Salah Mokred | Engineering | Best Researcher Award

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Dr.Salah Mokred | Engineering | Best Researcher Award

PhD Candidate at Southeast university ,China

Salah Mokred is an accomplished electrical engineer and power systems researcher, currently pursuing his Ph.D. in Electrical Engineering at Southeast University, China . With deep expertise in  power system stability, analysis, and planning, he has contributed significantly through high-impact research and international publications . Salah holds a Master’s degree in Electric Power Systems from North China Electric Power University and a Bachelor’s from Sana’a University . He served as a teaching assistant at Sana’a University and has also worked on critical infrastructure projects involving Yemen’s national grid . Known for his commitment to innovation and resilience, Salah combines technical excellence with leadership and collaboration . His work has been recognized with multiple honors and CSC scholarships . Proficient in MATLAB, ETAP, and technical programming , Salah continues to drive forward cutting-edge research in voltage stability and smart grid protection technologies.

Professional Profile

ORCID

GOOGLE SCHOLAR

📘 Education and Experience 

Salah Mokred’s academic path began with a B.Sc. in Electrical Engineering from Sana’a University, Yemen (2009–2013) . He then pursued his M.Sc. in Electric Power Systems at North China Electric Power University (2017–2020) , and is currently finalizing his Ph.D. in Electrical Engineering at Southeast University (2020–2024) . His research focuses on power system stability and voltage collapse prediction . Professionally, he worked as a Teaching Assistant at Sana’a University (2014–2016)  and contributed to Yemen’s national grid security through a project analyzing high-voltage line attacks . Salah also served as an engineering consultant at Garmah Plastic Company in 2016–2017 . His practical experience blends academic excellence with field applications, especially in power grid protection and distribution system enhancement . Salah’s expertise extends to technical tools like MATLAB, ETAP, FORTRAN, and PLC systems .

📈 Professional Development 

Salah Mokred continually expands his professional skills through academic research, international conferences, and specialized training programs . He has completed training in English and programming at SEEDS Education Center , and undertaken advanced technical courses in PLC control, power grid analysis, and power system protection relay selection . Salah has actively participated in IEEE conferences, contributing to papers on voltage stability indices, capacitor bank applications, and intelligent grid technologies . His strong computer proficiency includes MATLAB, ETAP, C, FORTRAN, and MS Office tools . Salah also demonstrates strong leadership, communication, and teamwork skills, enabling him to contribute effectively to multidisciplinary research and collaborative engineering projects . He continues to advance professionally through scholarly publications in top-tier journals (SCI, Q1/Q3) and by collaborating with peers and mentors at Southeast University .

🔬 Research Focus

Salah Mokred’s research is rooted in the domain of Electrical Engineering, particularly in Power Systems . His focus lies in Voltage Stability Assessment, Contingency Ranking, and Optimal Placement of Distributed Generators (DGs) in power grids . Salah develops modern stability indices and collapse prediction methods that support the secure planning and operation of both transmission and distribution systems . His work blends theoretical modeling with real-world applications to improve grid reliability, especially in weak bus identification and dynamic loadability estimation . Salah has also explored series capacitor technologies, smart distribution systems, and intelligent protection schemes using fast-switch devices and relays . His innovative methodologies are helping reshape how engineers evaluate and strengthen power networks in volatile environments. His interdisciplinary approach involves simulation, grid modeling, and data-driven analysis using tools like MATLAB and ETAP .

🏆Awards and Honors 

Salah Mokred’s academic journey has been recognized with multiple prestigious honors . He received the CSC Scholarship twice: once for his Master’s studies (2017) and again for his Ph.D. (2020) in China . From 2021 to 2023, he was awarded Honor Certificates and the Academic Excellence Award by the Embassy of Yemen in recognition of his scholarly performance . Salah was honored with the Excellence Shield from the Yemenis Students Union for his role in academic programs and youth engagement initiatives . He also received a Certificate of Achievement from Garmah Plastic Company in 2017 for his engineering consulting contributions . Additionally, Salah participated in the “Youth in Nanjing” cultural exchange and was recognized for his contributions to international student engagement and creativity through events like “Star-Moon Dream Night” . These accolades highlight both his technical acumen and active involvement in cross-cultural academic life.

