Tieliang Zeng | Electrical Engineering | Excellence in Researcher Award

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Mr. Tieliang Zeng | Electrical Engineering | Excellence in Researcher Award

Master’s Degree Candidate at The Electrical Engineering College, Guizhou University, China

Tieliang Zeng, a passionate and emerging researcher, is currently pursuing his master’s degree at the Electrical Engineering College, Guizhou University. With a sharp focus on power electronics, his specialization lies in parameter identification of power electronic converters using digital twin technology 🔧🧠. As part of his academic journey, he has contributed to the Guizhou Provincial Key Technology R&D Program ([2024] General 049) and has successfully published one SCI-indexed paper in an MDPI journal 📄. Though early in his career, Tieliang’s commitment to innovation and technical precision is evident through his focused academic work. His field of study is essential to developing smarter, more efficient power systems 🌐⚡. As a budding scholar with a futuristic vision, he aims to expand his research through collaboration, scientific rigor, and practical application. Zeng is certainly a name to watch in the rapidly evolving domain of intelligent electrical systems and digital modeling technologies. 🚀🔬

Professional Profile

ORCID Profile

🎓 Education 

Tieliang Zeng embarked on his higher education journey with an enduring curiosity for electrical systems and smart technologies ⚡📘. He is currently a master’s degree candidate at the Electrical Engineering College of Guizhou University, one of China’s respected institutions in engineering education. His academic path has been defined by a commitment to technical depth and an interest in bridging physical systems with digital simulations through digital twin frameworks 🖥️🔄. With courses covering power electronics, control systems, and system modeling, Tieliang has built a solid theoretical and practical base to support his research. His continuous engagement with both classroom knowledge and real-world problems reflects his drive to excel academically 🎯📚. He is particularly focused on mastering advanced tools and methods for parameter identification in complex converter systems, which forms the foundation of his graduate thesis and current research endeavors. Tieliang’s academic foundation is both robust and forward-thinking. 🧠🧮

💼 Professional Experience 

As a young professional rooted in academia, Tieliang Zeng has initiated his professional journey through research-intensive roles and scholarly projects 🧑‍🔬🔌. His main involvement lies with the Guizhou Provincial Key Technology R&D Program, where he contributes to solving real-world challenges in power electronics through modeling and parameter extraction techniques 📊🔍. Although he has not yet ventured into large-scale consultancy or industrial projects, his participation in a government-funded initiative is a strong testament to his applied research capabilities. Tieliang’s work often involves digital simulations, hardware experimentation, and analytical evaluations – skills that mirror the evolving demands of modern electrical engineering 🌐🔋. Despite being early in his career, his focused technical contributions and publishing experience underscore his potential to make meaningful impacts in both academic and industrial settings in the near future. He’s actively shaping himself as a future innovator in digital twin-based power systems. 🛠️📈

🔬 Research Interests 

Tieliang Zeng’s research compass is firmly directed toward parameter identification in power electronic converters, a core challenge in creating accurate digital twin models 🔄⚡. His exploration dives deep into understanding the dynamic behavior of power systems and how virtual replicas can be developed to monitor, simulate, and control them in real time 🌍🧪. This specialized interest enables improved performance, predictive maintenance, and enhanced design processes in modern electrical infrastructure. His methodology often blends simulation tools, mathematical modeling, and real-world data analysis to ensure accuracy and adaptability 🧠📐. With the energy sector moving rapidly toward smart and autonomous systems, Tieliang’s work is aligned with the global shift toward digitalization and sustainability 🔋🌱. He is eager to refine these models further, enabling high-efficiency and fault-tolerant systems. By focusing his research within this transformative domain, he contributes to the foundational knowledge necessary for tomorrow’s power solutions. 🧬📡

🏆 Awards and Honors 

While Tieliang Zeng has not formally listed any academic awards or honors as of now, his inclusion in a key provincial R&D project and the successful publication of an SCI-indexed paper reflect a merit-based recognition of his talent and research abilities 🧾🏅. Being part of a selective and competitive government-funded research program is in itself an acknowledgment of his capabilities as a skilled researcher 🎯🎓. These achievements at an early stage signal his potential to receive future distinctions as his academic and professional journey unfolds. His scholarly persistence and contribution to innovative topics like digital twins in power systems are laying the groundwork for academic excellence and institutional accolades. With such a trajectory, awards and honors seem to be only a matter of time. His current achievements already reflect a commendable level of discipline, originality, and technical maturity 🌟📘.

