Liyun Li | Seismic Analysis | Best Researcher Award

Published on 08/03/202508/03/2025 by ScienceFather

Liyun Li | Seismic Analysis | Best Researcher Award

Prof. Liyun Li, Beijing University of Technology, China.

Professor Liyun Li is a distinguished scholar in Civil Engineering at Beijing University of Technology (BJUT), specializing in seismic analysis, underground construction, and geotechnical engineering. With a Ph.D. from Beijing University of Technology, he has contributed significantly to soil-structure interaction and slope protection. His expertise spans over 25 years, including research visits to the University of Pittsburgh, USA. As a member of SSC, ISSMGE, and CISMGE, he actively advances geotechnical engineering. His research has greatly impacted earthquake resilience and underground infrastructure, making him a leading figure in structural and geotechnical studies. 🌍🔬

Publication Profile

Orcid

Education & Experience

📚 Education:
✔ 2003–2007: Ph.D. in Civil Engineering, Beijing University of Technology
✔ 2001–2003: M.Sc., Institute of Engineering Mechanics, China Earthquake Administration
✔ 1992–1996: B.Sc., East China Institute of Technology

🔬 Professional Experience:
✔ 2021–Present: Professor, College of Architecture & Civil Engineering, BJUT
✔ 2013–2014: Visiting Scholar, University of Pittsburgh, USA
✔ 2007–2021: Associate Professor, College of Architecture & Civil Engineering, BJUT
✔ 1996–2001: Assistant Professor, Dept. of Geo-science, East China Institute of Technology

Suitability Summary

Professor LI Liyun, a distinguished expert in Civil Engineering, is a highly deserving recipient of the Best Researcher Award for his outstanding contributions to seismic analysis, underground engineering, and geotechnical research. As a Professor at Beijing University of Technology, his work has significantly advanced the understanding of soil-structure interaction, underground construction, and slope protection techniques. With a strong academic foundation and over two decades of research experience, Professor Li’s studies have provided critical insights into seismic safety, structural resilience, and ecological reconstruction, directly benefiting both academia and industry.

Professional Development

Professor Liyun Li is an esteemed expert in civil and geotechnical engineering, with a career dedicated to earthquake-resistant underground structures. His research focuses on seismic resilience, soil-structure interaction, and slope protection, contributing to safer and more sustainable infrastructure. As a visiting scholar at the University of Pittsburgh, he collaborated on advanced geotechnical modeling. His 25+ years of teaching and research have influenced numerous engineering projects in China and beyond. His active participation in international engineering societies ensures that his work aligns with global advancements in geotechnical engineering and underground construction. 🏗️🔬🌍

Research Focus

Professor Liyun Li specializes in seismic analysis of underground structures, ensuring that critical infrastructure can withstand earthquakes and natural disasters. His work explores soil-structure interaction, essential for designing resilient tunnels, foundations, and underground facilities. He is also deeply involved in slope protection and ecological reconstruction, integrating sustainability into geotechnical solutions. His research supports urban development, disaster mitigation, and infrastructure resilience, making significant contributions to civil and earthquake engineering. Through international collaborations, he advances new construction methodologies that enhance structural safety and environmental sustainability. 🌍🏢🌱

Awards & Honors 🏆

✔ Recognized Expert in Seismic & Underground Engineering 🏗️
✔ Visiting Scholar at University of Pittsburgh, USA 🌍
✔ Key Contributor to China’s National Geotechnical Projects 🏢
✔ Active Member of SSC, ISSMGE & CISMGE 🏅
✔ Multiple Teaching & Research Excellence Awards at BJUT 📚

Publication Top Notes

Investigation on Response of Site of Typical Soil–Rock Composite Strata in Changchun Induced by Shield Construction of Parallel Twin Tunnels, Applied Sciences, 2024.

A Data-Driven Indirect Approach for Predicting the Response of Existing Structures Induced by Adjacent Excavation, Applied Sciences, 2023.

Cheng-Wei Fei | Design of Materials and Components | Best Researcher Award

Published on 25/01/202525/01/2025 by ScienceFather

Prof. Dr. Cheng-Wei Fei | Design of Materials and Components | Best Researcher Award

Professor at Fudan University, China

Prof. Dr. Cheng-Wei Fei is a distinguished academic and researcher specializing in aerospace engineering, particularly in aeroengine structural strength and reliability. He is currently a Professor at Fudan University, with prior experience as a Research Fellow at Hong Kong University of Science and Technology and as a Postdoctoral Fellow at Hong Kong Polytechnic University. With a Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University, Prof. Fei has published over 130 SCI-indexed papers and authored six books. His research contributions, including 15 patents, focus on AI-driven advancements in aircraft health management and reliability, directly supporting key national projects like the C919 and CJ-1000 aircraft. He is an active leader in the academic community, serving as an editor for several prominent journals and holding multiple leadership roles in aerospace societies. Prof. Fei’s work bridges fundamental science and practical applications, positioning him as a key figure in aerospace research and development.

