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.

Ming Chen | Engineering | Research Excellence Award

Published on by Innovation Technologist

Dr. Ming Chen | Engineering | Research Excellence Award 

Lecturer at  Zhejiang Ocean University | China

Dr. Ming Chen is a researcher in composite structures, uncertainty quantification, and data-driven intelligent design, with a strong focus on underwater composite cylindrical shells. His work integrates numerical simulation, polynomial chaos expansion, Bayesian deep learning, symbolic regression, and automated machine learning for structural analysis, reliability assessment, and design optimization under uncertainty. He has published in leading journals including Mechanics of Advanced Materials and Structures and Journal of Marine Science and Engineering. According to Scopus, Dr. Ming Chen has 6 publications, 18 citations, and an h-index of 2. His research contributes to probabilistic machine learning frameworks, global sensitivity analysis, and digital-twin multi-fidelity modeling for advanced composite systems.

                            Citation Metrics (Scopus)

30

25

20

15

10

5

0

 

Citations
18
Documents
6
h-index
2

Citations

Documents

h-index

View Scopus Profile  View ORCID Profile

Featured Publications

Pascal Vrignat | Industry 4.0 | Research Excellence Award

Published on by Innovation Technologist

Dr. Pascal Vrignat | Industry 4.0 | Research Excellence Award

Prisme Laboratory at Orleans University | France

Pascal Vrignat is a researcher specializing in operational safety, diagnostics, prognostics, and maintenance strategies for complex systems, with particular expertise in Markovian and stochastic models. His work significantly advances methods for estimating system degradation using survival laws, hidden Markov models, and Remaining Useful Life approaches. He contributes to understanding system obsolescence and managing shortages across the life cycle of industrial systems. His research bridges theory and industrial application, encompassing industrial computing, advanced process control, human–machine interfaces, SCADA systems, IoT, M2M technologies, and digital communication protocols, including OPC-based architectures. He has an extensive record of scientific output, including journal publications, conference papers, book chapters, and a widely used textbook on industrial local networks. His recent works address bearing degradation monitoring and the role of AI in sustainability-focused applications. He is active in research project development, editorial responsibilities, and academic leadership within his institution and research laboratory. His contributions to industry-oriented R&D have earned recognition in international automation competitions. His scholarly impact is reflected in 618 citations (405 since 2020), an h-index of 10 (7 since 2020), and an i10-index of 13 (6 since 2020), underscoring his sustained influence in the fields of reliability engineering, automation, predictive maintenance, and digital industrial systems.

Profiles: Orcid | Google Scholar

Featured Publications

Vrignat, P., Kratz, F., & Avila, M. (2022). Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review. Reliability Engineering & System Safety, 218, 108140. https://doi.org/10.1016/j.ress.2021.108140
Cited by: 152

Pascal, V., Toufik, A., Manuel, A., Florent, D., & Kratz, F. (2019). Improvement indicators for total productive maintenance policy. Control Engineering Practice, 82, 86–96. https://doi.org/10.1016/j.conengprac.2018.09.019
Cited by: 81

Vrignat, P., Avila, M., Duculty, F., & Kratz, F. (2015). Failure event prediction using hidden Markov model approaches. IEEE Transactions on Reliability, 64(3), 1038–1048. https://doi.org/10.1109/TR.2015.2426458
Cited by: 49

Aggab, T., Avila, M., Vrignat, P., & Kratz, F. (2021). Unifying model-based prognosis with learning-based time-series prediction methods: Application to Li-ion battery. IEEE Systems Journal, 15(4), 5245–5254. https://doi.org/10.1109/JSYST.2021.3080125
Cited by: 32

Vrignat, P., Avila, M., Duculty, F., Aupetit, S., Slimane, M., & Kratz, F. (2012). Maintenance policy: Degradation laws versus Hidden Markov Model availability indicator. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 226(2), 137–155. https://doi.org/10.1177/1748006X11406335
Cited by: 21