Publications Top Notes

  • Title: Digital Twin-Based Multi-Parameter Coordinated Identification Method for Three-Phase Four-Leg Converter

  • Authors: Tieliang Zeng, et al.

  • Journal: Electronics

  • Year: 2025

  • DOI: 10.3390/electronics14102002

  • ISSN: 2079-9292

  • Source: MDPI – Electronics Journal

Conclusion 

In conclusion, Tieliang Zeng stands as a dedicated and promising figure in the field of electrical engineering, particularly in the niche domain of digital twin-based parameter identification for power converters 🔌🧠. As a master’s student with strong research orientation, he is already contributing to meaningful scientific discourse through government-supported projects and peer-reviewed publications 📚💡. Although at the early stages of his career, his focused efforts, analytical mindset, and technical competence set a solid foundation for impactful research and future innovation. Tieliang’s ambitions clearly resonate with the global move toward smart grid solutions and digital infrastructure, positioning him as a valuable asset to both academia and industry 🌍🔬. His journey reflects the beginning of a career with significant potential, where theory and practical application merge to solve complex power challenges. With continued dedication and collaboration, Tieliang Zeng is poised to advance the next wave of digital electrical technologies. 🚀🔧

Ehsan Adibnia | Engineering | Best Academic Researcher Award

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Dr. Ehsan Adibnia | Engineering | Best Academic Researcher Award

Dr. Ehsan Adibnia at University of Sistan and Baluchestan, Iran

Dr. Ehsan Adibnia 🎓 is a dedicated academic researcher in electrical engineering ⚡, specializing in cutting-edge fields such as artificial intelligence 🤖, machine learning 📊, deep learning 🧠, nanophotonics 💡, optics 🔬, and plasmonics ✨. He is proficient in Python 🐍, MATLAB 🧮, and Visual Basic, and utilizes simulation tools like Lumerical 📈, COMSOL 🧪, and RSoft 🔧 to drive innovative research. Fluent in English 🇬🇧 and Persian 🇮🇷, Dr. Adibnia contributes to academic conferences and peer-reviewed journals 📚. He is currently pursuing his Ph.D. and actively engaged in interdisciplinary scientific exploration 🌐.

Professional Profile:

Orcid

Scopus

Google Scholar

🔹 Education & Experience 

🎓 Ph.D. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (Expected 2025)
🎓 B.S. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (2014)
🧑‍💼 Executive Committee Member – 27th Iranian Conference on Optics and Photonics & 13th Conference on Photonic Engineering and Technology
🖋️ Assistant Editor – International Journal (Name not specified)
🔍 Researcher – Actively engaged in interdisciplinary AI & photonics research projects

🔹 Professional Development 

Dr. Ehsan Adibnia continually enhances his professional growth through active participation in conferences 🧑‍🏫, committee leadership 🗂️, and editorial work 📑. He develops algorithms and conducts simulations using advanced tools such as Lumerical 🔬, COMSOL 🧪, and RSoft 💻. His expertise in AI and photonics drives innovative research and collaboration 🌍. He also hones his programming skills in MATLAB 🧮, Python 🐍, and VBA 🧠, ensuring precision in modeling and data analysis. His hands-on knowledge in PLC systems 🤖 and industrial automation makes him versatile across both academic and applied research settings 🏭.

