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

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

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)

Akeem Kareem | Mechanical Engineering | Best Researcher Award

Akeem Kareem | Mechanical Engineering | Best Researcher Award

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

Publication profile

Orcid

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)