Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

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Mr. Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

King Fahd University of Petroleum and Minerals | Saudi Arabia

Ibrahim Khalil Kabir is a control and robotics researcher working at the intersection of control theory and artificial intelligence, with a strong focus on learning-based robotics, socially aware navigation, and human–robot interaction. He holds an MSc in Systems and Control Engineering and a BEng in Mechatronics Engineering, with a solid academic record and advanced training in autonomous systems. His research experience spans graduate teaching and research assistantships, where he contributed to robot path planning, navigation, and hands-on laboratory instruction using real robotic platforms. His scholarly output includes peer-reviewed journal and conference publications covering UAV control, mobile robot navigation, deep reinforcement learning, and socially aware robotic systems. According to Google Scholar, his research profile reflects an emerging h-index supported by multiple indexed documents and a steadily growing citation count, indicating increasing impact in robotics and intelligent control research. His work has appeared in reputable venues such as IEEE Access, Machine Learning and Knowledge Extraction, and IEEE conferences. He has received several academic honors, including national merit scholarships and highest GPA awards. Overall, his research trajectory demonstrates a strong foundation and growing influence in intelligent robotics, positioning him well for advanced doctoral research in learning-enabled autonomous systems.

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Ganiyat Salawu | Engineering and Technology | Research Excellence Award

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Dr. Ganiyat Salawu | Engineering and Technology | Research Excellence Award

University of KwaZulu-Natal,Durban | South Africa

Dr. Ganiyat Abiodun Salawu is a mechanical and mechatronics engineer and researcher with strong expertise in advanced manufacturing systems, robotics, renewable energy technologies, and intelligent engineering solutions. She holds a PhD in Mechanical Engineering (Mechatronics and Robotics) from the University of KwaZulu-Natal, South Africa, following earlier degrees in mechanical engineering and education from Nigerian institutions. Her academic and professional career spans lecturing, postgraduate supervision, research coordination, and postdoctoral research, with extensive experience in both university and polytechnic systems. Her research interests focus on disruptive manufacturing technologies, IoT-based systems, renewable energy optimization, smart automation, tribology, composite materials, and sustainable engineering design. Dr. Salawu has authored over 20 peer-reviewed journal and conference publications, with an approximate h-index of 3, and over 20 cumulative citations based on available scholarly records. She has received multiple competitive research grants, including TETFund institutional and doctoral awards, and was honored with an Award of Excellence as Best Researcher by the University of KwaZulu-Natal. Through impactful research, supervision, and innovation-driven teaching, she continues to contribute significantly to engineering education, sustainable technology development, and applied industrial research in Africa and beyond.

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Dike Chijindu P.; Sam Obu C.V.; Imuran A.S.; Salawu G.A.; Shuaib A.A. (2025).
Production and Mechanical Evaluation of Bio-Composite Materials from Coconut, Palm Kernel and Periwinkle Shells as an Alternative to Grinding Wheel Production.

International Journal of Applied and Advanced Engineering Research, Vol. 8, No. 5, 2025

Jimoh A.A.; Iromini N.A.; Oladuntoye Q.O.; Ajiteru S.O.; Salawu G.A. (2024).
Design and Deployment of an Internet of Things Based Weather Station for Real-Time Monitoring of Environmental Conditions.

International Journal of Earth Design and Innovation Research, Vol. 3, No. 4, 2024

Dike Chijindu P.; Sam Obu C.V.; Imuran A.S.; Salawu G.A.; Shuaib A.A.; Afolabi A.A. (2025).
Investigating the Mechanical Performance of Offshore Wind Turbine Towers Using Finite Element Analysis for Sustainable Renewable Energy.

Journal of Engineering, Logical and Modelling Research, 2025

Investigation of Technical Feasibility and Efficiency of Wi-Fi Based Internet of Things Remote Monitoring and Control of Home Appliances.

International Journal of Science Research and Technology, Vol. 6, No. 9, pp. 121–135, 2024

Design and Development of Internet of Things Based Weather Station for Real-Time Monitoring of Environmental Conditions.

International Journal of Earth Design and Innovation Research, Vol. 3, No. 4, pp. 66–75, 2024

Jun Hu | Medicine and Health Sciences | Research Excellence Award

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Dr. Jun Hu | Medicine and Health Sciences | Research Excellence Award

Nanjing University of Chinese Medicine | China

Jun Hu is a medical researcher and lecturer specializing in Traditional Chinese Medicine (TCM)–based interventions for inflammatory and immune-mediated diseases. Trained as a Medical Doctor at Nanjing University of Chinese Medicine, Hu has developed a focused academic career combining mechanistic biomedical research with evidence-based evaluation of traditional therapies. His professional experience centers on teaching and research at a leading TCM institution, where he contributes to both undergraduate and postgraduate medical education while leading interdisciplinary studies. Hu’s research interests include herbal formulas, electroacupuncture, acupoint application, and moxibustion, with particular emphasis on asthma, rheumatoid arthritis, neuroinflammation, and immune regulation. He has played a key role in nationally funded research, including a National Natural Science Foundation of China project investigating autophagy-dependent ferroptosis mechanisms in moxibustion therapy for rheumatoid arthritis synovitis. His scholarly output includes peer-reviewed articles in high-impact journals such as Biomolecules, Frontiers in Pharmacology, Mediators of Inflammation, and Journal of Ethnopharmacology. With an h-index of 7, more than 11 scientific publications, and over 95citations, his work demonstrates sustained academic influence. Overall, Jun Hu’s research bridges traditional medical theory and modern molecular science, advancing integrative strategies for chronic inflammatory disease management.