🔹 Research Focus 

Dr. Adibnia’s research focuses on the fusion of artificial intelligence 🤖 and photonics 💡. His work explores machine learning 📊, deep learning 🧠, nanophotonics 🔬, plasmonics ✨, optical switching 🔁, and slow light 🐢 technologies. He is particularly interested in leveraging these technologies in biosensors 🧫, metamaterials 🔷, and quantum optics ⚛️. Through simulation and algorithm development, he aims to optimize performance in optoelectronic and photonic systems 🔍. His interdisciplinary research bridges electrical engineering with physics and AI, creating advanced systems for diagnostics, sensing, and smart environments 🌐.

🔹 Awards & Honors 

🏅 Executive Committee Role – 27th Iranian Conference on Optics and Photonics
🏅 Executive Committee Role – 13th Iranian Conference on Photonic Engineering and Technology
📜 Assistant Editor – International scientific journal (name not specified)
🧠 Scopus-indexed Researcher – Scopus ID: 58485414000

Publication Top Notes

🔹 High-performance and compact photonic crystal channel drop filter using P-shaped ring resonator

  • Journal: Results in Optics

  • Date: Dec 2025

  • DOI: 10.1016/j.rio.2025.100817

  • Summary: Proposes a novel P-shaped ring resonator design for channel drop filters in photonic crystal structures. Focuses on achieving high performance in terms of compactness and spectral selectivity for integrated optical circuits.

🔹 Optimizing Few-Mode Erbium-Doped Fiber Amplifiers for high-capacity optical networks using a multi-objective optimization algorithm

  • Journal: Optical Fiber Technology

  • Date: Sep 2025

  • DOI: 10.1016/j.yofte.2025.104186

  • Summary: Introduces a multi-objective optimization approach for designing few-mode EDFAs, targeting performance improvements in next-gen high-capacity optical networks.

🔹 Inverse design of octagonal plasmonic structure for switching using deep learning

  • Journal: Results in Physics

  • Date: Apr 2025

  • DOI: 10.1016/j.rinp.2025.108197

  • Summary: Utilizes deep learning for the inverse design of an octagonal plasmonic structure used in optical switching, demonstrating enhanced precision and compact design capability.

🔹 Chirped apodized fiber Bragg gratings inverse design via deep learning

  • Journal: Optics & Laser Technology

  • Date: 2025

  • DOI: 10.1016/J.OPTLASTEC.2024.111766

  • WOS UID: WOS:001311493000001

  • Summary: Applies deep learning to the inverse design of chirped apodized fiber Bragg gratings, optimizing the spectral characteristics for filtering and sensing applications.

🔹 Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach

  • Journal: Journal of Lightwave Technology

  • Date: 2025

  • DOI: 10.1109/JLT.2025.3534275

  • Summary: Proposes a hybrid CNN-MLP architecture to design fiber Bragg grating (FBG) optical filters, improving accuracy and speed in the inverse design process using deep learning techniques.

Conclusion

Dr. Adibnia is still in the process of completing his Ph.D., his broad technical expertise, multidisciplinary research focus, early academic leadership roles, and active participation in both national and international platforms make him a highly promising candidate for the Best Academic Researcher Award in the early-career researcher or emerging researcher category.

Shakil Ahmed | Engineering | Best Researcher Award

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Prof. Shakil Ahmed | Engineering | Best Researcher Award

Assistant Processor, Term at Iowa State University, United States

Shakil Ahmed is an Assistant Teaching Professor in Computer Engineering at Iowa State University (ISU), specializing in AI/ML, cybersecurity, IoT, cloud computing, and advanced networking. With a Ph.D. in Computer Engineering from ISU (2023) and over 2,000 citations across 35+ publications, he leads cutting-edge research on AI-driven solutions, digital twins, and quantum networks. As a principal investigator (PI), he mentors undergraduate, MS, and Ph.D. students while actively securing external grants. His expertise spans reinforcement learning, large language models, explainable AI, and meta-learning, contributing to pioneering advancements in next-gen networking and intelligent systems. 🚀🔍

