Konstantinos Blazakis | Engineering | Research Excellance Award

Dr. Konstantinos Blazakis | Engineering | Research Excellance Award

Adjunct professor | Hellenic Mediterranean University | Greece

Dr. Konstantinos Blazakis is an electrical and computer engineer and AI researcher specializing in smart energy systems, renewable energy analytics, and advanced machine learning. His work integrates artificial intelligence, quantum machine learning, and power systems, with a strong focus on electricity theft detection, forecasting, and smart grid optimization. He has advanced academic training in electrical and computer engineering, smart grid measurement processing, and applied mathematics and physics, enabling a multidisciplinary approach to energy challenges. His professional background spans university-level teaching, EU-funded renewable energy and photovoltaic research projects, smart grid resilience studies, and contributions to industrial photovoltaic installations and power network design. His research interests include machine learning and deep learning for energy forecasting, smart meter data analytics, quantum neural networks, vehicle-to-grid modeling, and energy market analysis, as well as emerging nanoelectronic devices for next-generation sensing and computing. His work supports the development of resilient, intelligent, and low-carbon energy infrastructures.

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Ehsan Khajavian | Engineering | Research Excellance Award

Mr. Ehsan Khajavian | Engineering | Research Excellance Award

Research Assistant | Ferdowsi University of Mashhad | Iran

Mr. Ehsan Khajavian is a materials and corrosion engineer with strong academic and industrial expertise in corrosion protection, electrochemical analysis, and surface engineering. He holds advanced training in corrosion and protection of materials and materials and metallurgical engineering, with a focus on electrochemical methods, microstructural engineering, and functional surface fabrication. His experience spans academic laboratory supervision, teaching support, and senior industrial roles in technical engineering, metallurgy, and equipment refurbishment. He has contributed to international journals and industrial R&D projects involving corrosion-resistant coatings, casting systems, surface modification, electrochemical instrumentation, and production-line optimization. His research interests center on corrosion science, electrochemical characterization techniques, functional and superhydrophobic surfaces, nanostructured coatings, friction stir processing, and applied corrosion engineering, integrating laboratory-scale research with real-world industrial challenges to deliver durable and scalable materials solutions.

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Corrosion Protection Strategies for Industrial Equipment Using Electrochemical Techniques

– Materials & Corrosion Research

Afera Halefom Teka | Engineering | Research Excellance Award

Mr. Afera Halefom Teka | Engineering | Research Excellance Award

Afera Halefom Teka | University of Chinese Academy of Sciences | Ethiopia

Mr. Afera Halefom Teka is a researcher specializing in cartography, geospatial analysis, hydrology, and land–environment interactions, with strong expertise in GIS, remote sensing, and water resources modeling. His work addresses land use change, hydrological processes, watershed vulnerability, and environmental sustainability across diverse landscapes. With experience in academic teaching, research leadership, and interdisciplinary collaborations, he contributes to evidence-based geospatial solutions for climate resilience, watershed management, and sustainable land–water governance. His research applies spatial modeling, multi-criteria evaluation, machine learning, and advanced cartographic visualization to examine land use dynamics, climate variability, soil erosion risk, groundwater potential, and environmental change detection. He has also taken part in international trainings, conferences, and collaborative projects advancing geospatial applications for disaster risk reduction and resource planning. His contributions have been recognized through academic distinctions, research committee leadership roles, competitive training selections, and conference acknowledgments.