 

Shyamal Acharya | Engineering | Research Excellence Award

Published on by Innovation Technologist

Mr. Shyamal Acharya | Engineering | Research Excellence Award

Assistant Professor | Chittagong University of Engineering & Technology (CUET) | Bangladesh

Mr. Shyamal Acharya is an accomplished researcher and academic in Civil Engineering with a strong specialization in Water Resources Engineering, combining teaching excellence with applied research and consultancy experience. His scholarly work focuses on sustainable water management, hydrologic alteration, reservoir sedimentation, flood risk assessment, and performance evaluation of urban water supply systems, with particular relevance to the socio-economic and environmental context of Bangladesh. He has contributed peer-reviewed research published by internationally recognized publishers, addressing critical issues such as the impacts of hydraulic infrastructure on river systems and efficiency assessment of public water utilities. His research methodology integrates remote sensing, hydrological modeling, risk assessment frameworks, and institutional performance indicators to support evidence-based policy and engineering decisions. Alongside academic research, he has extensive professional experience in high-impact consultancy projects, including feasibility studies and structural design of port infrastructure, tourism development initiatives, dam stability assessments, and industrial water-related engineering solutions. His involvement in reservoir irrigation feasibility and flood mitigation studies reflects a strong commitment to climate resilience, food security, and sustainable infrastructure development. As an educator and mentor, he actively contributes to capacity building in water resources engineering and civil engineering practice. He is a Life Fellow of a national professional engineering body and maintains strong links with professional and development institutions, enabling effective knowledge transfer between academia, industry, and policy stakeholders. His profile demonstrates sustained contributions to research excellence, practical engineering impact, and national development priorities in water and environmental engineering.

Profile: Scopus

Featured Publications

Acharya, S. (2025). Performance assessment of a public water supply provider in Bangladesh. Urban Water Journal.

Gul Durak | Engineering | Best Research Article Award

Published on by Innovation Technologist

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.

Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

Published on by Innovation Technologist

Mr. Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

State University of Campinas | Brazil

Mr. Salomon Dominique Edimo Kingue is a reservoir engineer and researcher specializing in enhanced oil recovery (EOR), reservoir simulation, and sustainable subsurface energy strategies. His expertise centers on FAWAG/WAG processes, CO₂ storage modeling, and integrated reservoir–production optimization for complex carbonate systems, particularly within Brazilian pre-salt environments. He is highly skilled in using CMG (IMEX, STARS, GEM, CMOST), Petrel, Python, and advanced analytical tools to investigate flow behavior, improve recovery efficiency, and reduce greenhouse gas emissions. His research spans numerical simulation of EOR mechanisms, uncertainty analysis, carbon capture and storage (CCS), fractured-vuggy reservoir upscaling, and evaluation of production potential in hydrocarbon basins. He has co-authored studies on underground LPG storage and reservoir performance prediction, and contributed to interdisciplinary projects involving major industry partners. His work also extends to geological interpretation, multidisciplinary collaboration, and scientific communication through symposiums, poster sessions, and peer-reviewed publications. Salomon combines strong analytical reasoning with leadership, teamwork, and effective communication, reflecting his commitment to innovation-driven reservoir management and the advancement of low-carbon energy solutions.

Profile: Orcid

Featured Publications

Kingue, S. D. E., Akinmuda, O. B., Kuiekem, D., & Djitchouang, G. L. (2025). Assessing the production potential of Niger Delta reservoirs under uncertainty using numerical simulation tools. Petroleum Science and Technology.

Kuiekem, D., Kingue, S. D. E., Boroh, W., Noupa, R. K., Matateyou, J., & Ngounouno, I. (2025). Simulation study of underground LPG storage in a depleted conceptual oil reservoir. Petro Chem Indus Intern, 8(2), 1–14.

Zhiqi Wu | Engineering | Best Researcher Award

Published on by Innovation Technologist

Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.