Atilla Biyikoglu | Parametric Design | Best Researcher Award

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Prof. Dr. Atilla Biyikoglu | Parametric Design | Best Researcher Award

Instructor at Gazi University, Turkey.

Dr. Atilla Biyikoglu is a distinguished academic and researcher in the field of mechanical engineering, specializing in energy systems, fuel cells, and thermal sciences. His scholarly journey reflects a commitment to advancing sustainable technologies, with a research portfolio that spans fuel cell models, thermal modeling, refrigeration systems, nanofluids, and energy efficiency in buildings. Over the years, he has published extensively in internationally recognized journals such as the International Journal of Hydrogen Energy and Optics & Laser Technology. Dr. Biyikoglu has also contributed to the practical applications of renewable energy, fuel cell technologies, and energy-efficient designs, shaping both theoretical and applied aspects of the field. His work is characterized by a balance between scientific rigor and industrial relevance, demonstrating his capacity to link research with real-world challenges. Through impactful publications, collaborative projects, and innovative ideas, he has become a recognized figure in sustainable engineering solutions.

Professional Profile

ORCID | Google Scholar

Education 

Dr. Atilla Biyikoglu pursued his higher education with a strong focus on mechanical engineering and energy systems, laying the foundation for his career in advanced research and innovation. His academic training provided him with a comprehensive understanding of thermodynamics, energy conversion, and applied mechanics, enabling him to transition seamlessly into specialized areas such as hydrogen energy, fuel cells, and renewable energy technologies. With a deep interest in sustainable engineering solutions, his educational background combined rigorous technical knowledge with multidisciplinary approaches, which later guided his research in energy-efficient building systems, clean energy integration, and advanced modeling techniques. Throughout his studies, Dr. Biyikoglu was actively involved in academic projects that emphasized problem-solving and innovation, skills that continue to define his research career today. His education not only shaped his expertise in mechanical and energy engineering but also instilled in him a vision of bridging science with real-world technological applications.

Experience 

Dr. Atilla Biyikoglu has built a strong academic and research career marked by significant contributions to mechanical engineering and energy sciences. His professional journey includes extensive teaching, research supervision, and leadership in collaborative projects. He has contributed to the development of advanced fuel cell technologies, renewable energy systems, and energy-efficient building solutions, often working at the intersection of academia and industry. His experiences extend to publishing high-impact journal articles, presenting at international conferences, and engaging with multidisciplinary teams to address global energy challenges. In addition, Dr. Biyikoglu has demonstrated expertise in simulation, modeling, and optimization of thermal and energy systems, enhancing their performance and sustainability. His collaborative spirit has led to co-authored works with national and international researchers, broadening the scope and impact of his studies. Over the years, he has also been recognized with awards for scientific publication, further underlining the value of his contributions to the academic and engineering community.

Research Focus 

Dr. Atilla Biyikoglu’s research focuses on sustainable energy systems, fuel cell technologies, thermal modeling, and energy efficiency in engineering applications. His work covers a wide range of areas, including proton exchange membrane fuel cell models, syngas production through coal gasification, advanced thermal modeling for selective laser melting processes, and optimization of organic Rankine cycle turbines. A key aspect of his research is improving the efficiency and sustainability of energy conversion systems, integrating nanofluids into refrigeration, and developing solutions for heat removal in complex systems. In building sciences, he has investigated optimum insulation thickness using life cycle cost analysis, contributing to sustainable residential construction practices. His research strategy combines modeling, experimental studies, and multi-objective optimization to produce results with both scientific and industrial relevance. By addressing critical issues such as clean energy transition, renewable integration, and energy-efficient design, his research aligns with global sustainability goals and future-oriented energy innovations.

Awards and Honors 

Throughout his career, Dr. Atilla Biyikoglu has received several awards and recognitions for his scholarly achievements and contributions to energy systems research. His work has been acknowledged through national scientific publication awards, reflecting the impact and quality of his contributions in leading international journals. These honors underscore his consistent dedication to advancing the field of fuel cells, renewable energy, and mechanical engineering. In addition to his publication awards, he has been involved in research projects supported by funding institutions, highlighting both the academic and practical relevance of his work. His contributions have also been recognized within academic communities, where he has been invited to present his findings and engage in collaborative research initiatives. These accolades not only validate his research excellence but also affirm his leadership in bridging innovative science with engineering applications. His awards and honors collectively establish him as a leading figure in sustainable and renewable energy research.

Publication Top Notes

Title: RETRACTED: Review of proton exchange membrane fuel cell models
Authors: A. Biyikoglu
Summary: A review of proton exchange membrane fuel cell (PEMFC) models, covering theoretical and computational approaches for performance prediction. Later retracted, but an early effort to synthesize PEMFC modeling knowledge.

Title: Development of thermal model for the determination of SLM process parameters
Authors: K. Ökten, A. Biyikoglu
Summary: Proposed a thermal model for optimizing parameters in Selective Laser Melting (SLM), improving heat transfer understanding and material quality in additive manufacturing.

Title: Design and multi-objective optimization of organic Rankine turbine
Authors: M. Erbaş, A. Biyikoglu
Summary: Designed and optimized an organic Rankine cycle turbine, focusing on efficiency and sustainability in power generation.

Title: Determination of optimum insulation thickness by life cycle cost analysis for residential buildings in Turkey
Authors: N. Aydin, A. Biyikoglu
Summary: Identified optimal insulation thickness using life cycle cost analysis to improve energy efficiency in residential buildings.

Title: A parametric study on coal gasification for the production of syngas
Authors: A. Gungor, M. Ozbayoglu, C. Kasnakoglu, A. Biyikoglu, B.Z. Uysal
Summary: Analyzed parameters affecting coal gasification efficiency and syngas composition for cleaner fuel production.

Title: Production of anhydrous borax from borax pentahydrate
Authors: A. Biicoglu, E. Jackson
Summary: Investigated production of anhydrous borax from borax pentahydrate, focusing on process efficiency and product quality.

Title: Enhancing the performance of a vapour compression refrigerator system using R134a with a CuO/CeO2 nano-refrigerant
Authors: H.E. Mohamed, U. Camdali, A. Biyikoglu, M. Aktas
Summary: Improved refrigeration system efficiency by using R134a with CuO/CeO2 nanoparticles as a nano-refrigerant.

Title: Heat removal improvement in an enclosure with electronic components for air conditioning devices
Authors: M.Z. Yilmazoglu, O. Gokalp, A. Biyikoglu
Summary: Proposed enhanced thermal management techniques for better heat removal in electronic enclosures of air conditioning devices.

Title: Historical development, working principles and current status of fuel cells
Authors: A. Biyikoglu
Summary: Reviewed the evolution, principles, and current advancements in fuel cell technology.

Title: Determination of heat transfer coefficient between heated floor and space using ANSI/ASHRAE standard 138 test chamber
Authors: M.F. Evren, A. Ozsunar, A. Biyikoglu, B. Kilkis
Summary: Evaluated heat transfer coefficients in heated floor systems using ASHRAE standard test chamber methodology.

Conclusion

Dr. Atilla Biyikoglu’s research record demonstrates depth, diversity, and sustained contribution to energy systems and mechanical engineering. His publications, projects, and leadership roles establish him as a strong candidate for the Best Researcher Award. With continued emphasis on international visibility, industry collaboration, and interdisciplinary expansion, his profile has the potential to achieve even greater global impact in advancing sustainable energy technologies.

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Maryam Sadeghi | Smart Cities and Architecture | Best Researcher Award

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Mrs. Maryam Sadeghi | Smart Cities and Architecture | Best Researcher Award

Full-time Faculty Member at Islamic Azad University, Iran.

