened by a B.Tech. in Electrical Engineering and a Diploma in Electrical Engineering, complemented by a strong record of academic excellence throughout his studies.

Professional Experience 

With over a decade of academic and research experience, Dr. Dash serves as an Associate Professor at Centurion University of Technology and Management, Odisha. His prior roles include research and academic positions in engineering colleges and at the Council of Scientific and Industrial Research. He has held key administrative positions such as Dean and Associate Dean of the School of Engineering and CEO of the Smart Infrastructure Research Center, where he has led interdisciplinary projects integrating IoT, automation, and renewable energy systems.

Research Interests 

His research focuses on power electronics, multilevel inverter design, power quality enhancement, electric vehicle charging infrastructure, smart grid systems, and IoT-enabled automation. He also works extensively on agricultural automation, including polyhouse automation, speed breeding chambers, and plant phenotyping systems. Emerging interests include machine learning applications for plant disease detection, robotics, and smart farming technologies.

Awards and Honors 

Dr. Dash has received multiple accolades, including the Distinguished Achiever Award at the Provost Research Awards and recognition as a session chair at IEEE international conferences. He is the founder of a technology-driven startup and actively engages in professional communities such as the IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE SIGHT.

Research Skills 

He possesses strong expertise in the design, modeling, and implementation of cascaded multilevel inverters, power quality control algorithms, and renewable energy integration. His skills extend to IoT-based system design, automation technologies, electric vehicle charging systems, and cloud-based agricultural monitoring. He is also an experienced reviewer for several high-impact international journals in power electronics and smart grid applications.

Publications 

A unified control of grid-interactive off-board EV battery charger with improved power quality

Citations: 49

Year: 2022

Reactive power compensation using vehicle-to-grid enabled bidirectional off-board EV battery charger

Citations: 34

Year: 2021

Adaptive LMBP training‐based icosϕ control technique for DSTATCOM

Citations: 33

Year: 2020

Analysis of PI and PR controllers for distributed power generation system under unbalanced grid faults

Citations: 33

Year: 2011

Design and implementation of a cascaded transformer coupled multilevel inverter‐based shunt active filter under different grid voltage conditions

Citations: 24

Year: 2019

Conclusion 

Dr. Ashish Ranjan Dash is a forward-looking researcher and educator whose work bridges advanced power electronics with practical applications in smart infrastructure and agricultural automation. His multidisciplinary expertise, leadership in funded projects, and dedication to mentoring the next generation of engineers make him a valuable contributor to both academia and industry. His continued research promises innovative advancements in electric mobility, renewable energy integration, and intelligent automation systems.

Mutiu Shola | Electrical Engineering | Best Researcher Award

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Dr. Mutiu Shola | Electrical Engineering | Best Researcher Award

Kampala International University, Uganda

Dr. Bakare Mutiu Shola is a dedicated academic and researcher in the field of Electrical and Electronics Engineering. He holds a Ph.D. from Kampala International University, Uganda, an M.Eng. from the University of Ilorin, Nigeria, and a B.Eng. from the Federal University of Technology, Minna. His expertise spans renewable energy, smart grids, load forecasting, high-voltage technology, artificial intelligence, and power systems. With a rich background in both industry and academia, Dr. Bakare has contributed significantly through high-impact research publications in top-tier journals and active teaching roles in higher institutions.

Publication Profile 

Scopus

Orcid

Educational Background 🎓

  • Ph.D. in Electrical and Electronics Engineering
    Kampala International University, Uganda (2022 – 2025)

  • Master of Engineering (M.Eng.) in Electrical and Electronics Engineering
    University of Ilorin, Nigeria (2017 – 2021)

  • Bachelor of Engineering (B.Eng.) in Electrical and Computer Engineering
    Federal University of Technology, Minna, Nigeria (2008 – 2014)
    Graduated with Second Class Upper Division

Professional Experience 💼

  • Assistant Lecturer
    Department of Electrical and Electronics Engineering, Kampala International University, Uganda
    (2022 – Present)
    Courses taught include Power Electronics, Power Quality Management, Circuit Theory, and Electrical Installation & Maintenance.

  • Research Assistant
    Advanced Power and Green Energy Research Group (APGER), University of Ilorin, Nigeria
    (2019 – 2022)

  • Physics & Mathematics Tutor
    Government Day Secondary School, Nigeria
    (2018 – 2019)

  • Site Engineer
    Thamar Engineering Company Ltd, Nigeria
    (2015 – 2018)
    Responsibilities included transformer installation, lighting, and generator setup.

Research Interests 🔬

  • Renewable Energy Systems

  • Energy Management

  • Load Forecasting

  • Smart Grid Technologies

  • Electrical Power System Optimization

  • Artificial Intelligence Applications in Power Systems

Awards and Honors🏆✨

  • Multiple Q1 and Q2-ranked journal publications in high-impact engineering journals such as Scientific Reports, Results in Engineering, Energy Reports, and Energy Conversion and Management: X.

  • Active participation in IEEE academic workshops and international conferences such as ICASSP 2020.

Conclusion🌟

Dr. Bakare Mutiu Shola is a rising scholar in electrical engineering with a strong background in both practical engineering and academic research. His consistent record of publications, academic service, and technical expertise in emerging power systems reflects his commitment to driving innovation in sustainable and intelligent energy solutions. With a future-focused mindset, Dr. Bakare is poised to make continued contributions to both academia and the global energy sector.

