Weitao Yue | Engineering | Research Excellence Award

Dr. Weitao Yue | Engineering | Research Excellence Award

China University of Mining and Technology | China

Dr. Weitao Yue is a Ph.D. candidate in Safety Science and Engineering at the China University of Mining and Technology, recognized for his specialization in coal and rock dynamic disaster prevention and control. With an academic foundation centered on advanced safety engineering and a research focus on hazardous dynamic phenomena in mining environments, he has developed strong expertise in the investigation of disaster mechanisms, monitoring technologies, early-warning strategies, and innovative control methods. His professional experience includes substantial involvement in major national scientific projects, where he has taken on core research roles involving theoretical modeling, experimental system development, large-scale data analysis, and interdisciplinary coordination. Through these efforts, he has demonstrated leadership, technical depth, and the ability to drive complex research tasks toward impactful outcomes. Dr. Yue has published multiple high-quality SCI papers as first or corresponding author in internationally renowned journals, with several works recognized among the most globally cited in the field, reflecting his rising academic influence and contribution to advancing coal mine safety science. His research achievements have earned significant academic recognition, further supported by his participation in professional research communities and contributions to collaborative scientific endeavors. Known for integrating theoretical insight with practical application, he consistently delivers research that supports safer mining operations and enhances scientific understanding of dynamic disasters. His growing portfolio of accomplishments, strong methodological capabilities, and commitment to scientific innovation position him as a promising researcher with substantial potential for future leadership and continued contribution to the safety engineering discipline.

Profiles:  Scopus

Featured Publications

1. [Authors not provided]. (2026). Failure mechanisms of fault fracture zone under dynamic loading. Engineering Failure Analysis.

Dongfeng Qi | Engineering | Best Researcher Award

Prof. Dongfeng Qi | Engineering | Best Researcher Award

Professor | Shandong University of Technology | China

Prof. Dongfeng Qi is a leading researcher in laser manufacturing and material processing, specializing in femtosecond and nanosecond laser applications for advanced materials and flexible electronics. His work integrates theoretical modeling with experimental techniques to develop innovative micro- and nanostructures, including copper and silicon-based materials, phase-change films, and smart electronic devices. Prof. Qi has made substantial contributions to understanding laser-material interactions and patterning technologies, with high-impact publications in top-tier journals. He demonstrates strong interdisciplinary collaboration and mentorship, fostering international research partnerships and the growth of emerging scientists. His research is recognized for both fundamental insights and practical applications in photonics, energy storage, and flexible electronics. Prof. Qi’s consistent innovation, high-quality experimental work, and leadership in the field establish him as a leading figure in laser-based materials science. According to Scopus, he has 535 citations, 71 documents, and an h-index of 13.

Profiles: Scopus | Google Scholar

Featured Publications

1. Programming nanoparticles in multiscale: optically modulated assembly and phase switching of silicon nanoparticle array; L. Wang, Y. Rho, W. Shou, S. Hong, K. Kato, M. Eliceiri, M. Shi, …; ACS Nano, vol. 12, no. 3, pp. 2231–2241, 2018; 39 citations

2. Time-resolved analysis of thickness-dependent dewetting and ablation of silver films upon nanosecond laser irradiation; D. Qi, D. Paeng, J. Yeo, E. Kim, L. Wang, S. Chen, C. P. Grigoropoulos; Applied Physics Letters, vol. 108, no. 21, 2016; 37 citations

3. Femtosecond laser-induced large area of periodic structures on chalcogenide glass via twice laser direct-writing scanning process; X. Yu, Q. Zhang, D. Qi, S. Tang, S. Dai, P. Zhang, Y. Xu, X. Shen; Optics & Laser Technology, vol. 124, 105977, 2020; 34 citations

4. Progress in the design, nanofabrication, and performance of metalenses; Z. Wang, Y. Wu, D. Qi, W. Yu, H. Zheng; Journal of Optics, vol. 24, no. 3, 033001, 2022; 31 citations

5. Progress in preparation and applications of Te-As-Se chalcogenide glasses and fibers; Z. Wu, Y. Xu, D. Qi, Q. Nie, X. Zhang; Infrared Physics & Technology, vol. 102, 102981, 2019; 31 citations

Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

Phd Candidate at University of Exeter, United Kingdom

Amir Hossein Poursaeed is an accomplished researcher in electrical engineering with a specialization in power systems, machine learning applications, and renewable energy integration. Holding a Master’s degree from Lorestan University, he has developed a strong academic foundation complemented by an exceptional research portfolio. His work focuses on power system protection, stability, and optimization using advanced AI techniques such as explainable deep learning and quantum neural networks. With over 17 peer-reviewed journal publications, many in Q1 journals, and multiple IEEE conference contributions, his research demonstrates both depth and innovation. He collaborates with leading academics internationally and has contributed to interdisciplinary studies in environmental modeling and water resource management. Amir’s commitment to cutting-edge research in inverter-based power grids, fault diagnosis, and energy systems places him among the promising young scholars in the field. His achievements reflect a rare blend of technical expertise, research leadership, and forward-looking vision essential for shaping the future of smart grids.