Maryam Sadeghi is an accomplished researcher and faculty member in Electrical Engineering, specializing in smart grids, distributed control, and intelligent energy systems. She has served as a full-time instructor at the Islamic Azad University, Islamshahr Branch, where she has also chaired the Power Engineering Department. Over the years, she has successfully combined teaching, supervision, and leadership with impactful research contributions. As a PhD candidate at the Iran University of Science and Technology, her doctoral work has advanced the field of power systems with an emphasis on adaptive and intelligent control. Beyond academia, she has actively collaborated with national research and industrial centers, particularly in areas such as SCADA applications, FPGA development, and distributed automation. Her career demonstrates a consistent focus on renewable energy integration, intelligent universal transformers, and advanced automation, positioning her as a thought leader in the evolving landscape of modern electrical engineering.

Professional Profile

Google Scholar

Education

Maryam Sadeghi’s educational background reflects a strong and progressive journey through electrical engineering disciplines. She earned her B.Sc. in Electrical Engineering with a focus on Electronics from the Islamic Azad University, Tehran Central Branch. She further specialized in Control Systems at the M.Sc. level from Islamic Azad University, Tehran South Branch, where she explored adaptive control methodologies. To expand her expertise in the energy sector, she pursued doctoral studies in Electrical Engineering with a specialization in Power Systems at the Iran University of Science and Technology. Her PhD research, with defense approved, focuses on advanced power system automation and intelligent control strategies, including adaptive neuro-fuzzy inference systems and multi-agent approaches for smart grids. Through this academic journey, she has built deep expertise in intelligent systems, renewable integration, and distributed energy automation, forming the backbone of her subsequent teaching, research, and industry collaborations in both traditional and emerging power engineering domains.

Experience 

Maryam Sadeghi has built a multifaceted career blending academia, research, and industry collaboration.  She has been a full-time faculty member at the Islamic Azad University, Islamshahr Branch, teaching undergraduate and graduate courses in power systems and control. As Head of the Power Engineering Department for four years, she led curriculum development, faculty coordination, and student mentorship. Her industry-linked research experience includes a decade as Senior Researcher at Novin Ray Control Co., where she worked on solar energy monitoring, SCADA systems, and energy management integration. She has also contributed to telecommunication research through FPGA-based SDH system design, and to control systems development in distributed automation protocols, particularly IEC 61499. These roles reflect her ability to connect theoretical knowledge with practical applications. Her experience across teaching, applied research, and leadership showcases her as a versatile expert committed to advancing both education and innovation in intelligent energy systems.

Research Focus

Maryam Sadeghi’s research is centered on intelligent power systems, with a focus on adaptive control, fuzzy logic, and distributed automation for modern grids. Her work on Intelligent Universal Transformers (IUTs) has introduced innovative control methodologies using fuzzy logic, artificial neural networks, and genetic algorithms to optimize distribution automation. She has also contributed to decentralized multi-agent coordination frameworks for smart distribution restoration, enabling resilience and flexibility in power networks. Her studies in renewable energy integration—particularly inverter-based distributed generation and wind turbine inverters—highlight her commitment to sustainable energy solutions. Additionally, she has advanced methodologies in GPS-based time synchronization and IEC 61499-based distributed control systems. By combining advanced algorithms with real-world applications such as SCADA and EMS, she bridges the gap between theory and practice. Her research trajectory demonstrates a consistent pursuit of scalable, adaptive, and intelligent solutions for next-generation power grids within the context of smart cities and sustainable development.

Awards and Honors

Maryam Sadeghi has received recognition for her academic and research contributions at both institutional and national levels. She has been nominated for the ARCH Best Researcher Award, reflecting her impactful body of work in power systems and control. Her multiple ISI-indexed publications in smart grids, intelligent automation, and renewable energy integration demonstrate her influence in advancing knowledge in her field. As a contributor to national research centers in Iran, she has played a significant role in developing and implementing control solutions aligned with national energy and telecommunication priorities. Her leadership as Head of the Power Engineering Department also underscores her recognition as an academic mentor and innovator. The combination of research excellence, teaching distinction, and industrial collaboration has positioned her as a respected figure within the engineering community. These honors highlight her dedication to advancing intelligent energy solutions and promoting the integration of innovative methodologies into modern power systems.

Publication Top Notes

Title: Time Synchronizing Signal by GPS Satellites
Authors: M. Sadeghi, M. Gholami
Summary: This paper simulates GPS-based synchronization in MATLAB to achieve high-precision timing. It highlights GPS as a reliable solution for communications and distributed automation systems.

Title: Fuzzy Logic Approach in Controlling the Grid Interactive Inverters of Wind Turbines
Authors: M. Sadeghi, M. Gholami
Summary: The study applies fuzzy logic to enhance grid-connected wind turbine inverter performance. Results show improved stability and efficiency under varying wind conditions.

Title: Advanced Control Methodology for Intelligent Universal Transformers Based on Fuzzy Logic Controllers
Authors: M. Sadeghi, M. Gholami
Summary: The authors propose fuzzy logic controllers for Intelligent Universal Transformers (IUTs). The approach improves adaptability and response in advanced distribution automation.

Title: A Novel Distribution Automation Involving Intelligent Electronic Devices as IUT
Authors: M. Sadeghi, M. Gholami
Summary: This paper presents IUTs as intelligent devices for distribution automation. It demonstrates improved grid reliability and fault management.

Title: Fully Decentralized Multi-Agent Coordination Scheme in Smart Distribution Restoration: Multilevel Consensus
Authors: M. Sadeghi, M. Kalantar
Summary: The research introduces a decentralized multi-agent consensus method for smart distribution restoration. It enhances system resilience and scalability without central control.

Title: Developing Adaptive Neuro-Fuzzy Inference System for Controlling the Intelligent Universal Transformers in ADA
Authors: M. Sadeghi, M. Gholami
Summary: An ANFIS-based controller is developed for IUTs to improve adaptability and precision. The hybrid method outperforms conventional control strategies.

Title: Genetic Algorithm Optimization Methodology for PWM Inverters of Intelligent Universal Transformer for the Advanced Distribution Automation of Future
Authors: M. Sadeghi, M. Gholami
Summary: The study uses genetic algorithms to optimize PWM inverters in IUTs. It reduces harmonic distortion and improves inverter efficiency.

Title: Optimized Control Strategy to Adjust the Intelligent Universal Transformer for Integrating Distributed Resources to Grid
Authors: M. Sadeghi, M. Gholami
Summary: This work introduces an optimized control strategy for IUTs to integrate distributed energy resources. It ensures stable and flexible grid operations.

Conclusion

Overall, Maryam Sadeghi is a strong candidate for the Best Researcher Award. Her research reflects both depth and breadth in intelligent power systems, with practical applications that align with the future of energy distribution and smart grid technologies. With her combination of academic leadership, teaching excellence, and impactful research, she demonstrates qualities that merit recognition. By expanding her international reach and enhancing visibility through broader collaborations and higher-impact publications, she can further solidify her position as a leading researcher in her domain.

Yazhou Zhao | Energy-Efficient Architecture | Young Scientist Award

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Assist. Prof. Dr. Yazhou Zhao | Energy-Efficient Architecture | Young Scientist Award

Experimental Scientist at  Zhejiang University, China

Dr. Yazhou Zhao is an Assistant Research Professor at the College of Energy Engineering, Zhejiang University, and Senior Experimental Scientist at the Key Laboratory of Refrigeration & Cryogenic Technology of Zhejiang Province. A core member of the AI-for-Energy Research Group, he leads projects at the intersection of renewable energy, artificial intelligence, and thermodynamic systems. He has developed the GKS physics simulator for generative-AI-assisted teaching and has contributed to numerous national and international energy projects, including collaborations with the Chinese Academy of Sciences, the Chinese Academy of Engineering, and government–industry programs in geothermal and heat pump technologies. With over 30 peer-reviewed journal publications, multiple patents, and recognition such as the Qianjiang Energy Science & Technology Award, his work focuses on intelligent control of energy systems, geothermal technologies, and digital-twin-based optimization. Dr. Zhao’s contributions align with global low-carbon and net-zero energy goals, positioning him as a leader in energy-efficient architecture and sustainable technologies.