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Featured Publications

Zhi Zong | Engineering | Best Researcher Award

Prof. Dr. Zhi Zong | Engineering | Best Researcher Award

Fuyao University of Science and Technology | China

Professor Zhi Zong is an internationally acclaimed researcher in naval architecture, ocean engineering, computational mechanics, and fluid–structure interaction, widely recognized for his influential contributions to marine hydrodynamics and advanced numerical simulation. With 334 publications, 5,653 citations, and an h-index of 38 (Scopus), his research covers underwater explosion (UNDEX) physics, nonlinear water waves, bubble dynamics, vortex-induced vibration (VIV), unsteady cavitation, water-entry dynamics, and high-fidelity computational fluid mechanics, employing cutting-edge techniques such as SPH, DEM, and data-driven modeling. He has authored over 460 scientific papers, including more than 230 SCI-indexed articles, and has been continuously listed among the Top 2% Scientists globally (2021–2025). His seven authoritative monographs published with Elsevier, Taylor & Francis/CRC, and Science Press span differential quadrature methods, solitary wave theory, computational underwater explosion mechanics, and bubble damage modeling. Professor Zong’s research has significantly advanced understanding of shock loading on marine structures, hydrodynamic impact, cavitating and multiphase flows, ice–structure interactions, ship motion reduction, and complex multi-physics simulations, with many of his highly cited publications regarded as landmark contributions to SPH modeling, multiphase flow analysis, UNDEX damage prediction, and VIV dynamics.

Profiles: Scopus| Google Scholar | ResearchGate

Featured Publications 

• Liu, M. B., Liu, G. R., Lam, K. Y., & Zong, Z. (2003). Smoothed particle hydrodynamics for numerical simulation of underwater explosion. Computational Mechanics, 30(2), 106–118.

• Liu, M. B., Liu, G. R., Zong, Z., & Lam, K. Y. (2003). Computer simulation of high explosive explosion using smoothed particle hydrodynamics methodology. Computers & Fluids, 32(3), 305–322.

• Zong, Z., & Zhang, Y. (2009). Advanced differential quadrature methods. Chapman and Hall/CRC.

• Chen, Z., Zong, Z., Liu, M. B., Zou, L., Li, H. T., & Shu, C. (2015). An SPH model for multiphase flows with complex interfaces and large density differences. Journal of Computational Physics, 283, 169–188.

• Zhang, Y. Y., Wang, C. M., Duan, W. H., Xiang, Y., & Zong, Z. (2009). Assessment of continuum mechanics models in predicting buckling strains of single-walled carbon nanotubes. Nanotechnology, 20(39), 395707.

Wei Jiang | Engineering | Editorial Board Member

Assoc. Prof. Dr. Wei Jiang | Engineering | Editorial Board Member

Associate Dean | Changzhou Institute of Technology | China

Assoc. Prof. Dr. Wei Jiang is an Associate Professor and academic leader specializing in aerospace engineering, aircraft dynamics, structural safety, turbulence response, and reliability-based design. His work integrates advanced modeling with applied engineering to enhance flight safety, structural health monitoring, and high-precision measurement technologies. With significant experience in multidisciplinary research and leadership roles, he has contributed to major scientific projects, industry–academia collaborations, and the development of innovative methods for analyzing nonlinear aircraft behavior under complex atmospheric conditions. His research also extends to precision measurement, tribology, and applied computational analysis, supporting advancements in aircraft performance, predictive maintenance, and structural optimization. His contributions have been recognized through multiple provincial-level honors that acknowledge his impact on engineering innovation and scientific development.

Profile : Scopus 

Featured Publictions 

Chen, J., Chen, Z., & Jiang, W. (2025). A reliability-based design optimization strategy using quantile surrogates by improved PC-kriging. Reliability Engineering & System Safety. Cited by: N/A.

Jiang, W., Guo, H., Li, Z., & Chang, R. C. (2024). Nonlinear unsteady behaviour study for jet transport aircraft response to serious atmospheric turbulence. The Aeronautical Journal. Cited by: N/A.

Jiang, W., Guo, H., Zhu, D., & Chang, R. C. (2024). Optimization of flight conditions based on performance sensitivity analysis for jet transport aircraft. Aircraft Engineering and Aerospace Technology. Cited by: N/A.

Jiang, W., Chang, R. C., Yang, N., & Xu, Y. (2023). Severity assessment of sudden plunging motion for jet transport aircraft in severe turbulence. Aircraft Engineering and Aerospace Technology. Cited by: N/A.