Professional Profile

Education

Prof. Dr. Cheng-Wei Fei has a strong academic foundation in aerospace engineering. He earned his Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University in 2014, following a Master’s degree in the same field from Shenyang Aerospace University in 2010. His undergraduate studies were in Electrical Engineering and Automation, which he completed at Fujian University of Technology in 2007. Throughout his academic journey, Prof. Fei has continually sought to advance his knowledge, first as a student and later as a researcher and educator. His rigorous education laid the groundwork for his future contributions to aerospace science, particularly in the areas of aeroengine reliability, AI applications in aerospace, and advanced propulsion technologies. Prof. Fei’s ongoing commitment to academic excellence is reflected in his long-standing position as a Professor at Fudan University, where he continues to push the boundaries of aerospace research.

Professional Experience

Prof. Dr. Cheng-Wei Fei has extensive professional experience in both academic and research settings. He currently serves as a professor in the Department of Mechanical Engineering, specializing in the design and analysis of materials and components. Throughout his career, Dr. Fei has been involved in numerous high-impact research projects related to structural reliability, materials behavior, and dynamic system modeling. His expertise spans computational mechanics, dynamic modeling of structures, and advanced materials design, with a focus on integrating multi-physics approaches for solving real-world engineering problems. Dr. Fei has also contributed significantly to the advancement of reliability-based design optimization and surrogate modeling strategies. He has collaborated with industry partners and government organizations, applying his research to practical challenges in the aerospace, automotive, and energy sectors. With over 100 peer-reviewed publications, Dr. Fei is a leading figure in his field, recognized for his contributions to engineering design and innovation.

Research Interest

Prof. Dr. Cheng-Wei Fei’s research interests are centered around aerospace propulsion, structural strength, and reliability, with a particular focus on integrating artificial intelligence (AI) into aerospace systems. He has made significant contributions to the development of new theories and methodologies, such as information fusion fault diagnosis, dynamic assembly reliability design, and intelligent reliability design for aeroengines and aircraft. His research aims to address critical challenges in aircraft health management, intelligent operation and maintenance, and the overall reliability of aerospace technologies. Prof. Fei’s work supports the development of key national aerospace projects, including China’s C919 and CJ-1000 aircraft, as well as advanced aeroengines. He is deeply involved in applying AI and advanced engineering models to improve the performance and safety of aerospace systems, with his research outcomes directly influencing the design and operational efficiency of modern aircraft and engines. His interdisciplinary approach blends aerospace engineering with cutting-edge AI techniques, pushing the boundaries of innovation in the field.

Award and Honor

Prof. Dr. Cheng-Wei Fei has received numerous accolades for his exceptional contributions to aerospace engineering and research. He has been recognized for his groundbreaking work in aeroengine reliability, AI integration, and aerospace health management, which has significantly impacted national aerospace projects like the C919 and CJ-1000 aircraft. As an academic leader, Prof. Fei holds prestigious editorial positions in renowned journals, including Shock and Vibration, Aerospace, and Mechanical Design. He has also been invited as a session chair at major international conferences, such as AAME 2024 and ISAES 2024, further underscoring his global reputation. In addition to his academic achievements, Prof. Fei is actively involved in professional societies, holding leadership roles such as Vice Chairman of the National Committee of Experts on Aerospace Materials and Deputy Director of the Aeronautical Power Professional Committee of Shanghai Aeronautical Society. These honors reflect his significant influence and leadership in the aerospace research community.

Conclusion

Prof. Dr. Cheng-Wei Fei is highly suitable for the Best Researcher Award. His extensive research output, leadership roles, significant contributions to national aerospace projects, and strong academic background make him an outstanding candidate. Addressing the noted areas for improvement, particularly by broadening his research scope and emphasizing global impact, could further enhance his qualifications for international recognition.