Professional Profile

Education & Experience 📚👨‍🏫

  • Ph.D. in Computer Engineering – Iowa State University (2023) 🎓
  • M.S. in Electrical Engineering – Utah State University (2019) ⚡
  • B.S. in Electrical and Electronic Engineering – Khulna University of Engineering & Technology, Bangladesh (2014) 🏅
  • Assistant Teaching Professor – Iowa State University (2024–Present) 🎓
  • Researcher & PI – Leading projects on AI, 6G, cybersecurity, IoT, and digital twins 🔬
  • Advisor & Mentor – Supervising undergraduate, MS, and Ph.D. students in advanced networking and AI 🧑‍🎓

Professional Development 📈🧠

Shakil Ahmed actively contributes to AI-driven networking, secure systems, and IoT advancements. He plays a vital role in research funding, securing grants exceeding millions of dollars. As a guest editor at MDPI and reviewer for 150+ articles, he ensures high research standards. His teaching experience spans multiple STEM courses, where he integrates hands-on learning tools like Zybooks and Canvas. He has delivered invited talks on next-gen wireless technologies and collaborates with multidisciplinary teams to shape the future of AI, cloud computing, and quantum networking. His work has significantly impacted academia, research, and industry. 🚀🔬📡

Research Focus 🏆🔍

Shakil Ahmed’s research is at the intersection of AI, networking, and cybersecurity, with a focus on:

  • AI/ML & Deep Learning – Reinforcement Learning (RL), Large Language Models (LLM), Explainable AI (XAI) 🤖
  • Cybersecurity & Quantum Networking – Secure network protocols, quantum neural networks (QNN) 🔒
  • IoT & Cloud Computing – System design for connected environments, mobile edge computing ☁️
  • Digital Twin & 6G+ Networks – AI-driven tactile internet, smart infrastructure, and futuristic networking 🌍📡
    His work integrates cutting-edge AI techniques, optimization frameworks, and network simulations to solve real-world challenges.

Awards & Honors 🏅🎖️

  • Professional Development Fund – Iowa State University ($10,000) 💰
  • Presidential Fellowship – Utah State University ($90,000) 🏆
  • Best Paper Award – IEEE International Conference on Informatics, Electronics, and Vision (2016) 🥇
  • Graduate & Professional Student Senate Research Award – ISU ($700) 📜
  • ECpE Department Support Grant – ISU ($600) 🎓
  • Professional Advancement Grant (PAG) – ISU ($400) 🎖️
  • Military Communications Conference Student Travel Grants – 2021 & 2022 ($1,000) ✈️
  • Graduate & Professional Student Council Grant – ISU ($750) 🏅
  • ECE Department Support Grant – Utah State University ($1,000) 🏆

Publication Top Notes

  1. 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions

    • Authors: Mostafa Zaman Chowdhury, Md. Shahjalal, Shakil Ahmed, Yeong Min Jang
    • Journal: IEEE Open Journal of the Communications Society
    • Year: 2020
    • Citation: Chowdhury, M. Z., Shahjalal, M., Ahmed, S., & Jang, Y. M. (2020). 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions. IEEE Open Journal of the Communications Society, 1, 957–975.

  2. Energy-Efficient UAV-to-User Scheduling to Maximize Throughput in Wireless Networks

    • Authors: Shakil Ahmed, Mostafa Zaman Chowdhury, Yeong Min Jang
    • Journal: IEEE Access
    • Year: 2020
    • Citation: Ahmed, S., Chowdhury, M. Z., & Jang, Y. M. (2020). Energy-Efficient UAV-to-User Scheduling to Maximize Throughput in Wireless Networks. IEEE Access, 8, 21215–21225.

  3. Energy-Efficient UAV Relaying Communications to Serve Ground Nodes

    • Authors: Shakil Ahmed, Mostafa Zaman Chowdhury, Yeong Min Jang
    • Journal: IEEE Communications Letters
    • Year: 2020
    • Citation: Ahmed, S., Chowdhury, M. Z., & Jang, Y. M. (2020). Energy-Efficient UAV Relaying Communications to Serve Ground Nodes. IEEE Communications Letters, 24(4), 849–852.