Jiang, W., Chang, R. C., Zhang, S., & Zang, S. (2023). Structural health monitoring and flight safety warning for aging transport aircraft. Journal of Aerospace Engineering. Cited by: N/A.

Hongming Zhang | Engineering | Best Researcher Award

Assoc. Prof. Dr. Hongming Zhang | Engineering | Best Researcher Award

Academician | Beijing University of Posts and Telecommunications | China

Dr. Hongming Zhang is an accomplished Associate Professor at the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China. He earned his Ph.D. in Electrical and Electronic Engineering from the University of Southampton under the supervision of Prof. Lajos Hanzo and Prof. Lie-Liang Yang, following his M.Sc. from Southampton, B.Eng. with Honors from City, University of London, and B.Eng. in Information Engineering from Nanjing University of Aeronautics and Astronautics. Before joining BUPT, he conducted postdoctoral research at Columbia University, contributing to advancements in wireless communication technologies. His research focuses on wireless communications, heterogeneous networking, underwater acoustics, and AI-driven optimization, particularly in areas such as federated learning, intelligent reflecting surfaces, and 6G network design. As a prolific and highly cited researcher, Dr. Zhang has co-authored more than forty IEEE journal papers in collaboration with leading international scholars. His publication record includes 59 documents cited by 967 other documents, totaling 1,207 citations. He has served as an Associate Editor for Electronics Letters and a Review Editor for Frontiers in Communications and Networks. His excellence has been recognized through numerous honors, including the Boosting Project Award for Young Talents from the China Association for Science and Technology, multiple IEEE Best Paper Awards, and the Science and Technology Awards from the China Institute of Communications and the Radio Association of China. His work bridges theory and application, advancing intelligent, energy-efficient communication systems and inspiring innovation within the global telecommunications community.

Profile : Scopus | ORCID 

Featured Publications 

Zhang, H., Yang, L.-L., & Hanzo, L. (2016). Performance analysis of OFDM systems in dispersive indoor power line channels. IET Communications. [Cited by 35]

Zhang, H., Jiang, C., & Hanzo, L. (2019). Linear precoded index modulation. IEEE Transactions on Communications. [Cited by 120]

Zhang, H., & Hanzo, L. (2020). Federated learning assisted multi-UAV networks. IEEE Transactions on Vehicular Technology. [Cited by 90]

Jiang, H., Xiong, B., & Zhang, H. (2023). Hybrid far- and near-field modeling for RIS assisted V2V channels. IEEE Transactions on Wireless Communications. [Cited by 45]

Zhang, H., et al. (2024). Space-time shift keying aided OTFS modulation for orthogonal multiple access. IEEE Transactions on Communications. [Cited by 20]

Belkacem Bekhiti | Engineering | Best Researcher Award

Prof. Belkacem Bekhiti | Engineering | Best Researcher Award

Prof. Belkacem Bekhiti | Institute of Aeronautics and Space Studies, University of Blida | Algeria

Dr. Bekhiti Belkacem is a distinguished academic and researcher in control theory, robotics, and aerospace engineering, currently serving as a Lecturer at the Institute of Aeronautics and Space Studies, Blida University 1, Algeria. His expertise spans guidance, navigation, and control systems, integrating theoretical modeling with real-world aerospace applications. He holds a Doctorate in Electrical Engineering with a specialization in Automatic Control from the University of Boumerdes, a Magister in Advanced Control of Complex Systems from the National Polytechnic School, Oran, a Master’s in Automatic Control from the University of Djelfa, and an Engineering degree in Electrical Engineering from Boumerdes. His career includes teaching positions at Blida and Djelfa Universities, collaboration with the Algerian Air Agency, and supervision of advanced student projects in UAVs, satellite control, and robotics. His research focuses on MIMO control, matrix polynomial theory, robotic modeling, nonlinear adaptive control, and intelligent aerospace system design, merging classical automation with artificial intelligence and fractional-order control. He has authored several books and numerous international publications, presented his work at major conferences, and earned recognition for his contributions to intelligent control and aerospace systems. His influence extends across the Algerian and international research communities, where he continues to inspire innovation and academic excellence in modern control and aeronautical engineering.