Publications 📚

  • 🧠 Comparative Evaluation of Different Fuzzy Tuning Rules on Energy Management Systems Cost Savings
    Ibrahim, O., Bakare, M. S., et al.
    📝 Results in Engineering (2025) – Q1 Journal

  • ☀️ Revolutionizing Solar Power: Enhancing Solar Power Efficiency with Hybrid GEP-ANFIS MPPT under Dynamic Weather Conditions
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Manas Ranjan Sethi | ECE | Best Researcher Award

Published on by Innovation Technologist

Mr. Manas Ranjan Sethi | ECE | Best Researcher Award

Research Scholar at NIT Silchar, India

Manas Ranjan Sethi is a dedicated academic professional currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar, with a strong focus on machine learning applications in fault diagnosis and energy systems. He holds an M.Tech in Electronics & Telecommunication from BPUT, Odisha and has over 12 years of teaching experience, having worked as an Assistant Professor at Gandhi Institute for Technology (GIFT) and as a Lecturer at Koustuv Institute of Self Domain, Bhubaneswar. His research interests include machine learning, signal processing, and sustainable energy systems, particularly in wind turbine diagnostics and emotion recognition using EEG signals. Manas has contributed to numerous journals, conferences, and book chapters, and he has earned distinctions such as qualifying CBSE-UGC NET and GATE. He is also skilled in technical tools, enjoys singing, and has a passion for reading.

Publication Profile : 

Scopus

 

🎓 Educational Background :

Manas Ranjan Sethi is currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar (since March 2020). He holds an M.Tech in Electronics & Telecommunication (Specialization in Communication Engineering) from BPUT, Odisha (2012), with a CGPA of 8.20. He completed his B.E. in Electronics & Telecommunication from BPUT, Odisha, in 2006, securing a 62.19%. Additionally, he completed his +2 Science and Matriculation from MP Board, Madhya Pradesh.

💼 Professional Experience :

Manas has a rich academic career spanning over 12 years. He served as an Assistant Professor in the Electronics & Communication Engineering Department at Gandhi Institute for Technology (GIFT), Bhubaneswar, from November 2013 to March 2020. Prior to that, he worked as a Lecturer in the Electronics & Telecommunication Engineering Department at Koustuv Institute of Self Domain, Bhubaneswar, from July 2007 to November 2013. He has a strong foundation in teaching and mentoring students in the field of Electronics and Communication Engineering.

📚 Research Interests : 

Manas’s research interests lie in the domains of Machine Learning, Signal Processing, and Fault Diagnosis. His work focuses on vibration signal-based diagnostics and energy extraction using wind turbines. He is passionate about leveraging machine learning techniques for predictive maintenance and condition monitoring. His recent research includes the application of meta-classifiers for diagnosing wind turbine blade faults and exploring emotion recognition through EEG signals.

🏆Achievements & Certifications :

Manas has earned several academic distinctions, including qualifying the CBSE-UGC NET (Electronic Science) in July 2018, and securing GATE scores of 260 (2016) and 218 (2011) in Electronics and Communication. He has also attended and contributed to various seminars, workshops, and short-term courses in fields such as VLSI Design, Microwave Filters, and Adaptive Signal Processing.

📝 Publication Top Notes :

  • Sethi, M. R., Subba, A. B., Faisal, M., Sahoo, S., & Koteswara Raju, D. (2024). Fault diagnosis of wind turbine blades with continuous wavelet transform based deep learning model using vibration signal. Engineering Applications of Artificial Intelligence, 138, 109372.
  • Sethi, M. R., Sahoo, S., Dhanraj, J. A., & Sugumaran, V. (2023). Vibration Signal-Based Diagnosis of Wind Turbine Blade Conditions for Improving Energy Extraction Using Machine Learning Approach. Smart and Sustainable Manufacturing Systems, 7(1), 14–40.
  • Chatterjee, S., Sethi, M. R., & Asad, M. W. A. (2016). Production phase and ultimate pit limit design under commodity price uncertainty. European Journal of Operational Research, 248(2), 658–667.
  • Sethi, M. R., Parhi, S. S., Sahoo, S., Sugumaran, V., & Mohanty, S. R. (2023). Fault Diagnosis of Wind Turbine Blades Through Vibration Signal Using Filtered Cultivation Data: A Comparative Study. Proceedings of the 2023 IEEE Region 10 Symposium, TENSYMP 2023.
  • Kar, P., Hazarika, J., & Sethi, M. R. (2023). A Comparative Study between Supervised and Unsupervised Techniques for Two Class Emotion Recognition using EEG. Proceedings of the 2023 IEEE 8th International Conference for Convergence in Technology, I2CT 2023.
  • Banala, H. S., Sahoo, S., Sethi, M. R., & Sharma, A. K. (2023). Fault Diagnosis in Wind Turbine Blades Using Machine Learning Techniques. In R. Doriya, B. Soni, A. Shukla, & X. Z. Gao (Eds.), Machine Learning, Image Processing, Network Security and Data Sciences (Lecture Notes in Electrical Engineering, Vol. 946), 401–411. Springer, Singapore.
  • Sethi, M. R., Sahoo, S., Kanoongo, S., & Hemasudheer, B. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Rule Classifier. Proceedings of the 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET 2022), 1–6. doi: 10.1109/ICEFEET51821.2022.9848401.
  • Sethi, M. R., Hemasudheer, B., Sahoo, S., & Kanoongo, S. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Vibration Data through META Classifiers. Proceedings of the 2022 4th International Conference on Energy, Power, and Environment (ICEPE 2022), 1–5. doi: 10.1109/ICEPE55035.2022.9798026.