Publications Top Noted

Title: Improved Kriging with extremum response surface method for structural dynamic reliability and sensitivity analyses
Authors: C Lu, YW Feng, RP Liem, CW Fei
Year: 2018
Citations: 108
Title: Fusion information entropy method of rolling bearing fault diagnosis based on n-dimensional characteristic parameter distance
Authors: YT Ai, JY Guan, CW Fei, J Tian, FL Zhang
Year: 2017
Citations: 102
Title: LSTM-based multi-layer self-attention method for remaining useful life estimation of mechanical systems
Authors: J Xia, Y Feng, C Lu, C Fei, X Xue
Year: 2021
Citations: 100
Title: Moving extremum surrogate modeling strategy for dynamic reliability estimation of turbine blisk with multi-physics fields
Authors: C Lu, CW Fei, HT Liu, H Li, LQ An
Year: 2020
Citations: 98
Title: Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression
Authors: LK Song, GC Bai, CW Fei
Year: 2019
Citations: 84
Title: Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes
Authors: LK Song, CW Fei, J Wen, GC Bai
Year: 2017
Citations: 81
Title: Improved decomposed-coordinated kriging modeling strategy for dynamic probabilistic analysis of multicomponent structures
Authors: C Lu, YW Feng, CW Fei, SQ Bu
Year: 2019
Citations: 80
Title: Multi-extremum-modified response basis model for nonlinear response prediction of dynamic turbine blisk
Authors: B Keshtegar, M Bagheri, CW Fei, C Lu, O Taylan, DK Thai
Year: 2021
Citations: 78
Title: Reliability-based low-cycle fatigue damage analysis for turbine blade with thermo-structural interaction
Authors: H Gao, C Fei, G Bai, L Ding
Year: 2016
Citations: 77
Title: Probabilistic analyses of structural dynamic response with modified Kriging-based moving extremum framework
Authors: C Lu, CW Fei, YW Feng, YJ Zhao, XW Dong, YS Choy
Year: 2021
Citations: 76
Title: Enhanced network learning model with intelligent operator for the motion reliability evaluation of flexible mechanism
Authors: CW Fei, H Li, HT Liu, C Lu, LQ An, L Han, YJ Zhao
Year: 2020
Citations: 73
Title: Multilevel nested reliability-based design optimization with hybrid intelligent regression for operating assembly relationship
Authors: CW Fei, H Li, HT Liu, C Lu, B Keshtegar, LQ An
Year: 2020
Citations: 73

Giuseppe Prenesti | Chemical Engineering | Best Scholar Award

Published on 26/11/202426/11/2024 by ScienceFather

Giuseppe Prenesti | Chemical Engineering | Best Scholar Award

Mr. Giuseppe Prenesti, University of Calabria, Italy.

Giuseppe Prenesti is an Italian researcher and Ph.D. student in Chemical Engineering at the University of Calabria 🇮🇹, specializing in lithium recovery from batteries through membrane processes. With a solid academic foundation, including a Master’s degree in Chemical Engineering 🧪 and international experience via Erasmus+ in Spain 🇪🇸, Giuseppe has cultivated expertise in hydrogen purification and renewable energy technologies. As a tutor and teaching assistant, he actively contributes to academic excellence, while his innovative research is featured in leading journals. Passionate about sustainable energy and advanced materials, Giuseppe is shaping the future of chemical engineering. 🌍📚

Publication profile

Scopus

Education and Experience

Ph.D. Student in Chemical Engineering, University of Calabria (2023–present)
Excellence Track Researcher, University of Calabria (2022)
Master’s Degree in Chemical Engineering, University of Calabria (2020–2022)
Erasmus+ Trainee, Universidad Rey Juan Carlos, Madrid (2022)
Bachelor’s Degree in Environmental and Chemical Engineering, University of Calabria (2017–2020)
Teaching Assistant for Equipment for Solids Treatment, University of Calabria (2023–present)
Tutor for Chemical and Biochemical Reactors, University of Calabria (2023–present)
Mathematics Tutor, University of Calabria (2023)
Trainee, Caffo S.R.L, focusing on distillation processes (2019–2020)

Suitability For The Award

Mr. Giuseppe Prenesti is a highly deserving candidate for the Best Scholar Award due to his exceptional academic achievements, impressive research contributions, and active involvement in advancing the field of Chemical Engineering. His dedication to academic excellence, innovative research, and passion for teaching make him an outstanding scholar with a promising future in academia and industry.