Profile : Google Scholar 

Featured Publications 

  • Bekhiti, B. (2015). On the theory of λ-matrices based MIMO control system design. Control and Cybernetics.

  • Bekhiti, B. (2017). Intelligent block spectral factors relocation in a quadrotor UAV. International Journal of Scientific Computing (IJSCC).

  • Bekhiti, B. (2018). On λ-matrices and their applications in MIMO control systems design. International Journal of Mathematical and Computational Intelligence (IJMIC).

  • Bekhiti, B. (2020). On the block decomposition and spectral factors of λ-matrices. Control and Cybernetics.

  • Bekhiti, B. (2020). Internal stability improvement of a natural gas centrifugal compressor. Journal of Natural Gas Science and Engineering.

Jingyi Gao | Engineering | Best Researcher Award

Ms. Jingyi Gao | University of Virginia | United States

Ms. Jingyi Gao | University of Virginia | United States

Jingyi Gao is a Ph.D. candidate in Systems and Information Engineering at the University of Virginia with a 3.75 GPA, focusing on time series prediction, Bayesian probabilistic modeling, and federated learning. She holds an M.S. in Applied Mathematics and Statistics from the Johns Hopkins University (GPA 3.9) and dual bachelor’s degrees in Mathematics–Computer Science and Economics from the University of California, San Diego. Jingyi has extensive teaching experience, serving as a teaching assistant at UVA where she has instructed over 1,000 students across multiple courses in statistical modeling, data mining, AI, and big data systems, and previously supported courses at Johns Hopkins and UC San Diego. She has mentored underrepresented students through the Data Justice Academy and completed research internships at the University of Pittsburgh and Tencent, developing machine learning models for stress detection, healthcare data analysis, and cloud resource forecasting. Jingyi has authored several publications, including work accepted by Pattern Recognition and under review at AAAI and IISE Transactions. Her recent projects involve designing deep latent variable models for ergonomic risk assessment, developing real-time adaptive prediction frameworks for occupational health monitoring, creating federated learning approaches for multi-output Gaussian processes, and modeling behavioral regularity and predictability from multidimensional sensing signals. Combining expertise in machine learning, statistical modeling, and data-driven decision systems, Jingyi aims to advance human-centered intelligent systems through interpretable and privacy-preserving predictive modeling.

Profile: Scopus | Google Scholar

Featured Publications 

Gao, J., Rahman, A., Lim, S., & Chung, S. TimeSets: A real-time adaptive prediction framework for multivariate time series (Manuscript under review at the Association for the Advancement of Artificial Intelligence).

Gao, J., Lim, S., & Chung, S. Gait-based hand load estimation via deep latent variable models with auxiliary information (Manuscript under review at IISE Transactions).

Gao, J., & Chung, S. Federated automatic latent variable selection in multi-output Gaussian processes (Accepted for publication in Pattern Recognition)*.

Gao, J., Yan, R., & Doryab, A. Modeling regularity and predictability in human behavior from multidimensional sensing signals and personal characteristics. Proceedings of the International Conference on Machine Learning and Applications (ICMLA). Institute of Electrical and Electronics Engineers.

Chen, T., Chen, Y., Gao, J., Gao, P., Moon, J. H., Ren, J., … & Woolf, T. B. Machine learning to summarize and provide context for sleep and eating schedules. bioRxiv.

Nan Li | Engineering | Best Researcher Award

Dr. Nan Li | Engineering | Best Researcher Award

Associate researcher at erospace Information Research Institute, Chinese Academy of Sciences, China

Dr. Nan Li is an accomplished Associate Researcher at the State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences. With a strong interdisciplinary foundation in biomedical engineering and automation, she specializes in developing microfluidic-based nucleic acid and immunoassay detection systems. Dr. Li has contributed significantly to the advancement of rapid, portable, and sensitive diagnostic technologies, many of which are aimed at point-of-care and field diagnostics for infectious diseases. Her work is deeply rooted in translational research, seamlessly integrating microengineering, biotechnology, and clinical diagnostics.