Professional Profile

Scopus

Education

Dr. Yazhou Zhao has pursued a multidisciplinary academic path across engineering and computational sciences. He earned his Ph.D. from the University of the Chinese Academy of Sciences, specializing in Geological Engineering under the supervision of Academician Wang Jiyang and Professor Pang Zhonghe. His doctoral research focused on medium-depth ground-source heat pump systems and coupled thermal-reservoir simulations. Earlier, he completed his Master’s degree in Fluid Mechanics and Aerodynamics at the Institute of Applied Physics and Computational Mathematics, Beijing, conducting advanced research on aero-engine turbomachinery aerodynamics and Lagrangian mesh-free methods. His undergraduate studies were at Wuhan University of Science & Technology. where he earned a Bachelor’s degree in Built Environment & Equipment Engineering. This broad academic foundation across thermodynamics, numerical methods, and renewable energy systems underpins his innovative research in energy engineering and artificial intelligence for sustainable technologies.

Experience

Dr. Yazhou Zhao currently serves as an Experimental Scientist at Zhejiang University, where he advances research in intelligent energy systems and AI-driven simulations. Previously, he was a Postdoctoral Fellow at Zhejiang University, focusing on machine learning applications for building energy systems and multi-physics numerical simulations. His professional journey includes leadership as Principal Investigator on several major renewable energy projects funded by national and provincial programs, including geothermal system optimization and solar-assisted heating technologies. He has collaborated on international projects with partners in Finland and the Netherlands, addressing global challenges in carbon reduction and sustainable architecture. Beyond academia, he has contributed to government consulting projects on geothermal industry strategy and industrial energy-efficiency solutions. With his extensive project management, innovation in AI-assisted digital twins, and applied energy engineering expertise, Dr. Zhao has consistently translated theoretical advancements into practical applications across multiple sectors.

Research Focus

Dr. Yazhou Zhao’s  research bridges thermodynamics, artificial intelligence, and renewable energy engineering. His primary focus is on the intelligent control of building energy systems, with an emphasis on time-varying and nonlinear HVAC systems. He has pioneered AI-driven approaches for fault detection, health monitoring, and decision-making in energy-efficient architecture. A major part of his work involves geothermal and ground-source heat pump technologies, where he has developed novel simulation models and strategies to optimize performance under diverse climatic conditions, particularly in hot-summer/cold-winter zones. His research also advances large-scale computational fluid dynamics (CFD), leveraging machine learning to improve turbulence modeling and thermodynamic simulations across multi-phase and multi-scale systems. Furthermore, Dr. Zhao has contributed to digital twin platforms, integrating physical models, AI, and experimental data for smart operation of complex energy infrastructures. His research is strategically aligned with global carbon neutrality initiatives, offering innovative pathways to sustainable energy transformation.

Awards and Honors 

Dr. Yazhou Zhao ’s contributions have been recognized with multiple awards across academic, research, and coaching achievements. He received the Second Prize of the Qianjiang Energy Science & Technology Award for his groundbreaking project on IoT-based control of smart ground-source heat pump systems. During his early academic career, he won top prizes in national mathematics and modeling competitions, including First Prize in the National Undergraduate Mathematics Competition and honors at the COMAP Mathematical Contest in Modeling. Beyond his research, he has served as a coach, guiding teams to success in global competitions such as the S. T. Yau Science and Physics Awards and the HiMCM contest, securing multiple first prizes. His awards reflect both technical excellence and mentorship, underscoring his leadership in advancing the next generation of researchers while driving forward the field of renewable energy and energy-efficient systems.

Publication Top Notes

Title: An efficient hybrid model for thermal analysis of deep borehole heat exchangers
Authors: Zhao Y., Pang Z., Huang Y., Ma Z. 
Summary: Proposes a hybrid model integrating analytical and numerical methods to improve efficiency in modeling deep borehole exchangers.

Title: A fast simulation approach to the thermal recovery characteristics of deep borehole heat exchanger after heat extraction
Authors: Zhao Y., Ma Z., Pang Z. 
Summary: Introduces a rapid simulation method to evaluate thermal recovery of boreholes, enhancing geothermal system design.

Title: Heat transfer modeling on high-temperature charging and discharging of deep borehole heat exchanger with transient strong heat flux
Authors: Zhao Y., Qin X., Shi X. 
Summary: Develops transient models for high-intensity borehole heat storage, addressing system performance at elevated conditions.

Title: Performance evaluation of solar and condensing heat recovery systems for air reheating and humidification in industrial buildings
Authors: Wu F., Huang X., Zhang L., Gao J., Sun Y., Zhao Y., Zhang X. 
Summary: Evaluates hybrid solar and condensing heat recovery systems, showing improved efficiency in industrial HVAC applications.

Title: Study on the thermal imbalance characteristics and optimal operation strategy of ground source heat pump system in hot summer and cold winter areas
Authors: Zhao Y., Gao J., Wu F., Sun Y., Liu A., Yu Z., Zhang X. 
Summary: Investigates thermal imbalance issues in ground-source systems, offering optimized operation strategies for challenging climates.

Conclusion

Dr. Yazhou Zhao demonstrates a strong blend of academic rigor, technological innovation, and leadership in renewable energy and intelligent building systems. His consistent research contributions, particularly in geothermal energy and advanced heat pump systems, are aligned with pressing global challenges such as carbon neutrality and energy efficiency. With further emphasis on international collaboration and broader dissemination of his work, he stands out as a highly suitable candidate for the Best Researcher Award.

Yao Lu | Energy-Efficient Architecture | Best Researcher Award

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Assoc. Prof. Dr. Yao Lu | Energy-Efficient Architecture | Best Researcher Award

Associate Reseacher at Beijing Institute of Nanoenergy and Nanosystems, China

Dr. Yao Lu is an accomplished researcher specializing in smart batteries, lithium-ion batteries, and flexible sensors. He earned his Ph.D. from the University of Science and Technology Beijing, where he trained in advanced materials and physics at the Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science. He later joined Tsinghua University as a research fellow at the State Key Laboratory of Automotive Safety and Energy, where he advanced research on energy storage and battery safety. Currently, Dr. Lu serves as an Associate Researcher at the Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences. His research emphasizes developing safe, long-life, and energy-efficient battery systems by integrating flexible sensor technologies. With over 25 peer-reviewed publications in leading journals, he has made impactful contributions to both academic science and practical energy applications. Dr. Lu is recognized as a promising researcher shaping the future of sustainable energy storage.

Professional Profile

ORCID

Education

Dr. Yao Lu completed his doctoral studies at the University of Science and Technology Beijing (USTB), where he conducted research at the Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science. His Ph.D. work focused on advanced physics, nanomaterials, and energy systems, laying the foundation for his later work in smart batteries and flexible sensors. At USTB, he gained expertise in electrochemical energy storage mechanisms and safety analysis of high-performance batteries. Following his doctoral training, Dr. Lu pursued additional research opportunities at Tsinghua University, one of China’s most prestigious institutions, where he worked on automotive safety and energy technologies. These academic experiences provided him with a strong interdisciplinary background combining physics, materials science, electrochemistry, and engineering. This broad training equipped him to tackle the pressing challenges in next-generation energy storage technologies, particularly in developing safe, intelligent, and energy-efficient battery systems suitable for electric vehicles and renewable energy applications.