Publication of Top Notes

1.Title: Modern voltage stability index for prediction of voltage collapse and estimation of maximum loadability for weak buses and critical lines identification

Authors: S. Mokred, Y. Wang, T. Chen
Journal: International Journal of Electrical Power & Energy Systems
Year: 2023
Citations: 58

2.Title: A novel collapse prediction index for voltage stability analysis and contingency ranking in power systems

Authors: S. Mokred, Y. Wang, T. Chen
Journal: Protection and Control of Modern Power Systems
Year: 2023
Citations: 44

3.Title: Voltage stability assessment and contingency ranking in power systems based on modern stability assessment index

Authors: S. Mokred, Y. Wang
Journal: Results in Engineering
Year: 2024
Citations: 14

4.Title: Comparison of the effect of series and shunt capacitor application in 25kV radial power distribution network

Authors: S. Mokred, Q. Lijun, G. Kamara, T. Khan
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 10

5.Title: Protection performance during application of an intelligent and fast switch series capacitor to 25kV radial power distribution network

Authors: S. Mokred, Q. Lijun, T. Khan
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 8

6.Title: Transient and protection performance of a fixed series compensated 500 kV transmission line during various types of faulty conditions

Authors: S. Mokred, Q. Lijun, T. Khan
Journal: Journal of Electrical Engineering & Technology
Year: 2021
Citations: 7

7.Title: Voltage stability estimation for complex power system based on modal analytical techniques

Authors: M.M.A. Seedahmed, S.A.S. Mokred, G. Kamara
Conference: IEEE SPIN Conference
Year: 2019
Citations: 7

8.Title: Smart design of distribution series capacitor bank application for improved voltage quality and motor start

Authors: S. Mokred, Q. Lijun, G. Kamara
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 6

9.Title: Protection and Impact of Series Compensation Technology in High Voltage Transmission Line

Authors: S.A.S. Mokred, Q. Lijun, M. Ali
Journal: IJIEEE
Year: 2019
Citations: 3

10.Title: A Novel Approach for Voltage Stability Assessment and Optimal Siting and Sizing of DGs in Radial Power Distribution Networks

Authors: S. Mokred, Y. Wang, M. Alruwaili, M.A. Ibrahim
Journal: Processes
Year: 2025
Citations: Not yet available

Conclusion

Dr. Salah Mokred’s consistent academic excellence, strong citation record, impactful contributions to voltage stability and grid protection, and participation in IEEE conferences and journal leadership make him a standout candidate for the Best Researcher Award. His research not only advances theory but provides applicable solutions to power system challenges in both developing and developed countries.

Prof . Len Gelman | Artificial Intelligence | Best Researcher Award

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Prof . Len Gelman | Artificial Intelligence | Best Researcher Award

Prof. Len Gelman , University of Huddersfield , United Kingdom

Professor Len Gelman 🇬🇧 is a globally recognized expert in signal processing and condition monitoring 🔍. He currently serves as Chair Professor and Director at the University of Huddersfield 🏫. With over two decades of academic leadership, he has significantly contributed to vibro-acoustics and non-destructive testing 🔧. A Fellow of multiple prestigious organizations 🌐, Prof. Gelman’s international collaborations span across Europe, Asia, and the USA 🌏. His innovations have advanced aerospace and medical diagnostics ✈️🧬. He continues to lead global initiatives and research committees, shaping the future of engineering diagnostics and reliability technologies 🔬🛠️.

Professional Profile

SCOPUS

Education and Experience 

Prof. Len Gelman holds a PhD and Doctor of Science (Habilitation) 🎓, with BSc (Hons) and MSc (Hons) degrees in engineering 📘. He is a British citizen 🇬🇧. Since 2017, he has been a Professor and Chair at the University of Huddersfield 🏛️. Prior to that, he served at Cranfield University (2002–2017) as Chair in Vibro-Acoustical Monitoring 🔊. His distinguished academic journey includes visiting professorships in China 🇨🇳, Denmark 🇩🇰, Poland 🇵🇱, Spain 🇪🇸, Italy 🇮🇹, and the USA 🇺🇸. Prof. Gelman combines deep technical expertise with global educational outreach 🌍👨‍🏫.

Professional Development 

Prof. Gelman has held key international leadership roles including Chair of the International Scientific Committee of the Condition Monitoring Society 🌐. He is a Fellow of BINDT, IAENG, IDE, and HEA 🎖️, and an Academician of the Academy of Sciences of Applied Radio Electronics 🧠. He chairs award and honors committees for top acoustics and vibration institutions 🏅. As Visiting Professor at Tsinghua, Jiao Tong, and Aalborg Universities, among others 🎓, he mentors emerging researchers globally 🌎. Prof. Gelman’s commitment to professional excellence shapes the advancement of diagnostic technologies and engineering education 📈🔧.

Research Focus 

Prof. Gelman’s research focuses on signal processing, vibro-acoustics, and condition monitoring of engineering systems 🔍🔊. His work spans non-destructive testing (NDT), fault diagnostics, and performance optimization in sectors such as aerospace, healthcare, and manufacturing ✈️🏥🏭. He develops advanced algorithms for fault detection and predictive maintenance using machine learning and big data 🧠📊. His interdisciplinary approach benefits both industry and academia 🌐🔬. Prof. Gelman also pioneers applications in medical diagnostics and intelligent systems for real-time monitoring 🧬⚙️. His innovations contribute to safer, more efficient engineering systems across global platforms 🌍🚀.