Professional Development

Giuseppe Prenesti is actively enhancing his skills in advanced chemical engineering technologies . He excels in simulation software like MATLAB and UniSim, vital for process optimization and membrane technology research. His expertise spans CFD simulation, hydrogen purification, and anisotropic materials . Giuseppe has participated in renowned schools, such as the EMS Summer School and Gricu Winter School , solidifying his foundation in renewable energy technologies and advanced materials. Through continuous learning and international collaborations, Giuseppe is committed to developing sustainable solutions for the chemical engineering industry while maintaining his passion for innovation.

Research Focus

Giuseppe Prenesti’s research is centered on sustainable energy and advanced material technologies . As a Ph.D. student, he focuses on lithium recovery from exhausted batteries through membrane processes , addressing critical challenges in renewable energy storage. His expertise includes hydrogen purification through Pd-based membranes and computational simulations . Giuseppe’s research interests extend to catalytic efficiency, CO2 adsorption in zeolites , and temperature optimization in reactors . With a passion for sustainable engineering and innovation, his work contributes to the advancement of cleaner, more efficient technologies for a greener future.

Awards and Honors

MS/Ph.D. Students Award – EMS Euromembrane 2024 (06/06/2024)
EMS Summer School – Participant (2023 & 2024)
Gricu Winter School – Participant (2024)

Publications

Three-Dimensional Morphological Study of MnTe-like Structures by Assessment of Tortuosity Tensor Using Computational Fluid Dynamics – 2024, 0 citations .
Optimal permeance ratio, flux direction and layer distribution in composite asymmetric membranes composed of sequences of layers obeying real-power flux laws – 2024, 1 citation .
H2 and CO purification by CO2 removal from syngas coupling membrane module and water-absorption unit: An economic analysis – 2024, 0 citations .
Evaluation of CO2 Adsorption Parameters in Fluidised Zeolite 13X Beds Using Non-Linear Multivariate Optimisation – 2023, 1 citation .
Effect of flux direction through supported metal membranes: Golden ratio as maximum benefit in pure hydrogen and concept of swap point in mixture – 2023, 1 citation .
Assessment of effectiveness factor in porous catalysts under non-symmetric external conditions of concentration – 2023, 1 citation .
Optimization of temperature distribution in the novel power-to-heat matrix-in-batch OnePot© reactor – 2022, 2 citations .

Akeem Kareem | Mechanical Engineering | Best Researcher Award

Published on 22/11/202422/11/2024 by ScienceFather

Akeem Kareem | Mechanical Engineering | Best Researcher Award

Mr. Akeem Kareem, Kumoh National Institute of Technology, South Korea.

Akeem Kareem, MNSE, MIAENG, is a dynamic researcher and engineer specializing in R&D on Digital Twin, Metaverse (VR & AR), and Prognostics and Health Management (PHM). Currently pursuing a Doctor of Science in Mechanical Engineering at Kumoh National Institute of Technology, South Korea, he brings extensive expertise in data-driven AI processes and 3D animation. With professional stints in mechanical engineering, facilities management, and data science, Akeem combines technical precision with a passion for innovation. His multilingual fluency in Yoruba and English, certifications in Machine Learning, and published works highlight his commitment to leveraging technology for groundbreaking solutions.

Publication profile

Orcid

Education

Doctor of Science, Mechanical Engineering – Kumoh National Institute of Technology (2023–2026)
Masters, Mechanical Engineering – Kumoh National Institute of Technology (2021–2023)
BEng, Mechanical Engineering (Thermofluid Option) – University of Ilorin, Nigeria (2013–2017)
OND, Mechanical Engineering – Kwara State Polytechnic, Nigeria (2009–2011)

Experience

Research and Development Specialist – FD&P (2023–Present)
Graduate Research Assistant – Kumoh National Institute of Technology (2021–2023)
Lead Project Manager (Facilities) – James Cubitt Facilities Managers (2018–2021)
Graduate Mechanical Engineer – Dangote Group (2012–2013)
Automotive Technician – CFAO CICA Nig Limited (2011–2012)

Suitability For The Award

Mr. Akeem Kareem is a strong candidate for the Best Researcher Award, showcasing a multidisciplinary expertise in semiconductor engineering, data-driven processes, and mechanical systems. His innovative contributions span Digital Twins, Metaverse technologies, reinforcement learning, and predictive health monitoring (PHM). With an impressive academic and professional track record, including publications in advanced areas of fault diagnostics and computational analysis, Mr. Kareem demonstrates exceptional research acumen and industry impact.