Research Focus 

Dr. Yao Lu’s research focuses on the intersection of energy storage technology, sensor integration, and sustainability. His primary work explores smart lithium-ion batteries enhanced with flexible and implantable sensors that improve safety, performance, and life cycle management. He investigates critical challenges in battery technology, including thermal runaway mechanisms, lithium dendrite suppression, and rapid charging solutions. By combining materials engineering, electrochemical analysis, and sensor fusion techniques, his work aims to create next-generation batteries that are both safe and efficient. Additionally, Dr. Lu contributes to research on zinc-ion batteries and sodium-ion batteries, offering sustainable alternatives to traditional lithium-ion systems. His studies also incorporate AI-enabled battery management systems, providing intelligent monitoring and predictive maintenance capabilities for electric vehicles and large-scale energy storage. Overall, his research represents a forward-looking approach to clean energy innovation, addressing global needs for safer, more reliable, and environmentally responsible power storage solutions.

Publication Top Notes

Title: Zinc-ion batteries: pioneering the future of sustainable energy storage through advanced materials and mechanisms
Authors: Zixuan Chen, Liang Zhang, Tianyu Yu, Huancheng Yang, Yao Lu, Xiaodan Wang, Rui Li, Zonglun Ye, Yue Wang, Pengwei Li et al.
Summary: This article explores zinc-ion batteries as sustainable alternatives to lithium-ion systems. It provides mechanistic insights and highlights material strategies for performance enhancement, opening pathways for environmentally friendly storage solutions.

Title: Manipulation of lithium dendrites based on electric field relaxation enabling safe and long-life lithium-ion batteries
Authors: Xuebing Han, Shuoyuan Mao, Yu Wang, Yao Lu, Depeng Wang, Yukun Sun, Yuejiu Zheng, Xuning Feng, Languang Lu, Jianfeng Hua et al.
Summary: This study addresses lithium dendrite formation, a critical safety issue. The team demonstrated how electric field relaxation strategies can suppress dendrites, prolonging battery life and improving reliability.

Title: AI enabled fast charging of lithium-ion batteries of electric vehicles during their life cycle: review, challenges and perspectives
Authors: Daoming Sun, Dongxu Guo, Yufang Lu, Jiali Chen, Yao Lu, Xuebing Han, Xuning Feng, Languang Lu, Hewu Wang, Minggao Ouyang
Summary: A comprehensive review highlighting AI-driven methods for safe fast charging. The paper identifies challenges and future directions for integrating AI with EV battery management.

Title: Early warning for thermal runaway in lithium-ion batteries during various charging rates: Insights from expansion force analysis
Authors: Kuijie Li, Chen Li, Xuebing Han, Xin Gao, Yao Lu, Depeng Wang, Weixiong Wu, Yuan-cheng Cao, et al.
Summary: This work introduces expansion force analysis as a diagnostic method for predicting thermal runaway, contributing to improved safety monitoring in Li-ion batteries.

Title: In situ evaluation and manipulation of lithium plating morphology enabling safe and long-life lithium-ion batteries
Authors: Shuoyuan Mao, Yu Wang, Yao Lu, Xuebing Han, Yuejiu Zheng, Xuning Feng, Xinqi Ren, Languang Lu, Minggao Ouyang
Summary: The study reports advanced in situ techniques to monitor and control lithium plating, enhancing battery safety and durability.

Title: Smart batteries enabled by implanted flexible sensors
Authors: Yao Lu, Xiaodan Wang, Shuoyuan Mao, Depeng Wang, Daoming Sun, Yukun Sun, Anyu Su, Chenzi Zhao, Xuebing Han, Kuijie Li et al.
Summary: This article highlights how flexible sensors implanted within batteries can revolutionize energy storage by enabling real-time state monitoring and improved safety performance.

Conclusion

Dr. Yao Lu is an outstanding candidate for a Best Researcher Award. His innovative work on smart, safe, and sustainable battery technologies positions him at the forefront of energy materials research. With strong publication achievements, impactful collaborations, and recognition through competitive grants, he demonstrates the qualities of a researcher whose contributions will continue to shape the future of energy storage and flexible sensing technologies.

Dandan Zhu | Parametric Design | Best Researcher Award

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Assoc. Prof. Dr. Dandan Zhu | Parametric Design | Best Researcher Award

Deputy Director of Department at China University of Petroleum, Beijing 

Dr. Dandan Zhu is an Associate Professor at the College of Artificial Intelligence, China University of Petroleum, Beijing. She holds a Ph.D. in Precision Engineering from the University of Tokyo and a Master’s in Aircraft Design from Beihang University. she has advanced pioneering research that connects artificial intelligence with petroleum engineering, specializing in intelligent drilling, trajectory control, and geosteering. Her expertise extends to reinforcement learning, geological modeling, and automation technologies that optimize drilling operations under uncertainty.Dr. Zhu has become a recognized name in intelligent automation. She has collaborated with leading energy enterprises such as CNPC, Sinopec, and CNOOC, ensuring her research achieves practical industry impact. Through her academic leadership, cross-disciplinary collaborations, and contributions to applied AI systems, she has established herself as a forward-looking researcher contributing to innovation in parametric design, energy engineering, and computational intelligence.

Professional Profile

Google Scholar

Education

Dr. Zhu’s academic foundation is built upon two of Asia’s most prestigious universities. She completed her Master’s degree in Aircraft Design at Beihang University, where she gained expertise in structural mechanics, system design, and advanced computational modeling. Driven by her commitment to precision and innovation, she pursued a Ph.D. in Precision Engineering at the University of Tokyo, one of the world’s leading centers for advanced engineering research. Her doctoral studies focused on integrating computational methods, optimization techniques, and AI-based modeling, giving her a strong interdisciplinary foundation. This unique educational background allowed her to bridge the gap between traditional engineering and emerging computational technologies. Her academic journey reflects a balance of theory and applied learning, preparing her to apply parametric design, reinforcement learning, and automation methods to real-world challenges in petroleum engineering. This solid academic training has been instrumental in shaping her contributions to intelligent drilling, trajectory optimization, and automated decision-making systems.

Experience

Dr. Zhu has served as an Associate Professor at the China University of Petroleum, Beijing .Over the course of her career, she has led more than 40 research projects and collaborated with leading global enterprises. Her work has contributed to 27 consultancy projects, directly influencing the development of intelligent drilling and geosteering systems deployed by CNPC, Sinopec, and CNOOC. She has authored 39 peer-reviewed journal articles, presented her findings at international conferences, and actively participates in professional communities such as IEEE, ACM, and SPE. Her experience spans both academia and industry, enabling her to merge advanced computational research with applied petroleum engineering practices. Dr. Zhu’s mentoring of graduate students and supervision of doctoral research further highlight her commitment to cultivating the next generation of engineers and researchers. Her professional journey reflects a blend of academic innovation, technical expertise, and practical solutions, all contributing to advancements in parametric design and energy technologies.

Research Focus 

Dr. Zhu’s research is focused on integrating artificial intelligence with petroleum engineering to create intelligent, adaptive, and sustainable drilling solutions. She specializes in reinforcement learning, parametric design, trajectory control, and real-time decision-making algorithms that address complex geological conditions. Her work leverages simulation-driven optimization and generative models to improve the robustness of drilling strategies. One of her major contributions is the development of a high-interaction learning framework that unites offline training, real-time decision-making, and post-operation knowledge transfer. She has also advanced AI-driven geosteering and subsurface automation frameworks, enhancing exploration efficiency and operational safety. By combining data-driven modeling with practical field-tested systems, her research strengthens automation in petroleum exploration. Looking forward, Dr. Zhu’s vision includes extending parametric design methodologies into sustainable energy technologies, creating intelligent systems that can adapt to future energy transitions. Her work exemplifies the fusion of computational intelligence, applied AI, and design optimization in engineering innovation.

Publication Top Notes

Title: End-to-end multiplayer violence detection based on deep 3D CNN 
Authors: C. Li, L. Zhu, D. Zhu, J. Chen, Z. Pan, X. Li, B. Wang
Summary: This study introduced a deep 3D Convolutional Neural Network (CNN) for activity recognition. The approach enhanced the detection of multiplayer violent behaviors in video sequences, demonstrating improvements in accuracy and robustness. Its applications extend to public safety, surveillance systems, and automated monitoring in complex environments.

