Ehsan Khajavian | Engineering | Research Excellance Award

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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.

Citation Metrics (Scopus)

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80

60

40

20

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Citations
72

Documents
3

h-index
2

        🟦 Citations    🟥 Documents    🟩 h-index


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Featured Publications


Corrosion Protection Strategies for Industrial Equipment Using Electrochemical Techniques

– Materials & Corrosion Research

Wei Jiang | Engineering | Editorial Board Member

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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.

Belkacem Bekhiti | Engineering | Best Researcher Award

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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

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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

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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.

Karla Filian | Engineering | Best Researcher Award

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Mrs Karla Filian |  Engineering |  Best Researcher Award

Graduate student in the Master’s program in Earth Sciences,  at Faculty of Engineering in Earth Sciences, ESPOL Polytechnic University,  Ecuador

Karla Filian Haz is a graduate student pursuing a Master’s in Earth Sciences at ESPOL Polytechnic University. With a background in Mining Engineering, she works as a Project Analyst, contributing to research and academic initiatives in Earth Sciences. Her research focuses on environmental pollution mitigation, water treatment technologies, and sustainable engineering solutions. She has co-authored two indexed journal articles and two conference papers, collaborating with international institutions such as Ghent University and the Mexican Geological Survey. Her work aims to develop innovative solutions for environmental management in mining and water treatment.

Profile:

Academic & Professional Background:

Mining Engineer pursuing a Master’s in Earth Sciences at ESPOL. Currently a Project Analyst, contributing to research, academic initiatives, and program coordination in Earth Sciences. Expertise in event organization, documentation management, and compliance.

Research & Innovations:

  • Research Projects: 4
  • Publications: 2 indexed journal articles, 2 conference papers
  • Citations: h-index: 1, Citations: 2
  • Collaborations: Ghent University (Belgium), Catholic University of Santiago de Guayaquil, Universidad del Pacífico (Ecuador), Mexican Geological Survey (SGM)

Research Areas:

Environmental engineering, pollution mitigation in mining, water treatment technologies, sustainable engineering solutions.

Key Contributions:

Research on environmental pollution, tailing dam risks, and desalination optimization using advanced membranes. Findings contribute to sustainable solutions for water treatment and environmental management in the mining industry.

Publication Top  Notes:

Title: Assessment of Environmental Pollution and Risks Associated with Tailing Dams in a Historical Gold Mining Area of Ecuador
Authors: B. Salgado-Almeida, A. Briones-Escalante, D. Falquez-Torres, E. Peña-Carpio, S. Jiménez-Oyola
Journal: Resources (2024)
Citations: 1