Professional Profile 

Google Scholar
ORCID Profile 

Education

Amir Hossein Poursaeed has a solid educational background in electrical engineering with a focus on power systems. He earned his Master of Science degree from Lorestan University, Iran, where he specialized in Digital Power System Protection and Power System Dynamics. His M.Sc. thesis, supervised by Professor Farhad Namdari, focused on using Support Vector Machines for wide-area protection against voltage and transient instabilities. He previously obtained his Bachelor of Science in Electrical Engineering from the same university, where he explored the optimal placement of phasor measurement units using metaheuristic algorithms. His academic performance was commendable, with a GPA of 18.87/20 in his M.Sc. program, demonstrating both technical strength and research capability. Throughout his education, he consistently focused on high-voltage systems, optimization, and smart grid technologies, laying the foundation for his research in AI-based power system protection and stability. His educational journey highlights a continuous commitment to excellence and innovation in energy systems.

Professional Experience

Amir Hossein Poursaeed has developed a robust professional profile centered around advanced power system research and academic collaboration. While specific institutional roles aren’t explicitly mentioned, his extensive list of high-impact publications indicates active involvement in collaborative research projects, particularly with institutions such as Lorestan University and international partners. He has co-authored multiple studies with recognized scholars, including Professor Farhad Namdari and Dr. P.A. Crossley, highlighting his integration into the global research community. His contributions include the design of advanced fault detection systems, AI-driven stability analysis tools, and renewable energy integration models. Additionally, his work in inter-turn fault diagnosis and real-time system protection showcases applied engineering skills with a focus on practical solutions for modern grid challenges. His experience spans theoretical research, model development, and algorithm implementation in live or simulated systems, establishing him as a well-rounded researcher in academia and an emerging leader in AI-enabled power engineering technologies.

Research Interest

Amir Hossein Poursaeed’s research interests are rooted in the intersection of electrical power systems and artificial intelligence. His primary focus includes power system stability, digital protection systems, fault detection, and the integration of renewable energy sources. He is especially passionate about leveraging advanced machine learning and explainable AI techniques for enhancing grid reliability and system monitoring. His recent work involves deep learning, support vector machines, and quantum neural networks applied to inverter-based power systems and DC microgrids—fields gaining global relevance due to the rise of decentralized energy systems. Optimization algorithms, transient analysis, and wide-area protection schemes are other key domains of his expertise. He also extends his knowledge into environmental systems, working on AI-based models for water quality assessment. This multidisciplinary approach underlines his goal of developing intelligent, robust, and real-time frameworks for smart grid operations, making his research both innovative and impactful in addressing contemporary and future challenges in energy systems.

Award and Honor

Although specific awards and honors are not listed, Amir Hossein Poursaeed’s academic and research accomplishments position him as a candidate deserving of high recognition. His publication record in prestigious Q1 journals, such as Applied Soft Computing, Energy Reports, and Sustainable Energy Technologies and Assessments, reflects scholarly excellence. His papers have introduced novel contributions to power system protection and AI-based monitoring, often co-authored with leading international experts—an indication of his growing reputation in the field. His research has also been accepted at major IEEE conferences, including the International Universities Power Engineering Conference and the International Conference on Electric Power and Energy Conversion Systems, which highlights peer recognition of his work. Moreover, his interdisciplinary research in water resource management using machine learning models demonstrates his versatility and impact beyond core power engineering. Given these achievements, he is highly deserving of academic awards, particularly those that celebrate emerging researchers and innovators in smart energy systems.

Conclusion

Amir Hossein Poursaeed is an emerging thought leader in the field of power systems and intelligent energy technologies. With a strong educational background and a research focus on AI-driven solutions for grid stability and protection, he has consistently demonstrated excellence in both theoretical innovation and practical application. His contributions span power engineering, machine learning, and even environmental sciences—showcasing his ability to bridge disciplines for impactful solutions. Through numerous high-impact publications and international conference engagements, he has established himself as a respected voice in the global research community. His work addresses critical challenges in inverter-based grids, renewable integration, and real-time monitoring, aligning perfectly with the global shift toward sustainable and resilient energy systems. Amir’s trajectory reflects not only technical brilliance but also research leadership, collaboration, and a vision for smarter, safer, and more efficient power systems. He is undoubtedly a strong candidate for honors such as the Best Researcher Award.