Title: Investigation on automatic recognition of stratigraphic lithology using ensemble learning
Authors: K. Gong, Z. Ye, D. Chen, D. Zhu, W. Wang
Summary: This paper proposed an ensemble learning framework to automatically recognize stratigraphic lithology from well logging data. By integrating multiple models, it improved drilling decision-making accuracy and provided reliable geological insights. The work contributes to more efficient and precise subsurface exploration.

Title: Target-aware well path control via transfer reinforcement learning
Authors: Z. Dandan, Q. Xu, F. Wang, D. Chen, Z. Ye, H. Zhou, K. Zhang
Summary: This research applied transfer reinforcement learning for adaptive well path control. By dynamically adjusting trajectories under uncertain geological conditions, the method improved drilling efficiency and accuracy. The framework demonstrated the potential of AI in real-time wellbore guidance.

Title: Reinforcement learning-based 3D guided drilling 
Authors: H. Liu, D. Zhu, Y. Liu, A. Du, D. Chen, Z. Ye
Summary: The study introduced a reinforcement learning method for 3D guided drilling. It moved beyond conventional ground control by enabling intelligent automation in drilling operations. This advancement provided a foundation for safer and more efficient drilling practices.

Title: Deep learning for drilling decisions using APC-LSTM 
Authors: D. Zhu, X. Dai, Y. Liu, F. Wang, X. Luo, D. Chen, Z. Ye
Summary: This work developed the APC-LSTM deep learning model for drilling decision-making in subhorizontal drain geosteering. The model significantly improved predictive accuracy in complex geological formations. It enhanced decision support systems for real-time drilling applications.

Title: Surface dynamometer card reproduction using periodic current data 
Authors: D. Zhu, X. Luo, Z. Zhang, X. Li, G. Peng, L. Zhu, X. Jin
Summary: This research proposed an AI-based approach to reproduce surface dynamometer cards using periodic electric current data. The method provided a cost-effective diagnostic tool for petroleum production monitoring. Its outcomes improved operational reliability and efficiency in field applications.

Title: Comprehensive control system for gathering pipe networks using reinforcement learning 
Authors: Q. Wu, D. Zhu, Y. Liu, A. Du, D. Chen, Z. Ye
Summary: The paper designed a reinforcement learning-based control system for pipeline gathering networks. It optimized energy flow and minimized operational inefficiencies in petroleum transport. The system showed promise in enhancing automation and sustainability in energy infrastructure.

Title: Gait coordination feature modeling for recognition 
Authors: D. Zhu, L. Ji, L. Zhu, C. Li
Summary: This study introduced a multi-scale gait representation framework for gait recognition. By modeling coordination features, the method improved recognition performance across varying walking styles. It contributed to advancements in biometric identification and security systems.

Conclusion

Dr. Dandan Zhu is a strong candidate for the Best Researcher Award. Her record reflects innovation, productivity, and significant contributions to AI-driven petroleum engineering, with tangible outcomes in both academic and industrial contexts. With further growth in international outreach, leadership positions, and wider academic visibility, she has the potential to establish herself as a global leader in intelligent energy systems research.

Dandan Zhu | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Dandan Zhu | Artificial Intelligence | Best Researcher Award

Deputy Director of Department at China University of Petroleum, Beijing, China

Professional Profile

Google Scholar

Summary

Dr. Dandan Zhu is an Associate Professor in the College of Artificial Intelligence at China University of Petroleum, Beijing (CUPB). With a solid background in precision engineering and aircraft design, she specializes in integrating artificial intelligence with petroleum engineering. Since joining CUPB in 2015, she has led numerous national and industry-supported projects, focusing on intelligent drilling, geological modeling, and data-driven automation in subsurface energy exploration. Her work bridges fundamental research and field-based application, contributing to advancements in digital oilfield technologies.

Educational Details:

Dr. Zhu holds a Ph.D. in Precision Engineering from the University of Tokyo, Japan, and a Master’s degree in Aircraft Design from Beihang University, China. Her interdisciplinary academic training provides a unique foundation for innovation at the intersection of engineering mechanics, AI systems, and petroleum technology.

Professional Experience:

Since 2015, Dr. Zhu has been serving as Associate Professor at CUPB’s College of Artificial Intelligence. She has directed over 40 research projects and 27 consultancy collaborations, often partnering with major energy enterprises such as CNPC, Sinopec, and CNOOC. Her initiatives span intelligent trajectory control systems, hydraulic fracturing optimization, and 3D geological simulations. She is also a contributing reviewer and participant in technical forums under IEEE, ACM, and SPE.

Research Interests:

Her core research areas include reinforcement learning, trajectory control algorithms, wellbore guidance systems, and generative simulation environments. Dr. Zhu has developed an integrated learning framework for intelligent drilling that combines offline training, real-time decision-making, and post-drilling optimization. This system improves adaptability in uncertain geological formations and supports automation in energy extraction operations.

Author Metrics:

Dr. Zhu has authored 39 peer-reviewed journal publications indexed in SCI and Scopus. Her work has received a total of 62 citations since 2020. She has published 1 academic book (ISBN: 978-7-3025-3524-9) and holds 5 patents in the domain of AI-enhanced petroleum engineering technologies. Her Google Scholar profile can be accessed here.

Awards and Honors:

Dr. Zhu’s contributions have earned recognition through national-level research grants and industry partnerships. She has been instrumental in building interdisciplinary teams and field-tested innovations that have enhanced both academic understanding and operational performance in petroleum systems. She is actively involved in professional networks such as IEEE, ACM, and SPE, contributing to peer reviews and international conferences.

Publication Top Notes

1. End-to-End Multiplayer Violence Detection Based on Deep 3D CNN

Conference: Proceedings of the 2018 VII International Conference on Network Technology (ICNT)
Publication Date: 2018
Contributors: C. Li, L. Zhu, D. Zhu, J. Chen, Z. Pan, X. Li, B. Wang
Citations (as of latest record): 19
Abstract Summary: This study introduces an end-to-end multiplayer violence detection system utilizing deep 3D convolutional neural networks (CNNs). By analyzing spatial-temporal features in video frames, the model effectively detects violent interactions in multiplayer scenarios, offering potential applications in surveillance and security systems.

2. Investigation on Automatic Recognition of Stratigraphic Lithology Based on Well Logging Data Using Ensemble Learning Algorithm

Conference: SPE Asia Pacific Oil and Gas Conference and Exhibition (Paper ID: D021S016R003)
Publication Date: 2018
Contributors: K. Gong, Z. Ye, D. Chen, D. Zhu, W. Wang
Citations: 12
Abstract Summary: This paper presents an ensemble learning-based methodology for automatically identifying stratigraphic lithology using well logging data. The integration of multiple machine learning models significantly improves lithology classification accuracy, providing intelligent support for geological interpretation in drilling operations.

3. A Reinforcement Learning Based 3D Guided Drilling Method: Beyond Ground Control

Conference: Proceedings of the 2018 VII International Conference on Network Technology (ICNT)
Publication Date: 2018
Contributors: H. Liu, D. Zhu, Y. Liu, A. Du, D. Chen, Z. Ye
Citations: 8
Abstract Summary: The study introduces a reinforcement learning-based 3D guided drilling method to improve directional control in subsurface operations. The framework leverages real-time learning and environmental feedback to optimize drilling paths in complex geological settings, advancing autonomy in petroleum engineering.

4. A Target-Aware Well Path Control Method Based on Transfer Reinforcement Learning

Journal: SPE Journal
Publication Date: 2024
Contributors: Dandan Zhu, Q. Xu, F. Wang, D. Chen, Z. Ye, H. Zhou, K. Zhang
Citations: 6
Abstract Summary: This paper proposes a novel well path control strategy using transfer reinforcement learning to enhance adaptability in trajectory optimization. The model incorporates prior knowledge from similar geological environments to accelerate convergence and ensure target-aware control in complex drilling tasks.