Professional Development

Akeem Kareem is dedicated to professional growth, showcasing expertise in machine learning, electromechanical engineering, and data science. With certifications in Machine Learning with Python, Introduction to Data Science, and Electromechanical Engineering, he bridges engineering solutions with data-driven insights. Akeem actively contributes to publications in AI-based diagnostics, leveraging supervised learning and FEA assessments. His proficiency in developing robust AI frameworks and commitment to continuous learning position him as a catalyst for innovative solutions in engineering, digital twin technology, and AR/VR applications.

Research Focus

Akeem Kareem’s research emphasizes advanced engineering systems integrating Digital Twin, Metaverse technologies (VR & AR), and Prognostics and Health Management (PHM). His expertise lies in developing data-driven fault diagnostics, reliability enhancement for electronic components, and AI-powered frameworks for autonomous systems. With a focus on machine learning and reinforcement deep learning, he seeks to revolutionize industries through predictive analytics and system optimization. By combining academic rigor with real-world applications, Akeem is driving innovation at the intersection of engineering and digital transformation.

Awards and Honors

Certified Graduate Mechanical Engineer – Dangote Group
Recognized for contributions to facilities management – James Cubitt Facilities Managers
Multiple publications in AI and diagnostics frameworks
Certifications in Machine Learning, Electromechanical Engineering, and Data Science
Research contributions to enhancing AI reliability in harsh environments

Publications

“A Comparative Data Augmentation-Assisted Diagnostic Framework for Industrial Centrifugal Pumps”
“A Comparative Study of Deep-Learning Autoencoders (DLAEs) for Vibration Anomaly Detection in Manufacturing Equipment”
“Enhancing Transformer Core Fault Diagnosis and Classification through Hilbert Transform Analysis of Electric Current Signals”
“Transformer Core Fault Diagnosis via Current Signal Analysis with Pearson Correlation Feature Selection”
“Hyperelastic and Stacked Ensemble-Driven Predictive Modeling of PEMFC Gaskets Under Thermal and Chemical Aging”
“Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps”
“ANN-based Reliability Enhancement of SMPS Aluminium Electrolytic Capacitors in Cold Environments” (2023)
“ANN-Based Reliability Enhancement of SMPS Aluminum Electrolytic Capacitors in Cold Environments” (2023)

jili Qu | Geotechnical Engineering | Best Researcher Award

Published on 12/11/202412/11/2024 by ScienceFather

jili Qu | Geotechnical Engineering | Best Researcher Award

Prof. jili Qu, Kashgar University, China.

Qu Jili is a seasoned professor specializing in geotechnical engineering at East China Normal University. With extensive experience in civil engineering, he has made notable contributions to soil stabilization and sustainable infrastructure. Prof. Qu earned his Ph.D. from Tongji University and has since led numerous research projects focused on microbial mineralization, soil corrosion resistance, and eco-friendly construction methods . As a faculty member at Kashgar University, he plays a pivotal role in advancing resilient engineering practices and environmental research. Widely recognized for his innovative work, Prof. Qu has received multiple awards for excellence in teaching and research .

Publication profile

Scopus

Education and Experience

Ph.D. in Underground Engineering, Tongji University, Shanghai, 2002
M.Sc. in Engineering Geology, Nanjing University, Shanghai, 1993
B.Eng. in Hydrogeology and Engineering Geology, Guilin University of Technology, Shanghai, 1985
Professor, School of Civil Engineering, Kashgar University, 2021-present
Associate Professor, University of Shanghai for Science and Technology, 2005-2021
Postdoctoral Fellow, Civil Engineering, Shanghai Jiao Tong University, 2002-2005

Suitability For The Award

Dr. Qu Jili appears to be a highly suitable candidate for the Best Researcher Award, given his exceptional contributions to the fields of geotechnical engineering and environmental sustainability. His research on soil mechanics, microbial solidification, and the durability of soil materials has had a significant impact on both academic and practical applications.

Professional Development

Qu Jili’s professional journey reflects his commitment to advancing geotechnical engineering and sustainable infrastructure . Over the years, he has spearheaded pioneering research on microbial soil reinforcement, long-term weathering resistance, and corrosion-resistant soil stabilization. His work addresses key challenges in civil engineering, particularly the environmental impact of geotechnical practices and sustainable construction techniques. Prof. Qu has hosted multiple high-impact research projects funded by national and provincial agencies . Through his research and academic leadership, he contributes to innovations in civil engineering, supporting resilient and eco-friendly infrastructure development.