  4. Non-Orthogonal Multiple Access in a mmWave Based IoT Wireless System with SWIPT

    • Authors: Hao Sun, Qiang Wang, Shakil Ahmed, Rose Hu
    • Conference: IEEE Vehicular Technology Conference (VTC Spring)
    • Year: 2017
    • Citation: Sun, H., Wang, Q., Ahmed, S., & Hu, R. (2017). Non-Orthogonal Multiple Access in a mmWave Based IoT Wireless System with SWIPT. In 2017 IEEE 85th Vehicular Technology Conference (VTC Spring) (pp. 1–5).

  5. A Disaster Response Framework Based on IoT and D2D Communication Under 5G Network Technology

    • Authors: Shakil Ahmed, Md Rashid, Farzana Alam, B. Fakhruddin
    • Conference: 2019 29th International Telecommunication Networks and Applications Conference (ITNAC)
    • Year: 2019
    • Citation: Ahmed, S., Rashid, M., Alam, F., & Fakhruddin, B. (2019). A Disaster Response Framework Based on IoT and D2D Communication Under 5G Network Technology. In 2019 29th International Telecommunication Networks and Applications Conference (ITNAC) (pp. 20–25).

 

Shengnan Zhang | Engineering | Best Researcher Award

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Dr. Shengnan Zhang | Engineering | Best Researcher Award

None  at School of Mechatronic Engineering and Automation, Shanghai University

Short Bio

  • shengnan zhang is a Ph.D. researcher at Shanghai University specializing in electromagnetic flowmeters, signal processing, and mathematical modeling for industrial processes. With experience in engineering and automation, she integrates theoretical and applied research to enhance industrial measurement accuracy and efficiency.

Professional Profile

Educational Background

  • shengnan zhang is currently pursuing a Ph.D. in the School of Mechatronic Engineering and Automation at Shanghai University (2021–2024). She earned her master’s degree in Control Science and Engineering (Automation) from Inner Mongolia University of Science and Technology in 2020.

Professional Experience

  • shengnan zhang has gained diverse experience in both industry and academia. She worked as a junior engineer in the Mechanical and Electrical Department at State Grid Xinyuan Chifeng Company, Inner Mongolia (2020–2021). She later transitioned into roles as a Hardware R&D Engineer at JiDan Biotechnology Co., Ltd. and a High School Mathematics Teacher at Nanjing Yunjushi Education Co., Ltd. in 2021.

Research Interests

    • Her research focuses on electromagnetic flowmeters, signal processing, and mathematical modeling of complex industrial processes. She is particularly interested in developing advanced computational techniques for industrial automation and measurement systems.

Author Metrics

  • Currently, shengnan zhang is actively engaged in research and has contributed to scholarly publications in her field. Her work includes studies on signal processing applications in industrial automation and measurement technologies.

Publication Top Noted

  • Study on the Match-Filtering Ability of the Electromagnetic Flowmeter Signals Based on the Generalized Dual-Frequency Walsh Transform
    Flow Measurement and Instrumentation, March 2025
    DOI: 10.1016/j.flowmeasinst.2024.102767
  • Generalized Walsh Transform Sequency-Domain-Based Match Filtering for Electromagnetic Flowmeter Signal Measurement
    IEEE Sensors Journal, April 2024
    DOI: 10.1109/JSEN.2024.3366238
  • A Sequency Match Filtering Algorithm Based on the Generalized Walsh Transform for Processing Rectangular Wave Signals
    Review of Scientific Instruments, February 2024
    DOI: 10.1063/5.0175079
  • Study on Match Filtering Based on Sequency Spectrum Characteristics of the Walsh Transform for Electromagnetic Flowmeter Signal Measurement
    Measurement, February 2024
    DOI: 10.1016/j.measurement.2023.114021

Conclusion

  • Dr. shengnan zhang is a highly qualified researcher with notable contributions to signal processing and industrial measurement systems. Her innovative approaches using Generalized Walsh Transform have the potential to improve electromagnetic flowmeter accuracy significantly. With further collaboration, higher citation impact, and real-world application of her research, she would be an excellent candidate for the Best Researcher Award.