5. Deep Learning Approach of Drilling Decision for Subhorizontal Drain Geosteering Based on APC-LSTM Model

Journal: SPE Drilling & Completion, Volume 38, Issue 01, Pages 1–17
Publication Date: 2023
Contributors: D. Zhu, X. Dai, Y. Liu, F. Wang, X. Luo, D. Chen, Z. Ye
Citations: 6
Abstract Summary: The article introduces an APC-LSTM (Adaptive Prediction and Control with Long Short-Term Memory) deep learning model to enhance real-time decision-making in subhorizontal geosteering operations. This approach improves trajectory accuracy and decision response under uncertain formation conditions.

Conclusion

Assoc. Prof. Dr. Dandan Zhu is a strong and deserving candidate for the Best Researcher Award in Artificial Intelligence. Her innovative, interdisciplinary research, leadership in AI-driven drilling automation, and commitment to real-world applications make her stand out. With a growing publication record, industrial collaboration, and dedication to AI advancement in energy, she embodies the qualities of a forward-thinking and impactful researcher. Strategic international exposure and editorial roles can further enhance her already impressive research trajectory.

Li Qianmu | Technology | Best Researcher Award

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Prof. Dr. Li Qianmu | Technology | Best Researcher Award

Professor at Nanjing University of Science and Technology, China

Professional Profile

Orcid
Scopus

Summary

Professor Li Qianmu is an eminent academic and research leader at Nanjing University of Science and Technology, serving as Deputy Dean of its Research Institute and a PhD supervisor. Internationally recognized for his groundbreaking work in cybersecurity, Professor Li has held influential positions across academia, government, and industry, including as a foreign academician, Tencent Cloud Most Valuable Expert, and Deputy Director of the Expert Committee of the Talent Center under China’s Ministry of Industry and Information Technology. He has contributed significantly to trustworthy intelligent systems and data space technologies, and has published over 70 high-impact papers and authorized more than 100 patents.

Educational Details

Professor Li Qianmu holds a doctoral degree and has cultivated a career anchored in scientific excellence and innovation. As a doctoral supervisor, he plays a pivotal role in mentoring the next generation of researchers in cybersecurity and trustworthy systems.

Professional Experience

Professor Li currently serves as Professor and Deputy Dean at the School of Science and Technology, Nanjing University of Science and Technology. He is a member of the university’s Academic Committee and has also taken on leadership roles such as Vice President of the Jiangsu Computer Society, Vice President of the Jiangsu Cyberspace Security Society, and Team Leader of the General Group of the Jiangsu Digital Standardization Technical Committee. Nationally, he has been involved in shaping AI investment and standards as an Expert Member of the National Artificial Intelligence Industry Investment Fund Advisory Committee and Member of IEC SEG13.

Research Interests

His core research areas include cybersecurity in computing power networks, trustworthy intelligent systems, ontology-based security architectures, industrial internet security, and intelligent perception in large-scale computing networks. His research emphasizes multi-scenario threat modeling, autonomous defense systems, and cognitive countermeasure technologies for critical infrastructure.

Author Metrics 

Professor Li has published over 70 high-level scientific papers indexed in SCI and Scopus journals and conferences, including multiple top-tier international venues. He is the author of the book “Multi-Scenario Threat Endogenous Defense Architecture and Ontology Security Key Technologies” (ISBN: 978-1631815652). His work has garnered extensive citations, and his publications have been included in the 2023 Highly Cited Papers of Wiley and reprinted by NASA laboratories. He was also named the 2019 Challenge Problem Winner at AAAI and authored one of the Top 50 Best Papers at TRB’s centennial conference.

Awards and Honors

Professor Li has received 5 first prizes and 9 second prizes in provincial and ministerial science and engineering categories. Notable achievements include:

  • First Prize, Jiangsu Provincial Science and Technology Progress Award (2023)

  • Top 10 Scientific and Technological Advances in Communications, China Institute of Communications (2024)

  • Second Prize, Wu Wenjun Artificial Intelligence Science and Technology Award (2025)

  • First Prize, Science and Technology Award, China Command and Control Society (2024)

  • Second Prize, Outstanding Achievements Award in Social Sciences, Ministry of Education

  • Second Prize, Jiangsu Provincial Philosophy and Social Sciences Award
    His technologies have been recognized by the China Education and Research Network and adopted into Jiangsu’s standardization initiatives supporting high-quality economic development.

Publication Top Notes

1. A Knowledge Distillation Enhanced Semi-Supervised Federated Learning Framework for Intrusion Detection in EV Charging Networks

  • Journal: IEEE Internet of Things Journal

  • Publication Date: 2025

  • DOI: 10.1109/JIOT.2025.3577666

  • Contributors: Luanjuan Jiang, Qianmu Li, Xun Che, Xin Chen

  • Abstract Summary: This paper presents a semi-supervised federated learning framework enhanced with knowledge distillation for detecting intrusions in electric vehicle (EV) charging networks. The framework addresses data privacy concerns while achieving high detection accuracy with limited labeled data.

2. A Novel Multi-Agent Game-Theoretic Model for Cybersecurity Strategies in EV Charging Networks: Addressing Risk Propagation and Budget Constraints

  • Journal: Energy

  • Publication Date: September 2025

  • DOI: 10.1016/j.energy.2025.136847

  • Contributors: Luanjuan Jiang, Qianmu Li, Xin Chen

  • Abstract Summary: The study introduces a game-theoretic model involving multiple agents to optimize cybersecurity strategies in EV charging networks, accounting for the spread of cyber risks and financial limitations.

3. Research on Hidden Backdoor Prompt Attack Method

  • Journal: Symmetry

  • Publication Date: June 16, 2025

  • DOI: 10.3390/sym17060954

  • Contributors: Huanhuan Gu, Qianmu Li, Yufei Wang, Yu Jiang, Aniruddha Bhattacharjya, Haichao Yu, Qian Zhao

  • Abstract Summary: This article proposes a new prompt-based hidden backdoor attack technique targeting large language models and neural networks, exploring stealth strategies and their implications for AI security.

4. Understanding Convolutional Neural Networks From Excitations

  • Journal: IEEE Transactions on Neural Networks and Learning Systems

  • Publication Date: May 2025

  • DOI: 10.1109/TNNLS.2024.3430978

  • Contributors: Zijian Ying, Qianmu Li, Zhichao Lian, Jun Hou, Tong Lin, Tao Wang

  • Abstract Summary: This research provides a new interpretability framework for convolutional neural networks (CNNs) based on excitation analysis, enhancing understanding of model behavior and feature relevance.

5. BioElectra-BiLSTM-Dual Attention Classifier for Optimizing Multilabel Scientific Literature Classification

  • Journal: The Computer Journal

  • Publication Date: May 15, 2025

  • DOI: 10.1093/comjnl/bxae132

  • Contributors: Muhammad Inaam ul Haq, Qianmu Li, Khalid Mahmood, Ayesha Shafique, Rizwan Ullah

  • Abstract Summary: The paper introduces a novel BioElectra-BiLSTM-Dual Attention model to enhance the multilabel classification of scientific documents, addressing semantic dependencies and optimizing classification accuracy.

Conclusion

Prof. Dr. Li Qianmu stands out as a top-tier candidate for the Best Researcher Award in Technology. His sustained contributions to cutting-edge cybersecurity and AI research, policy advisory roles, and patent output reflect a rare blend of scholarly excellence and practical impact. He represents the ideal embodiment of innovation-driven research leadership.