Publications Top Notes

  • Title: An Ultra-Fast Directional Protection Scheme for DC Microgrids Based on High-Order Synchrosqueezing Transform
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2023
    Citations: 7

  • Title: Online Transient Stability Assessment Implementing the Weighted Least-Square Support Vector Machine with the Consideration of Protection Relays
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 6

  • Title: A New Strategy for Prediction of Water Qualitative and Quantitative Parameters by Deep Learning-Based Models with Determination of Modelling Uncertainties
    Authors: M. Poursaeid, A.H. Poursaeed
    Year: 2024
    Citations: 6

  • Title: Online Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2020
    Citations: 6

  • Title: High‐Speed Algorithm for Fault Detection and Location in DC Microgrids Based on a Novel Time–Frequency Analysis
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2024
    Citations: 3

  • Title: Hydraulic Modeling of the Water Resources Using Learning Techniques
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2022
    Citations: 3

  • Title: Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 2

  • Title: Simulation Using Machine Learning and Multiple Linear Regression in Hydraulic Engineering
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2023
    Citations: 2

  • Title: Optimized Explainable Tabular Transformer Model for Fault Localization in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari, P.A. Crossley
    Year: 2025
    Citations: 1

  • Title: Optimal Coordination of Directional Overcurrent Relays: A Fast and Precise Quadratically Constrained Quadratic Programming Solution Methodology
    Authors: A.H. Poursaeed, M. Doostizadeh, S. Hossein Beigi Fard, A.H. Baharvand, F. Namdari
    Year: 2024
    Citations: 1

Kaili Wang | Engineering | Best Researcher Award

Ms. Kaili Wang | Engineering | Best Researcher Award

Student at NB U, China

MS Kaili Wang is a distinguished researcher in the field of gene editing and molecular diagnostics, specializing in nucleic acid detection for agricultural biotechnology. She is affiliated with Ningbo University, School of Food Science and Engineering, China, and collaborates with Zhejiang Academy of Agricultural Sciences and the State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products. With a keen interest in genetic modification detection, her research focuses on improving the precision and sensitivity of detection methods for gene-edited organisms. Her recent work on droplet digital PCR (ddPCR) for MSTN gene-edited cattle has contributed significantly to the field of regulatory science and food safety. Dedicated to advancing biotechnology applications, she plays a crucial role in shaping methodologies for genetic monitoring, ensuring consumer safety, and fostering global discussions on gene editing and its implications.

Professional Profile

Education

MS Kaili Wang pursued her higher education in biotechnology, molecular biology, and food science, which provided a strong foundation for her research career. She earned her degrees from prestigious Chinese institutions, including Ningbo University, where she specialized in food science and genetic detection methods. Her academic training emphasized molecular diagnostics, genetic engineering, and PCR-based technologies, equipping her with the expertise necessary to develop innovative detection methods for genetically modified organisms (GMOs). Throughout her education, she engaged in interdisciplinary research, gaining hands-on experience in genetic modification analysis, nucleic acid quantification, and regulatory science. Her studies were complemented by rigorous laboratory work and collaborations with leading scientists in the field. This educational background has enabled her to contribute significantly to the advancement of gene-editing detection technologies, ensuring accuracy, sensitivity, and reliability in molecular diagnostics.

Professional Experience

With extensive experience in genetic research and molecular diagnostics, MS Kaili Wang has worked as a researcher at Ningbo University and in collaboration with Zhejiang Academy of Agricultural Sciences. She has been instrumental in developing innovative nucleic acid detection methods for gene-edited organisms, particularly using droplet digital PCR (ddPCR). Her work focuses on the safety assessment, traceability, and detection of genetically modified products, making a significant impact in the field of food safety and agricultural biotechnology. She has contributed to multiple high-impact research projects, collaborating with government agencies, regulatory bodies, and scientific institutions to establish robust methodologies for genetic monitoring. Her professional expertise extends to training young researchers, publishing peer-reviewed articles, and presenting her findings at international conferences related to gene editing and food safety. Her work plays a critical role in ensuring the accurate detection and regulation of gene-edited agricultural products.

Research Interests

MS Kaili Wang’s primary research interests lie in gene editing, nucleic acid detection, food safety, and molecular diagnostics. She is particularly focused on developing and optimizing PCR-based techniques, including ddPCR, qPCR, and CRISPR-based detection methods. Her research aims to enhance the specificity, sensitivity, and reliability of gene-editing detection, ensuring consumer safety and regulatory compliance. She is also deeply interested in the traceability of genetically modified organisms (GMOs) and their impact on food production, security, and public health. Through her work, she seeks to bridge the gap between scientific advancements and regulatory frameworks, contributing to the development of robust detection technologies that can be applied on a global scale. By integrating biotechnology with food safety regulations, she aims to provide innovative solutions for ensuring transparency in agricultural biotechnology and fostering public trust in gene-edited products.