Thi Hong Nhung Vu | Engineering | Best Researcher Award

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Dr. Thi Hong Nhung Vu | Engineering | Best Researcher Award 

Dr. Thi Hong Nhung V,  Vietnam National University of Forestry at Dong Nai, Vietnam

Dr. thi hong nhung v is a dedicated researcher and educator with nearly two decades of experience in teaching and research. Her studies have spanned multiple disciplines, focusing on the development of nanofibrous materials and composite biomaterials for medical and ecological applications. Her contributions include enhancing the fabrication and efficiency of PVA and PVA-chitosan nanofibers, with practical applications in drug delivery systems. An active participant in the academic community, she has attended numerous international conferences and has a strong publication record in high-impact journals. Dr. thi hong nhung v continues to innovate in the fields of nano biomaterials and bioengineering, driving advancements in both academia and applied sciences.

PROFILE

Orcid  Profile

Educational Detail

Dr. thi hong nhung v holds advanced degrees in fields related to biopolymers, nanomaterials, and bioengineering. She pursued her studies both in Vietnam and the Russian Federation. In Vietnam, she specialized in natural component extraction, while in the Russian Federation, her focus shifted to the development of nanofibrous materials for drug integration. Her education was complemented by projects involving artificial intelligence, optotechnics, bioengineering, and composite biomaterials.

Professional Experience

Dr. thi hong nhung v has 19 years of experience as a secondary school teacher and university lecturer in Vietnam. She has participated in and contributed to three significant research projects:

Artificial intelligence methods for cyber-physical systems.

Development of methods and tools for applied problems in optotechnics and bioengineering.

Composite biomaterials and technologies for ecophotonics and medicine.

Over the past five years, she has attended 12 international scientific conferences and published nine research articles in reputable journals indexed in SCI and Scopus. She has also contributed to book publications, with one carrying the ISBN 978-3-031-26907-3.

Research Interests

Dr. thi hong nhung v’s research interests include:

Biopolymers and polymers

Nano biomaterials and electrospinning

Nano biochemistry and nanomaterials

Her work focuses on developing and improving PVA and PVA-chitosan nanofibers, emphasizing solution composition, technological parameters, and the use of multicomponent solvent systems to enhance material properties and drug incorporation efficiency.

Top Notable Publications

thi hong nhung v, Study on Fabrication and Properties of Polyvinyl Alcohol/Chitosan Nanofibers Created from Aqueous Solution with Acetic Acid and Ethanol by the Electrospinning Method. Polymers, 2024, 16(23), 3393. DOI: 10.3390/polym16233393.

thi hong nhung v, Study on Fabrication and Properties of Polyvinyl Alcohol—Chitosan Nanofibers from Aqueous Solution with Acetic Acid and Ethanol by Electrospinning Method. Preprint, 2024. DOI: 10.20944/preprints202410.0296.v1.

thi hong nhung v, The Influence of Acetic Acid and Ethanol on the Fabrication and Properties of Poly(Vinyl Alcohol) Nanofibers Produced by Electrospinning. Polymer Bulletin, 2024, 81, 768-780. DOI: 10.1007/s00289-024-05168-2.

thi hong nhung v, A Systematic Investigation of Solution and Technological Parameters for the Fabrication and Characterization of Poly(Vinyl Alcohol–Chitosan) Electrospun Nanofibers. Polymers for Advanced Technologies, 2024, 35(5), 6423. DOI: 10.1002/pat.6423.

thi hong nhung v, Tafamidis Drug Delivery Systems Based on Chitosan/Polyvinyl Alcohol Matrix. ASEC 2023 Conference Proceedings, 2023. DOI: 10.3390/ASEC2023-15905.

thi hong nhung v, Fabrication of Polyvinyl Alcohol Nanofibers for the Delivery of Biologically Active Molecules. 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2022, pp. 117-123. DOI: 10.1109/iecbes54088.2022.10079434.

thi hong nhung v, Investigation of the Fabrication of Nanofibers from Aqueous Polyvinyl Alcohol Solutions by Electrospinning. Proceedings of the Voronezh State University of Engineering Technologies, 2022, 2, 210-220. DOI: 10.20914/2310-1202-2022-2-210-220.