Salma Akter | Marketing | Best Researcher Award

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Dr. Salma Akter | Marketing | Best Researcher Award

Associate Professor at East West University, Bangladesh

Professional Profile

Scopus

Summary

Dr. Salma Akter, Ph.D., MBA, MSc., FHEA, is an accomplished Associate Professor of Business Administration at East West University, Bangladesh. With over 17 years of global academic experience, she has held faculty roles in both Bangladesh and the UK, contributing significantly to higher education through her dynamic teaching, curriculum development, and student mentorship. She is a recipient of the prestigious East West University Research Excellence Award (2025) and is actively involved in research, academic reviewing, and international education initiatives.

Educational Details

Dr. Akter earned her Ph.D. in Consumer Behaviour from Cardiff Metropolitan University (2017), focusing on the role of children in family buying decisions among British Bangladeshi and Bangladeshi families. She holds an MSc in International Business Management from the University of Gloucestershire (2010), and both MBA and BBA degrees in Marketing from the University of Dhaka, graduating with top honors (1st and 2nd positions, respectively). She also received a Gold Medal for securing 9th place nationally in the HSC merit list. In addition, she holds a UK PTLLS Level 4 Certificate and a Business Certificate from Pearson UK.

Professional Experience

Dr. Akter has taught extensively across diverse academic institutions. She currently serves as Associate Professor at East West University (since July 2024), having previously worked as Assistant Professor there (2018–2024). Her academic tenure includes roles at North South University, London Churchill College, Nelson College, Brit College, and University of Dhaka, among others. In the UK, she taught HND and Edexcel business courses, served in assessment and internal verification roles, chaired academic committees, and led student-focused initiatives. She brings over seven years of teaching and assessment experience from the UK’s higher education sector in multicultural environments.

Research Interests

Her research spans consumer behaviour, F-commerce, artificial intelligence in marketing, and case-based learning strategies. Her doctoral work focused on cross-cultural family purchase decision-making. She has actively contributed to research ethics, data collection, triangulation, and publishing strategies during her Ph.D. studies. She frequently supervises postgraduate theses and is a passionate advocate of student-centered learning and research empowerment.

Author Metrics and Academic Service

Dr. Akter is a reviewer for several indexed journals, including the Asia Pacific Journal of Marketing and Logistics (Emerald), International Journal of Consumer Studies (Scopus), and Asia-Pacific Journal of Management Research and Innovation (SAGE). She also serves on the editorial panel of the Journal of Contemporary Development and Management Studies (UK). Since 2022, she has participated in the QS Higher Education Rankings as a nominated voter among Asian scholars.

Awards and Honors

  • Research Excellence Award 2025 – Faculty and Department level, East West University

  • Gold Medalist – National HSC Examination (9th place, girls' category)

  • Top Graduate – MBA (1st Position) and BBA (2nd Position), University of Dhaka

  • Fellow – Higher Education Academy (FHEA), UK

  • Certified Member – Department for Education (UK), and member of multiple academic societies

Publication Top Notes

1. Can Generative AI be an Effective Co-Teacher? An Experiment

Authors: Niloy, A. C., Akter, S., Sultana, J., Rahman, M. A., Sultana, N., Prome, T. I., Isha, N. J., Afroz, M., Zabeen, M., Tabassum, M., Chowdhury, R., & Sarkar, M.
Published in: Computers & Education: Artificial Intelligence, Elsevier

Volume: 8 | Year: 2025 |

DOI: https://doi.org/10.1016/j.caeai.2025.100418

Summary:
This experimental study evaluates the effectiveness of generative AI tools as co-teachers in higher education settings. The findings suggest that generative AI, when integrated strategically, enhances student engagement, facilitates adaptive learning, and supports instructors in delivering personalized content. This is a pioneering paper combining educational technology, AI integration, and pedagogical transformation, especially relevant in a post-pandemic digital learning environment.

2. Leadership and Innovation against Environmental Degradation

Authors: Rahman, A. & Akter, S.

Editors: Vig, S. & Pandey, A.

Year: 2024

Summary:
This chapter explores the intersection of environmental leadership and innovation, focusing on how corporate managers and policy leaders can adopt proactive, sustainable strategies in response to environmental degradation. It highlights innovative leadership models and CSR approaches, offering actionable insights into sustainability management in developing economies.

3. From Trendsetters to Tastemakers: How Influencer Marketing Influences Consumer Dietary Choices

Authors: Rahman, A. & Akter, S.

Journal: Contaduría y Administración, Elsevier

Year: 2024

Summary:
This paper analyzes the role of social media influencers in shaping consumer dietary behaviors, particularly focusing on health-conscious and youth markets. It applies consumer psychology and marketing theory to examine how trust, aesthetics, and frequency of exposure to influencer content affect nutritional decision-making. The study provides implications for health marketing, public policy, and influencer collaborations.

4. Ethical Considerations in AI-Powered Content Writing: A Case Study in a Developing Country

Authors: Akter, S., Shetu, J. F., Mahbub, F. B., & Nuha, N. T.

Journal: International Journal of Business Forecasting and Marketing Intelligence

Year: 2024

Summary:
This case study investigates the ethical implications of using AI-generated content in the digital marketing ecosystem of a developing country. The study critically evaluates plagiarism, content authenticity, authorship rights, and corporate responsibility. It provides a framework for ethical policy formulation in businesses adopting AI-generated communications.

5. Food Marketing through Social Media Influencers: The Impact on Millennial Cohort Consumers’ Purchasing Intention

Authors: Hoque, M. A., Akter, S., Hafiz, R., & Hoque, I.

Journal: Asian Journal of Business and Accounting (AJBA)

Year: 2024

Summary:
This study explores how food-related content shared by social media influencers affects millennials' purchasing behaviors. Using a quantitative survey design, the research highlights the psychological factors such as relatability, perceived authenticity, and product congruence that mediate influence. The study informs marketing strategies for food and beverage companies targeting digitally active youth.

Conclusion

Dr. Salma Akter exemplifies a well-rounded marketing scholar whose innovative research, pedagogical leadership, and institutional contributions reflect the qualities of an outstanding researcher. Her academic journey, spanning South Asia and the UK, has been marked by consistent output, student mentorship, and impactful scholarship.

Pham Ngoc Chien | Biomaterials | Best Researcher Award

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Dr. Pham Ngoc Chien | Biomaterials | Best Researcher Award

Research Professor at Seoul National University Bundang Hospital, South Korea

Professional Profile

Orcid
Scopus
Google Scholar

Summary

Dr. Pham Ngoc Chien is a biomedical researcher and professor specializing in protein biochemistry, cancer biology, and biomaterials. With over 15 years of interdisciplinary research experience in South Korea, he has made significant contributions to drug discovery, neurophysiology, and tissue engineering. Currently, he serves as a Research Professor at the Department of Plastic Surgery, Bundang Seoul National University Hospital (SNUH), focusing on the therapeutic potential of biomaterials in regenerative medicine.

Educational Details

Dr. Chien earned his Ph.D. in Biochemistry from Hanyang University, Korea (2005–2010), where he investigated the enzymatic mechanism of acetohydroxyacid synthase (AHAS) from Bacillus anthracis and Mycobacterium tuberculosis for antibacterial drug development. He also holds a Bachelor's degree in Biotechnology from Hanoi Open University, Vietnam (1999–2003), with a thesis focusing on genetic evaluation of litchi species using RAPID techniques.

Professional Experience

Dr. Chien has held a series of postdoctoral and leadership roles across top Korean research institutions. He began as a postdoctoral researcher at Hanyang University (2010–2014), focusing on the structural analysis of human PTP proteins. He later joined Konkuk University (2015–2018), where he explored memory formation through eye movement studies in mice. At Boramae SNUH (2018–2020), he investigated lung cancer treatment through signaling pathways in cancer cells. From 2020 to 2022, he worked on biomaterial evaluation in animal models at Bundang SNUH. He then served as Principal Investigator at H&Bio Company (2022–2025), leading translational research in regenerative materials. Since February 2025, he has continued his academic work as Research Professor at Bundang SNUH.