Awards and Honors 

Prof. Gelman has received numerous prestigious awards for innovation and research excellence 🏅. These include the Rolls-Royce Innovation Award (2012, 2019) ✈️, William Sweet Smith Prize by IMechE 🛠️, and COMADIT Prize by BINDT for impactful contributions to condition monitoring 🧲. He also received Best Paper Awards at CM/MFPT conferences 📄 and recognition from the USA Navy and Acoustical Society of America 🇺🇸🔊. His European and UK fellowships support cutting-edge human capital projects 🧠🇪🇺. He has chaired international committees in NDT and acoustics, continuing to shape future technologies through global leadership and innovation 🌐👨‍🔬.

Publication Top Notes

1. Vibration Analysis of Rotating Porous Functionally Graded Material Beams Using Exact Formulation

  • Citation: Amoozgar, M.R., & Gelman, L.M. (2022). Vibration analysis of rotating porous functionally graded material beams using exact formulation. Journal of Vibration and Control, 28(21–22), 3195–3206. https://doi.org/10.1177/10775463211027883Nottingham Repository+1SAGE Journals+1

  • Summary: This study investigates the free vibration behavior of rotating functionally graded material (FGM) beams with porosity, employing geometrically exact fully intrinsic beam equations. The research considers both even and uneven porosity distributions to simulate manufacturing imperfections. Findings reveal that material gradation and porosity significantly influence natural frequencies and mode shapes, emphasizing the necessity of accounting for these factors in the design and analysis of rotating FGM structures. Huddersfield Research Portal+2SAGE Journals+2Nottingham Repository+2

2. Vibration Health Monitoring of Rolling Bearings Under Variable Speed Conditions by Novel Demodulation Technique

  • Citation: Zhao, D., Gelman, L.M., Chu, F., & Ball, A.D. (2021). Vibration health monitoring of rolling bearings under variable speed conditions by novel demodulation technique. Structural Control and Health Monitoring, 28(2), e2672. https://doi.org/10.1002/stc.2672Wiley Online Library

  • Summary: Addressing the challenges of diagnosing rolling bearing faults under variable speed conditions, this paper introduces an optimization-based demodulation transform method. The technique effectively estimates fault characteristic frequencies with weak amplitudes and adapts to time-varying rotational speeds. Validation through simulations and experimental data demonstrates the method’s superior diagnostic capabilities compared to existing approaches. Huddersfield Research Portal+1Wiley Online Library+1

3. Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions

  • Citation: Zhao, D., Gelman, L.M., Chu, F., & Ball, A.D. (2020). Novel method for vibration sensor-based instantaneous defect frequency estimation for rolling bearings under non-stationary conditions. Sensors, 20(18), 5201. https://doi.org/10.3390/s20185201MDPI

  • Summary: This research presents a novel approach for estimating instantaneous defect frequencies in rolling bearings operating under non-stationary conditions. Utilizing vibration sensor data, the method enhances the accuracy of defect frequency estimation, facilitating improved fault diagnosis in dynamic operational environments. MDPI

4. Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing

  • Citation: Ciszewski, T., Gelman, L.M., & Ball, A.D. (2020). Novel fault identification for electromechanical systems via spectral technique and electrical data processing. Electronics, 9(10), 1560. https://doi.org/10.3390/electronics9101560MDPI

  • Summary: This paper introduces an innovative method for fault identification in electromechanical systems by integrating spectral analysis with electrical data processing. The approach enhances the detection and diagnosis of faults, contributing to the reliability and efficiency of electromechanical system operations. MDPI

5. Novel Prediction of Diagnosis Effectiveness for Adaptation of the Spectral Kurtosis Technology to Varying Operating Conditions

  • Citation: Kolbe, S., Gelman, L.M., & Ball, A.D. (2021). Novel prediction of diagnosis effectiveness for adaptation of the spectral kurtosis technology to varying operating conditions. Sensors, 21(20), 6913. https://doi.org/10.3390/s21206913PMC

  • Summary: This study proposes two novel consistency vectors combined with machine learning algorithms to adapt spectral kurtosis technology for optimal gearbox damage diagnosis under varying operating conditions. The approach enables computationally efficient online condition monitoring by predicting diagnosis effectiveness, thereby improving maintenance strategies.

Conclusion

Professor Len Gelman exemplifies the ideal candidate for the Best Researcher Award due to his groundbreaking contributions to condition monitoring, signal processing, and diagnostic technologies. His work not only advances academic knowledge but also addresses critical industry challenges in aerospace, healthcare, and manufacturing. With a sustained record of high-impact research, international leadership, and technological innovation, he stands out as a world-class researcher whose work continues to benefit both academia and society.