Research Focus

Prof. Qu Jili’s research centers on environmental and geotechnical resilience . His work on microbial mineralization and soil stabilization offers sustainable solutions to issues like soil erosion and dust control in arid regions . A significant aspect of his research investigates the durability and corrosion resistance of bio-reinforced soils, which are critical for long-term infrastructure stability. His projects also explore the use of organic and green materials in soil modification for ecological applications . Through innovative methodologies, he aims to advance sustainable engineering practices that prioritize environmental health alongside infrastructure development .

Awards and Honors

Excellent Teacher, University of Shanghai for Science and Technology, 2020
Reading Star, University of Shanghai for Science and Technology, 2020
Second Prize Nomination, Shanghai Natural Science Award, 2020
First Prize in Engineering Practice Innovation, University of Shanghai for Science and Technology, 2017
Outstanding Instructor, Summer Social Practice, University of Shanghai for Science and Technology, 2012
Third Prize, CABR Cup, Huaxia Construction Science and Technology, 2011
Second Prize, Shanghai Teaching Achievements, Shanghai Education Commission, 2010
Excellent Head Teacher, School of Environment and Architecture, 2009

Publications

Enhancing Aeolian Sand Stability Using Microbially Induced Calcite Precipitation Technology – Scientific Reports, 2024, 14(1), 23876 (Cited by: 0)
Roles of Corn Starch and Gellan Gum in Changing Unconfined Compressive Strength of Shanghai Alluvial Clay – Science and Engineering of Composite Materials, 2024, 31(1), 20240002 (Cited by: 1)
Geotechnical Properties of Yellow Silty Sand Soil Modified by Bio-Stimulation with Presence of NiCl2 – IOP Conference Series: Earth and Environmental Science, 2021, 938(1), 012001 (Cited by: 0)
Using the Tape Extensometer for Possibilities of Landslide Monitoring or Other Purposes – IOP Conference Series: Earth and Environmental Science, 2021, 906(1), 012026 (Cited by: 0)
Research on the Effect of Urease on Energy Absorption in Shanghai Clay by Unconfined Compressive Test – IOP Conference Series: Earth and Environmental Science, 2021, 719(4), 042060 (Cited by: 0)
Roes of Curing Conditions on Properties of Soil Reinforced with Palm Fiber and Lime – Emerging Materials Research, 2021, 10(1), pp. 90–102 (Cited by: 1)
Function of Palm Fiber in Stabilization of Alluvial Clayey Soil in Yangtze River Estuary – Journal of Renewable Materials, 2021, 9(4), pp. 767–787 (Cited by: 20)
Strength and Deformation Behavior of Shanghai Andesite Under Various Strain Rates in Uniaxial Loading Test – Geomechanics and Geoengineering, 2021, 16(1), pp. 44–51 (Cited by: 0)
Comparison of Secondary Crushing Operations Through Cone and Horizontal Shaft Impact Crushers – SGEM International Multidisciplinary Scientific GeoConference, 2020 (Cited by: 2)

Prof. Liyun Li, Beijing University of Technology, China.

Publication Profile

Education & Experience

Suitability Summary

Professional Development

Research Focus

Awards & Honors 🏆

Publication Top Notes

Education

Professional Experience

Research Interest

Award and Honor

Conclusion

Publications Top Noted

Mr. Giuseppe Prenesti, University of Calabria, Italy.

Publication profile

Education and Experience

Suitability For The Award

Professional Development

Research Focus

Awards and Honors

Publications

Mr. Akeem Kareem, Kumoh National Institute of Technology, South Korea.

Publication profile

Education

Experience

Suitability For The Award

Professional Development

Research Focus

Awards and Honors

Publications

“A Comparative Data Augmentation-Assisted Diagnostic Framework for Industrial Centrifugal Pumps”

“A Comparative Study of Deep-Learning Autoencoders (DLAEs) for Vibration Anomaly Detection in Manufacturing Equipment”

“Enhancing Transformer Core Fault Diagnosis and Classification through Hilbert Transform Analysis of Electric Current Signals”

“Transformer Core Fault Diagnosis via Current Signal Analysis with Pearson Correlation Feature Selection”

“Hyperelastic and Stacked Ensemble-Driven Predictive Modeling of PEMFC Gaskets Under Thermal and Chemical Aging”

“Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps”

“ANN-based Reliability Enhancement of SMPS Aluminium Electrolytic Capacitors in Cold Environments” (2023)

“ANN-Based Reliability Enhancement of SMPS Aluminum Electrolytic Capacitors in Cold Environments” (2023)

Prof. jili Qu, Kashgar University, China.

Publication profile

Education and Experience

Suitability For The Award

Professional Development

Research Focus

Awards and Honors

Publications