Research Interests

Dr. Chien’s interdisciplinary expertise spans enzymology, protein structure-function analysis, neurophysiology, cancer cell biology, and biomaterials. His recent focus involves evaluating novel biomaterials for wound healing and tissue regeneration using animal models. His technical skillset includes molecular cloning, protein expression/purification, X-ray crystallography, ELISA, Western blotting, immunostaining, and advanced microscopy techniques (SEM, TEM, Confocal). He also has experience in behavioral and physiological assays such as VOR/OKR in rodents.

Author Metrics

Dr. Pham Ngoc Chien has contributed to numerous peer-reviewed publications across biochemistry, physiology, and biomedical engineering. His work has been cited in international journals, with growing recognition in protein-targeted drug development and tissue repair research. Metrics such as h-index, citation count, and journal impact factors can be provided upon request or via his ORCID/Google Scholar profile.

Awards and Honors

Dr. Chien’s career is marked by steady academic progress, successful international collaborations, and recognition for excellence in applied research. Notably, he has led funded research as a Principal Investigator at H&Bio Company and has consistently contributed to high-impact research teams across leading Korean institutions. He continues to mentor junior researchers while advancing translational research in biomedical innovation.

Publication Top Notes

  1. A Comprehensive Review of Natural Compounds for Wound Healing: Targeting Bioactivity Perspective

    • Authors: XT Trinh, NV Long, LT Van Anh, PT Nga, NN Giang, PN Chien, SY Nam, ...

    • Journal: International Journal of Molecular Sciences

    • Volume/Issue: 23(17), Article No. 9573

    • Year: 2022

    • Citations: 111

    • Summary: A critical review examining the pharmacological potential of natural compounds in enhancing wound healing, focusing on anti-inflammatory, antimicrobial, and regenerative mechanisms.

  2. Anaplastic Large Cell Lymphoma: Molecular Pathogenesis and Treatment

    • Authors: XR Zhang, PN Chien, SY Nam, CY Heo

    • Journal: Cancers

    • Volume/Issue: 14(7), Article No. 1650

    • Year: 2022

    • Citations: 62

    • Summary: This paper outlines the molecular underpinnings of anaplastic large cell lymphoma and explores therapeutic approaches, including targeted immunotherapy.

  3. Benign Paroxysmal Positional Vertigo: What We Do and Do Not Know

    • Authors: D Nuti, DS Zee, M Mandalà

    • Journal: Seminars in Neurology

    • Volume/Issue: 40(1), pp. 49–58

    • Year: 2020

    • Citations: 60

  4. The Family-Wide Structure and Function of Human Dual-Specificity Protein Phosphatases

    • Authors: DG Jeong, CH Wei, B Ku, TJ Jeon, PN Chien, JK Kim, SY Park, ...

    • Journal: Biological Crystallography

    • Volume/Issue: 70(2), pp. 421–435

    • Year: 2014

    • Citations: 49

    • Summary: Investigates the crystal structures and enzymatic functions of human DUSP family phosphatases, contributing to insights into cell signaling and therapeutic targeting.

  5. The Light Cupula: An Emerging New Concept for Positional Vertigo

    • Authors: MB Kim, SM Hong, H Choi, S Choi, NC Pham, JE Shin, CH Kim

    • Journal: Journal of Audiology & Otology

    • Volume/Issue: 22(1), pp. 1–5

    • Year: 2017

    • Citations: 44

Conclusion

Dr. Pham Ngoc Chien stands out as an exceptionally well-rounded and impactful researcher in the biomaterials domain. His rich interdisciplinary background, translational focus, and robust publication record make him highly deserving of the Best Researcher Award. With minor enhancements—such as further emphasizing leadership in authorship and international exposure—his candidacy would be nearly impeccable.

Quentin Nouhessèwa Hounyonou | Economics | Best Researcher Award

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Dr. Quentin Nouhessèwa Hounyonou | Economics | Best Researcher Award

Research scholar at Paris 1 University - Panthéon Sorbonne, France

Professional Profile

Orcid

Summary

Dr. Quentin Nouhessèwa Hounyonou is a Beninese economist specializing in energy economics, development, and statistical modeling. With academic and teaching experience across renowned institutions in France, Morocco, and Africa, he focuses on understanding how energy systems influence socio-economic progress in developing countries. His work bridges economic theory and applied research to support resilient and inclusive energy policy design.

Educational Details

Dr. Hounyonou earned his Ph.D. in Economics from Mines Paris (Cerna), PSL University, France (2018–2022), where he studied energy access and Chinese import competition in Africa. He holds a Master’s in Development Economics from UCA, Cerdi, France (2017–2018), with research centered on the revenue impact of energy access in Tanzanian households. He also holds dual engineering degrees: one in Statistics from ENSAE-Dakar, Senegal (2013–2017), and another in Energy from the University of Abomey-Calavi, EPAC, Benin (2008–2013).

Professional Experience

Dr. Hounyonou has taught a wide range of subjects across institutions. From 2023 to 2025, he has been teaching Mathematics and Quantitative Techniques at Paris 1 Panthéon-Sorbonne University. He taught Energy and Development at the Master's level at Grenoble Alpes University (2022–2023), focusing on energy access and climate impact in low-income settings. Previously, he served at the Polytechnic University of Mohamed VI (UM6P) in Morocco (2018–2021), teaching core principles of economics and finance to engineering students.

Research Interests

His research explores the intersection of energy economics, development, and trade, particularly in the African context. He investigates the effects of energy access on household welfare, the role of informal economies in achieving Sustainable Development Goals, and how African firms adapt to global shocks, such as the influx of Chinese imports. His work also examines energy price uncertainty and trade integration across African economies.

Author Metrics

Dr. Hounyonou has presented at international conferences, including the CSAE Conference at the University of Oxford and the GTAP Global Economic Analysis Conference. His research is disseminated through working papers and academic platforms like ResearchGate and LinkedIn. While his ORCID currently lists one published work, several research papers are in progress and have been featured in leading academic forums.

Awards and Honors

Dr. Hounyonou’s work has been recognized through invitations to present at prestigious conferences in energy and development economics. His ongoing contributions to the discourse on energy access and trade in Africa underscore his emerging influence as a thought leader in sustainable development and economic policy.

Publication Top Notes

 How Does the Informal Economy Affect SDGs in Developing Countries?

  • Author(s): Dr. Quentin Nouhessèwa Hounyonou

  • Year: 2024

  • Summary:
    Investigates how the informal economy shapes progress toward Sustainable Development Goals in developing nations, emphasizing both its potential to alleviate poverty and the challenges it poses to policy integration and formal economic planning.

 African Firms’ Adaptation to Chinese Shock under Financial and Electricity Constraints

  • Author(s): Dr. Quentin Nouhessèwa Hounyonou

  • Year: 2022

  • Summary:
    Analyzes how firms in Africa respond to the surge of Chinese imports amid infrastructural and financial constraints. Highlights firm-level resilience linked to better financial access and reliable electricity.

 Advent of Chinese Goods into African Markets: Impact on Firms’ Growth

  • Author(s): Dr. Quentin Nouhessèwa Hounyonou

  • Year: 2021

  • Summary:
    Examines the dual impact of Chinese goods: while they introduce competitive pressure, they also drive innovation among African firms in some sectors.

Electricity Access, Consumption, and Home-Based Business: Evidence from Tanzanian Households

  • Author(s): Dr. Quentin Nouhessèwa Hounyonou

  • Year: 2019

  • Summary:
    Provides empirical evidence that reliable electricity access enables home-based enterprises to thrive, particularly benefiting female entrepreneurship and local economic development.

Conclusion

Dr. Quentin Nouhessèwa Hounyonou is an emerging thought leader in development and energy economics, with a unique multidisciplinary background and a strong record of presenting impactful, policy-relevant research. While his formal publication count is still developing, the depth, relevance, and recognition of his work clearly position him as a strong contender for the Best Researcher Award.