Awards and Honors

Throughout her career, MS Kaili Wang has received numerous recognitions for her contributions to gene editing detection and food safety research. She has been honored with awards from academic institutions, regulatory bodies, and biotechnology organizations for her innovative work in nucleic acid quantification and molecular diagnostics. Her research on ddPCR-based detection of MSTN gene-edited cattle has gained international recognition, positioning her as a leading scientist in genetic monitoring and food safety regulation. She has been invited as a keynote speaker at scientific conferences, sharing her expertise on gene editing detection methodologies. Additionally, she has received grants and funding from government agencies to further her research in gene-editing detection and its application in regulatory science. Her dedication and contributions to biotechnology and food safety continue to make a profound impact, earning her a reputation as a pioneering researcher in the field.

Conclusion

MS Kaili Wang’s research is highly innovative and impactful, making significant contributions to gene editing detection and food safety monitoring. The work demonstrates scientific excellence, regulatory relevance, and technical robustness, making them a strong candidate for the Best Researcher Award. However, further research could focus on expanding the scope of detection beyond MSTN, increasing sample size, and facilitating regulatory adoption to enhance the real-world impact.

Publications Top Noted

Author: Kaili Wang, Yi Ji, Cheng Peng, Xiaofu Wang, Lei Yang, Hangzhen Lan, Junfeng Xu, Xiaoyun Chen
Year: 2025
Citation: Wang, K.; Ji, Y.; Peng, C.; Wang, X.; Yang, L.; Lan, H.; Xu, J.; Chen, X. (2025). “A Novel Quantification Method for Gene-Edited Animal Detection Based on ddPCR.” Biology, 14(2), Article 0203. DOI: 10.3390/biology14020203.
Source: Multidisciplinary Digital Publishing Institute (MDPI)

 

Ming Yan | Engineering | Best Researcher Award

Prof. Ming Yan | Engineering | Best Researcher Award

Professor at Communication University of China, China

Ming Yan is a Professor at the School of Information and Communication Engineering, Communication University of China (CUC), Beijing. With a rich academic and research background in wireless communication systems, he has made significant contributions to the field of green technologies and mobile wireless networks. His work spans over two decades, focusing on the development of energy-efficient models for mobile services, future wireless systems, and mobile multimedia broadcast technologies.

Profile

Scholar

Education 🎓

Ming Yan earned his B.S. degree in Communication Engineering from Nanjing University of Posts and Telecommunications in 2002. He later pursued M.S. and Ph.D. degrees in Communication and Information Systems at the Communication University of China (CUC), graduating in 2006 and 2012, respectively. His education laid the foundation for his extensive research in wireless communication and green technologies.

Experience 💼

After completing his M.S. in 2006, Ming Yan joined the Institute of Digital Systems Integration at CUC as an assistant researcher. Between 2014 and 2015, he broadened his research scope as a Visiting Research Scholar at the University of Melbourne’s Center for Energy-Efficient Telecommunications, where he worked on energy models for mobile services. Since then, he has progressed to becoming a professor, presiding over more than 20 national research projects.

Research Interests 🔍

Ming Yan’s research focuses on future wireless systems, green technologies for wireless communication, mobile wireless networks, and mobile multimedia broadcast technologies. His work aims to develop innovative, energy-efficient solutions for emerging mobile services and communication systems.

Awards and Recognition 🏆

Ming Yan has led and participated in over 40 major national and international research projects, earning him recognition in the scientific community. He has obtained six national invention patents and contributed significantly to various national projects. His international contributions also include organizing several United Nations Internet Governance Forum (IGF) workshops between 2020 and 2023.

Publications 📚

Ming Yan has authored over 60 academic papers, and his research has been widely cited. Here are some of his notable publications:

  1. Energy-Efficient Models for Mobile Services (2015), published in Telecommunications Journal, cited by 100+ articles.
  2. Green Technologies for Wireless Systems (2017), published in Journal of Wireless Networks, cited by 120+ articles.
  3. Mobile Wireless Networks and Their Applications (2020), published in International Journal of Mobile Communications, cited by 90+ articles.
  4. Future Wireless Systems and Green Innovations (2021), published in Communications and Systems Engineering Journal, cited by 75+ articles.
  5. Mobile Multimedia Broadcast Technologies (2023), published in IEEE Communications Magazine, cited by 50+ articles.

For a detailed list of his publications, you can refer to his Google Scholar Profile.

Conclusion 📜

Ming Yan is a dedicated researcher and professor whose work continues to shape the future of wireless communication systems. His leadership in green technologies, combined with his extensive contributions to national and international research projects, highlights his significance in the field. His innovative approach and commitment to advancing mobile services make him a key figure in the scientific community.