Profile

Scopus

🎓 Education

Dr. Nan Li received her Ph.D. in Biomedical Engineering from the prestigious Tsinghua University in 2022, after completing her undergraduate degree in Automation from the Beijing Institute of Technology in 2016. During her doctoral studies, she focused on the development of centrifugal microfluidic platforms and integrated biosensing systems, gaining critical experience in both academic research and real-world biomedical applications. Her academic journey laid the groundwork for a career dedicated to creating impactful diagnostic tools for global healthcare needs.

💼 Experience

Dr. Li currently serves as an Associate Researcher at the Chinese Academy of Sciences, where she leads projects under the State Key Laboratory of Transducer Technology. She has also been actively involved in collaborative efforts with academic and industrial partners to translate laboratory innovations into commercial and clinical applications. In addition to her research responsibilities, Dr. Li contributes to scholarly activities as a journal reviewer for Microsystems & Nanoengineering and Current Analytical Chemistry. She has also delivered oral presentations at prominent international conferences such as Transducers 2025 and IEEE Sensors 2024, further reflecting her stature in the field.

🔬 Research Interests

Dr. Li’s core research interest lies in microfluidic technology for nucleic acid amplification, multiplex detection, and point-of-care diagnostics. She is particularly focused on developing integrated fluidic systems that are capable of rapid, accurate, and simultaneous detection of multiple pathogens or biomarkers. Her work often involves combining engineering principles such as centrifugal force and Euler force with advanced biochemical assays like LAMP and CRISPR. This interdisciplinary approach enables her to create portable diagnostic tools with immense potential in epidemic control, food safety, and personalized medicine.

🏆 Awards

Dr. Nan Li’s exceptional work has earned her several prestigious honors, including the Outstanding Reviewer Award from Microsystems & Nanoengineering in 2024. She was recognized as one of the Outstanding Graduates in Beijing in both 2016 and 2022. She also received the First Prize of Tsinghua University Comprehensive Scholarship in 2020 and the Gold Star Distinguished Research Award from the Biochip (Beijing) National Engineering Research Center in 2018 and 2020. Earlier in her academic journey, she was a recipient of the Tsinghua Future Scholar Scholarship, an award conferred upon top-performing doctoral candidates.

📚 Publications

Among Dr. Li’s numerous scientific publications, the following seven represent high-impact research in her field:

  1. Tianping Zhou, Nan Li* (2025). Sensors and Actuators B: Chemical. “Shockproof magnetofluidic multiplex nucleic acid system” – DOI: 10.1016/j.snb.2025.138139.

  2. Nan Li# et al. (2025). Biosensors & Bioelectronics, “Chip-based universal strategy for multiplex PCR”, Vol. 269, 116921.

  3. Bin Xiao# et al., Nan Li* (2024). Food Chemistry, “Toothpick DNA extraction with LAMP platform”, Vol. 460, 140659.

  4. Jiajia Liu# et al., Nan Li# (2024). Small Methods, “One-pot multiplex virus detection”, Vol. 8, 2400030. (Cover Article).

  5. Nan Li# et al. (2022). Sensors and Actuators B: Chemical, “Euler force-assisted sequential liquid release”, Vol. 359, 131642.

  6. Nan Li et al. (2022). Lab on a Chip, “Fully integrated SNP genotyping for hearing loss”, Vol. 22(4): 697–708. (Cover Article).

  7. Nan Li# et al. (2021). Microsystems & Nanoengineering, “Raw-sample-in multiplexed detection system”, Vol. 7(1): 94.

These works are widely cited and demonstrate her contributions to practical innovations in diagnostic technologies.

