Guanqun Li | Engineering | Best Researcher Award

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Dr. Guanqun Li | Engineering | Best Researcher Award

Associate Researcher at Shengli oilfield, SINOPEC, China

Guanqun Li (李冠群), born in May 1994 in Shandong, China 🇨🇳, is an Associate Researcher at Shengli Oilfield Company, SINOPEC 🛢️. He earned his PhD in Oil and Gas Field Development Engineering from China University of Petroleum (East China) 🎓. His work focuses on the microscopic characterization of shale reservoirs and fluid dynamics in oil and gas systems 🔬💧. With numerous publications in top journals like Fuel and Physics of Fluids 📚, he brings innovation to shale oil recovery technologies. Passionate about fractal modeling and fluid imbibition research, Guanqun Li is contributing significantly to modern energy development ⚙️🌍.

Professional Profile:

Scopus

🔹 Education and Experience 

  • 🎓 Sep. 2016 – June 2019: Master’s in Oil and Gas Field Development Engineering, Yangtze University

  • 📚 Sep. 2019 – June 2023: PhD in Oil and Gas Field Development Engineering, China University of Petroleum (East China)

  • 🏢 July 2023 – Present: Associate Researcher, Shengli Oilfield Company, SINOPEC

🔹 Professional Development 

Dr. Guanqun Li 📘 has shown consistent professional growth, moving from academic research to applied industry innovation. His academic journey through Yangtze University and the China University of Petroleum provided a solid foundation in oilfield development ⚒️. At SINOPEC, he applies his expertise in reservoir simulation, fracturing mechanics, and fluid flow modeling 🔬. He actively contributes to peer-reviewed journals and international conferences 🌍. Guanqun continuously develops novel analytical and fractal models for imbibition in shale formations 🌀. His cross-disciplinary collaboration and technical excellence are hallmarks of his evolving career in the energy sector 🚀.

🔹 Research Focus Category 

Guanqun Li’s research centers on unconventional oil and gas recovery, specifically shale oil reservoir characterization and fluid imbibition mechanisms 🛢️💧. His work explores microscale fluid motion, fractal modeling, and productivity analysis in hydraulically fractured formations 🔍📈. He is especially interested in the spontaneous and forced imbibition processes in complex porous media under various boundary conditions 🧪. His models help optimize horizontal well performance and support enhanced oil recovery (EOR) strategies 🧠⚙️. With a clear focus on improving efficiency in volume fracturing and fluid migration mechanisms, his research is highly impactful in modern petroleum engineering 🚧.

🔹 Awards and Honors 

  • 🏅 Interpore Conference Presentation (2020) – Recognized for outstanding research on production enhancement in fractured wells

  • 📖 Multiple First-Author Publications – Published in top journals like Fuel, Physics of Fluids, and Energy & Fuels

  • 🧠 Acknowledged for Innovative Fractal Modeling – In spontaneous/forced imbibition in shale formations

  • 🥇 Highly Cited Review Paper – On EOR techniques in shale oil (Geofluids, 2021)

Publication Top Notes

  • Title: Quantifying lithofacies-dependent imbibition behavior in continental shale oil by fractal modeling: A case study of the gentle slope fault zone, Jiyang DepressionAuthors: Li Guanqun, Peng Yanxia, Yang Yong, Cao Xiaopeng, Su YuliangJournal: Fuel

    Year: 2025

Conclusion

Dr. Guanqun Li stands out as an emerging leader in petroleum reservoir engineering with clear scientific originality, engineering relevance, and a solid record of first-author publications in high-impact journals. His work has contributed meaningfully to advancing the understanding of shale oil imbibition mechanisms and their application in field operations.

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.

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.