Conclusion 

Based on her academic achievements, impactful research contributions, and interdisciplinary approach, Dr. Thi Hong Nhung V is an exemplary candidate for the Research for Best Researcher Award. Her work has significantly advanced the fields of nanotechnology and biomaterials, contributing to both scientific progress and practical applications in medicine and engineering.

 

 

 

 

 

 

 

 

 

 

Bernardine Chidozie | Engineering | Best Researcher Award

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Mrs. Bernardine Chidozie | Engineering | Best Researcher Award

Mrs, Bernardine Chidozie, University of Aveiro, Portugal

Mrs. Bernardine Chidozie is a dedicated researcher and PhD student fellow at the University of Aveiro, Portugal, focusing on digital transformation, simulation modeling, and supply chain optimization, especially in the context of Industry 4.0 and 5.0. Her research employs simulation-based methods and digital tools to improve decision-making and operational performance in complex systems, such as healthcare and sustainable supply chains.

 

PROFILE

Orcid profile

Educational Details

With an academic foundation in engineering, Mrs. Chidozie has contributed significantly to projects like the “Sustainable Supply Chain Management Model for Residual Agroforestry Biomass,” utilizing a web platform to support her research, which began in 2022. Her publications explore the impact of digitalization on supply chains, including the optimization of biomass supply chains for sustainability. She has authored books like Simulation-Based Approaches to Enhance Operational Decision Support in Healthcare 5.0 and published articles in notable journals, such as Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix.

Professional Experience

Professionally, Mrs. Chidozie has been involved in various research and consultancy projects, including industry-relevant studies that analyze the role of simulation and digital transformation in optimizing supply chains. She is an active member of the Council for the Regulation of Engineering in Nigeria (COREN) and collaborates on initiatives that bridge research and real-world applications. Her primary goal is to create innovative, technology-driven strategies to enhance sustainability, efficiency, and resilience in industrial and healthcare sectors.

Research Interests

Digital transformation, simulation modeling, supply chain optimization, Industry 4.0 and 5.0 applications, sustainable biomass supply chains, healthcare systems improvement, and decision-support systems.

Top Notable Publications

Chidozie, B.C. (2024). Highlighting Sustainability Criteria in Residual Biomass Supply Chains: A Dynamic Simulation Approach. Sustainability, Published: 2024-11-07, DOI: 10.3390/su16229709, Source: Crossref.

Chidozie, B.C. (2024). Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix: A Methodical Approach. Logistics, Published: 2024-10-18, DOI: 10.3390/logistics8040107, Source: Crossref.

Chidozie, B.C. (2024). The Importance of Digital Transformation (5.0) in Supply Chain Optimization: An Empirical Study. Production Engineering Archives, Published: 2024-03-01, DOI: 10.30657/pea.2024.30.12, Source: Crossref.

Chidozie, B.C. (2024). Analytical and Simulation Models as Decision Support Tools for Supply Chain Optimization – An Empirical Study. The 17th International Conference Interdisciplinarity in Engineering (book chapter), DOI: 10.1007/978-3-031-54671-6_15, ISBN: 9783031546709, Source: Crossref.

Chidozie, B.C. (2024). Impacts of Simulation and Digital Tools on Supply Chain in Industry 4.0. The 17th International Conference Interdisciplinarity in Engineering (book chapter), DOI: 10.1007/978-3-031-54664-8_43, ISBN: 9783031546648, Source: Crossref.

Chidozie, B.C. (2024). Simulation-Based Approaches to Enhance Operational Decision-Support in Healthcare 5.0: A Systematic Literature Review. (book chapter), DOI: 10.1007/978-3-031-38165-2_78, Source: Crossref.