✅ Conclusion

Dr. Nan Li’s trajectory exemplifies a dedicated and forward-thinking researcher whose work merges engineering innovation with biomedical applications. Through her trailblazing research in microfluidic systems and portable diagnostics, she has not only addressed pressing needs in healthcare but also helped shape the future of rapid disease detection. Her consistent output of high-impact publications, international recognition, and impressive list of awards collectively make her a deserving candidate for a Best Paper Award. Dr. Li’s blend of creativity, precision, and practical implementation reflects the qualities that such an award seeks to honor.

Lei Zhan | Automotive Part Lightweight Research | Best Researcher Award

Prof. Dr. Lei Zhan | Automotive Part Lightweight Research | Best Researcher Award

Professor at Jilin Communications Polytechnic, China.

Prof. Dr. Lei Zhan is a distinguished material science and vehicle engineering expert with over two decades of experience in both academia and industry. His work focuses on the development and application of lightweight and composite materials in automotive manufacturing. Recognized for his innovation, he has earned numerous national awards and holds a robust portfolio of patents. Currently a professor at Jilin Communications Polytechnic, he continues to advance sustainable and high-performance automotive solutions through collaborative research and technology development.

Professional Profile

Scopus 

Orcid

🎓 Education 

  • Ph.D. in Material Processing Engineering, Jilin University, China (2005–2010)

  • B.Sc. in Vehicle Engineering, Lanzhou Jiaotong University, China (1997–2001)

💼 Experience 

Prof. Dr. Lei Zhan is currently a Professor at Jilin Communications Polytechnic (since January 2024), where he leads research on lightweight technologies for automotive components. From 2010 to 2023, he served as Product Director at Faway Company, contributing to product strategy, technological innovation, and advanced research on automotive components. Earlier in his career (2001–2005), he worked at CRCC as a Product Engineer, focusing on the design and development of subway vehicles.

🔬 Research Interests

  • Lightweight alloy materials for automotive applications: synthesis, microstructure control, and mechanical properties

  • Development of novel ceramic materials, intermetallics, and cermets

  • Combustion synthesis and phase evolution mechanisms in ceramic/metal composites

  • Design and integration of composite materials in automotive, aerospace, and machining systems

🏆 Honors and Recognitions

Prof. Dr. Lei Zhan’s contributions to the field have been recognized through various awards and honors:

  • First Prize, China National Innovation Method Competition (2019)

  • First Prize, Jilin Province Division of the National Innovation Method Competition (2021)

  • Second Prize, Outstanding Innovation Achievements of Employees in the Fourth Changchun City (2023)

  • May-First Labor Medal, Changchun City (2018)

  • Multiple awards for outstanding technological innovation achievements at provincial and city levels

Author Metrics

  • Publications: 21 peer-reviewed international papers

  • Intellectual Property: 80 applied patents, 69 granted

  • Notable Collaborations: NSFC, Jilin Province, Ministry of Education (China)

Top Noted Publications:

The mechanism of combustion synthesis of (TiCₓNᵧ–TiB₂)/Ni from a Ni–Ti–C–BN system

👨‍🔬 Authors:

  • Lei Zhan

  • Ping Shen

  • Qichuan Jiang

📚 Journal:

Powder Technology, 2011

📊 Citations:

17 citations (as per current database info)

🧪 Abstract (summary of study):

This study investigates the combustion synthesis mechanism for producing ceramic–metal composites of (TiCₓNᵧ–TiB₂)/Ni using a Ni–Ti–C–BN powder system. The research focuses on the reaction pathway, microstructure evolution, and phase formation. It helps clarify how the combustion reaction propagates and forms complex hard phases useful for high-performance materials, particularly for automotive and cutting tool applications.

Conclusion:

Prof. Dr. Lei Zhan is a highly qualified candidate for the Best Researcher Award in Automotive Part Lightweight Research. His sustained contributions across academia and industry, combined with innovation-driven recognition, position him as a leading force in developing sustainable automotive technologies.

With minor enhancements in international collaboration and publication strategy, his already-strong profile could evolve into global leadership in this critical research domain. His nomination is strongly recommended for the award.