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Qufeng Xuanbi Formula inhibits benzo[a]pyrene-aggravated asthma via the AhR/ROS/ERK pathway

Journal of Ethnopharmacology, 2024 · DOI: 10.1016/j.jep.2023.117203

Bebetebe Fetimi | Energy and Sustainability | Research Excellence Award

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Mr. Bebetebe Fetimi | Energy and Sustainability | Research Excellence Award

University of Strathclyde | United Kingdom

Mr. Bebetebe Fetimi marine engineering professional and early-career researcher with expertise in marine reliability engineering, human and equipment reliability, and safety-critical maritime systems. He holds a First Class B.Sc. in Marine Engineering and formal qualifications in safety and risk management, supported by advanced professional training in tanker operations, high-voltage systems, ship security, and international maritime regulations. His professional experience spans offshore oil and gas operations, shipyard HSEQ management, and dynamic positioning vessels, where he has contributed to machinery maintenance, safety audits, incident investigation, ISM compliance, and operational risk control. Currently engaged in doctoral-level research in marine reliability engineering, his research interests focus on human reliability assessment, alternative fuel ship propulsion safety, maritime risk modeling, and the application of structured methods such as HEART, CREAM, and root cause analysis to improve system resilience. His scholarly output reflects a developing research profile with h-index: 1, documents: 2, and citations: 10 (current records), demonstrating growing academic impact alongside strong industry relevance. He has been recognized for safety leadership, operational excellence, and analytical problem-solving within multidisciplinary teams. Overall, his profile represents a balanced integration of applied engineering practice and research-driven insight aimed at advancing reliability, sustainability, and risk-informed decision-making in modern maritime and offshore engineering.


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Scissors Approach in Human and Equipment Reliability vis-à-vis the Use of Alternative Fuel in Ship Propulsion

Maritime Safety & Reliability Engineering · Alternative Fuel Ship Propulsion

Jeremy Carlosama | Biomedical Engineering | Research Excellence Award

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Mr. Jeremy Carlosama | Biomedical Engineering | Research Excellence Award

Yachay Tech University | Ecuador

Jeremy Fabrizio Carlosama Quinatoa is an emerging researcher in biomedical engineering whose work focuses on applying machine learning and intelligent sensing technologies to healthcare and rehabilitation. He holds a degree in Biomedical Engineering from Yachay Tech University, where his academic training emphasized biomechanics, human motion analysis, and data-driven medical systems. His professional experience includes teaching and research activities in biomechanics and biomedical signal processing, as well as participation in interdisciplinary projects that integrate inertial sensors, motion capture systems, neural networks, and clinical data. His research interests span machine learning for healthcare, rehabilitation engineering, inertial sensor systems, neural-network-based medical diagnosis, and assistive technologies. He has authored peer-reviewed research outputs including a journal article in Sensors (MDPI) and international conference book chapters addressing low back pain assessment, sign-language recognition, and heart failure diagnosis using artificial intelligence. As of 2025, his scholarly record includes 4 publications, an h-index of 2, and over 30 citations, reflecting growing academic impact at an early career stage. His work demonstrates a strong commitment to translational research that bridges engineering innovation and clinical application, positioning him as a promising young scientist contributing to the advancement of intelligent healthcare technologies.

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Ecuadorian Sign Language Detection in Real Time

J. Carlosama, S. Criollo, C. Játiva, V. Mina, S. Velastegui, J. de-la-A, et al.
International Conference on Computer Science, Electronics and Industrial Engineering, 2023

InertialMov: Machine Learning Test Based on Inertial Sensors to Predict Mobility Impairment in Low Back Pain Patients

J. Carlosama, L. Zhinin-Vera, C. Guevara, C. Cadena-Morejón, et al.
Sensors, Vol. 25(21), Article 6665, 2025

Diagnosis of Heart Failure: Integrating Echocardiographic and Clinical Data Through Neural Networks

V. Arrobo-Sarango, J. Carlosama, D. Almeida-Galárraga, A. Tirado-Espín, et al.
International Conference on Smart Technologies, Systems and Applications, 2024

Adetayo Folorunso | Energy and Sustainability | Best Researcher Award

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Dr. Adetayo Folorunso | Energy and Sustainability | Best Researcher Award