 Conclusion

Mrs. Bernardine Chidozie’s research achievements, particularly her focus on digital transformation and sustainable supply chains, make her a suitable candidate for the Best Researcher Award. Her work is relevant and impactful, addressing key challenges in Industry 4.0 and Healthcare 5.0. Her publications, ongoing projects, and industry involvement illustrate her dedication to advancing sustainability and efficiency across industries, marking her as a distinguished researcher in her field.

 

 

 

 

 

Dongmin Shin | Engineering | Best Researcher Award

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Assist. Prof. Dr. Dongmin Shin | Engineering | Best Researcher Award

Assist. Prof. Dr. Dongmin Shin, Gyeongsang National University, South Korea

Dongmin Shin, Ph.D., is an Assistant Professor of Smart Energy and Mechanical Engineering at Gyeongsang National University, South Korea. His expertise encompasses mechanical system reliability and energy solutions, backed by extensive experience in research and academia at institutions like KIMM and KAIST.

PROFILE

Orcid profile

Educational Details

Dr. Shin holds a Ph.D. in Mechanical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), completed in August 2019, where he also earned his M.S. in Ocean System Engineering in February 2015. His foundational studies began at Hanyang University, where he received a B.S. in Mechanical Engineering in 2013, with a break for military service from 2008 to 2010.

Professional Experience

Dr. Shin joined Gyeongsang National University as an Assistant Professor in September 2022. Prior to this, he was a Post-doctoral Researcher at the Korea Institute of Machinery & Materials (KIMM), focusing on reliability assessment in mechanical systems. His academic journey includes roles at KAIST, where he served as a Research Assistant Professor at the Institute for Security Convergence Research, and at Kunsan National University as a Research Professor within the Shipbuilding & Ocean Equipment Industry Empowerment Center. Additionally, he has experience as a Teaching and Research Management Assistant at KAIST, supporting courses in Fluid Mechanics, Numerical Analysis, and mechanical practice, and assisting with 2-D and 3-D wave tank research.

Research Interests

Dr. Shin’s research interests lie in mechanical system reliability, smart energy systems, ocean engineering, and fluid mechanics, with applications in mechanical system safety and energy efficiency.

Top Notable Publications

“Design Analysis Using Evaluation of Surf-Riding and Broaching by the IMO Second Generation Intact Stability Criteria for a Small Fishing Boat”

Authors: Not provided

Year: 2024

Journal: Journal of Marine Science and Engineering

DOI: 10.3390/jmse12112066

“Numerical Study on Compact Design in Marine Urea-SCR Systems for Small Ship Applications”

Authors: Not provided

Year: 2023

Journal: Energies

DOI: 10.3390/en17010187

“Numerical analysis of thermal and hydrodynamic characteristics in aquaculture tanks with different tank structures”

Authors: Not provided

Year: 2023

Journal: Ocean Engineering

DOI: 10.1016/j.oceaneng.2023.115880

“Evaluation of Parametric Roll Mode Applying the IMO Second Generation Intact Stability Criteria for 13K Chemical Tanker”

Authors: Not provided

Year: 2023

Journal: Journal of Marine Science and Engineering

DOI: 10.3390/jmse11071462

“Wave-induced vibration of a fully submerged horizontal cylinder close to a free surface: a theory and experiment”

Authors: Not provided

Year: 2022

Journal: Ships and Offshore Structures

DOI: 10.1080/17445302.2021.1950344

“Assessment of Excessive Acceleration of the IMO Second Generation Intact Stability Criteria for the Tanker”

Authors: Not provided

Year: 2022

Journal: Journal of Marine Science and Engineering

DOI: 10.3390/jmse10020229

Conclusion

Assist. Prof. Dr. Dongmin Shin’s strong educational background, extensive professional experience, innovative research contributions, commitment to teaching and mentoring, and effective research management make him a highly suitable candidate for the Best Researcher Award. His achievements across academia, applied research, and project management reflect the qualities recognized by this award, underscoring his potential to continue contributing meaningfully to engineering and research fields.