Federal University of Technology, Akure | Nigeria

Adetayo Folorunso is an established scholar in applied geophysics and environmental geosciences with a strong record of scientific contributions to groundwater, marine, and exploration geophysics.  Academic training and professional experience span geophysics, earth sciences, and applied geoscience, with extensive involvement in teaching, postgraduate supervision, and collaborative research across Nigerian and international institutions. Research work integrates electrical resistivity tomography (ERT), marine geophysics, hydrogeophysics, seismic interpretation, and environmental geophysics, addressing critical challenges such as saline water intrusion, groundwater vulnerability, subsurface contamination, and reservoir characterization. Contributions include high-impact journal articles, interdisciplinary studies combining geophysical and geochemical methods, and methodological advances in finite-element and CSEM modeling. Recognition includes scholarly visibility, sustained citation performance, and leadership in collaborative geoscience research. Overall, the body of work demonstrates a strong commitment to advancing applied geosciences through data-driven analysis, field-based investigations, and solutions relevant to environmental sustainability, resource exploration, and geotechnical risk assessment.

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Integrated Geophysical and Geochemical Methods for Environmental Assessment of Municipal Dumpsite System

International Journal of Geosciences, 4(5), 850–862, 2013 · Citations: 59


Engineering Site Characterisation Using 2-D and 3-D Electrical Resistivity Tomography

Earth Science Research, 2(1), 133–142, 2013 · Citations: 41

Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

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Mr. Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Ecole Polytechnique de Tunisie | Tunisia

Oussama El Othmani is an emerging researcher and software engineer whose work bridges artificial intelligence, explainable machine learning, and applied computer engineering. He is currently pursuing a PhD in ETIC, following a strong academic foundation in computer engineering and preparatory mathematics–physics, with rigorous training in artificial intelligence, advanced learning algorithms, computer architecture, databases, and software methodology. Professionally, he has contributed to complex, mission-critical software systems, working across the full software development lifecycle while applying agile methodologies, object-oriented design, and hardware-aware optimization. His research interests focus on explainable and interpretable AI, machine learning, rough set theory, soft computing, computer vision, natural language processing, and AI applications in healthcare and high-stakes decision systems. He has led and contributed to multiple applied AI projects, including medical chatbots, diagnostic decision-support systems, blood anomaly detection, and antibiotic resistance classification. His scholarly output includes peer-reviewed publications in applied AI, He has also gained recognition through research-driven projects aligned with national and institutional initiatives. Overall, his profile reflects a strong balance of academic research, applied innovation, and real-world impact, positioning him as a promising contributor to the future of trustworthy and explainable artificial intelligence.

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Dapeng Zhang | Engineering and Technology | Research Excellence Award

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Dr. Dapeng Zhang | Engineering and Technology | Research Excellence Award

 Guangdong Ocean University | China

Dr. Dapeng Zhang is an Associate Professor in Ocean Engineering at Guangdong Ocean University, China, with expertise in the dynamic response of offshore and subsea structures. He earned his Doctor of Engineering from Zhejiang University through a joint PhD program with the University of Lisbon, following a Master of Engineering from Ningbo University.  He was recognized among the top 5% of highly cited scholars by CNKI, highlighting his influence in marine and offshore engineering. His research spans marine engineering structures, pipelines and risers, offshore oil underwater production systems, marine artificial intelligence, and triboelectric nanogenerators (TENG). Dr. Zhang has published extensively in leading JCR Q1 journals such as Ocean Engineering, Physics of Fluids, Marine Structures, and Aquacultural Engineering, contributing foundational and applied insights into subsea dynamics, hydrodynamics, and deployment optimization. He serves as Editor-in-Chief of Engineering Solutions to Mechanics, Marine Structures and Infrastructures, holds additional editorial roles, and acts as a reviewer for numerous international journals. Overall, his scholarship integrates theory, computation, and engineering practice to advance safe, efficient, and intelligent offshore systems.

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Dynamic analysis of towed cable with variable length during turning maneuvers

Scientific Reports, 13(1), 3525, 2023 · Citations: 23

Amir Hossein akbari | Engineering and Technology | Research Excellence Award

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Dr. Amir Hossein akbari | Engineering and Technology | Research Excellence Award

Iran University of Science and Technology | Iran

Amir Hosein Akbari is an accomplished researcher in industrial engineering with a strong record of scholarly impact his academic background is grounded in advanced industrial engineering education, complemented by progressive research experience spanning optimization, decision sciences, and intelligent systems. His professional experience includes active involvement in high-quality research collaborations and contributions to applied and theoretical studies addressing complex industrial and societal problems. His core research interests focus on supply chain management, optimization, meta-heuristic and evolutionary algorithms, scheduling, decision support systems, and artificial intelligence–driven industrial applications, with several influential works in expert systems, soft computing, and manufacturing systems. His publications have appeared in high-impact venues such as Expert Systems with Applications, Soft Computing, and Neural Computing and Applications, reflecting both methodological rigor and practical relevance. Recognition of his work is demonstrated through strong citation performance and collaborations with well-established scholars in operations research and industrial engineering. Overall, his research portfolio highlights a consistent commitment to advancing intelligent optimization methods and decision-making frameworks, contributing valuable insights to academia and industry while strengthening the scientific foundations of modern industrial engineering.

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