Chungwei Kuo | Computer Networks | Cybersecurity Achievement Award

Assist. Prof. Dr. Chungwei Kuo | Computer Networks | Cybersecurity Achievement Award

Assistant Professor, Feng Chia University, Taiwan

Dr. Chung-Wei Kuo is an Assistant Professor at Feng Chia University, specializing in IoT security, lightweight cryptography, and countermeasures against side-channel attacks (SCAs). His research is dedicated to developing innovative encryption solutions for IoT devices, ensuring robust security while maintaining resource efficiency. Dr. Kuo has an active role in industry collaborations and mentoring young researchers. With a focus on advancing security for IoT ecosystems, he is a key player in the global cybersecurity community. 🌐🔒

Publication Profile

ORCID

Education

Dr. Kuo completed his Ph.D. in Electrical and Communications Engineering at Feng Chia University in Taichung, Taiwan, in 2016. His academic background is deeply rooted in information security and wireless communications. 🎓📚

Experience

Dr. Kuo’s academic journey includes roles such as Assistant Professor in the Information Engineering and Computer Science Department at Feng Chia University. He also holds invited positions, such as Chief Director of Activities at Apple RTC (2023-2025). Additionally, he serves as a course consultant for the Information Education Center. He has secured multiple research grants from the National Science and Technology Council to fund his innovative work on IoT and security. 💼📡

Awards and Honors

Dr. Kuo has received several prestigious awards and honors, including recognition for his pioneering research in side-channel attacks and lightweight cryptographic protocols. His research has been widely acknowledged for its contributions to securing IoT ecosystems. 🏅🔐

Research Focus

Dr. Kuo’s research interests lie at the intersection of IoT security, cryptography, and side-channel attack prevention. He focuses on creating encryption mechanisms for microcontrollers, balancing security with efficiency, and addressing vulnerabilities in resource-constrained environments. His ongoing research includes developing post-quantum computing-based attack-resistant platforms and enhancing IoT security with electromagnetic band-gap structures. 🔍💡

Conclusion

With a passion for cybersecurity and a clear vision for securing the next generation of IoT technologies, Dr. Chung-Wei Kuo continues to be a leading force in the research and development of cutting-edge cryptographic techniques. His contributions to the field are not only significant but also essential for the evolving digital landscape. 🔐🚀

Publications:

 Dynamic Key Replacement Mechanism for Lightweight Internet of Things Microcontrollers to Resist Side-Channel Attacks. Future Internet, 17(1), 43. (SCIE)

Design and Application of Novel Stripline for IC-EMC Characteristic Measurement,  IET Science, Measurement & Technology, Accepted, 2024-11. (SCIE)

ML-based Intrusion Detection System for Precise APT Cyber-clustering,  Computers & Security, Accepted, 2024-11. (SCIE)

An authorization transfer protocol for confidentiality preserving in public access devices, Journal of Internet Technology, Accepted, 2024-07. (SCIE)

Design of Side-Channel-Resistant Electromagnetic Band-Gap on IoT Microcontroller,  Journal of Internet Technology, Accepted, 2024-05. (SCIE)

CoNN-IDS: Intrusion Detection System based on Collaborative Neural Networks and Agile Training,  Computers & Security, vol. 122, pp. 1-13, 2022-11. (SCIE)

 

Yunhyung LEE | Computer science| Best Researcher Award

Prof. Dr. Yunhyung LEE | Computer Science | Best Researcher Award

Professor, Korea Institute of Maritime and Fisheries Technology, South Korea

Dr. Yunhyung Lee is a distinguished professor at the Korea Institute of Maritime and Fisheries Technology and an adjunct professor at Korea Maritime and Ocean University. With an academic journey spanning nearly two decades, Dr. Lee has made significant contributions to marine systems engineering, control systems, and maritime research. A prolific researcher and academician, he is known for his innovative approaches in marine electric systems, fuzzy control, and genetic algorithms. His commitment to fostering maritime education and cutting-edge research has earned him several accolades and a global reputation in his field. 🌐✨

Publication Profile

ORCID

Education 🎓

Dr. Lee graduated summa cum laude with a Bachelor’s degree in Marine System Engineering from Korea Maritime and Ocean University in 2002. He further earned his Master’s degree in 2004 and completed his Ph.D. in Mechatronics Engineering in 2007. His academic excellence is reflected in multiple awards, including the President’s Award for graduating with the highest honors. 🏆📚

Professional Experience 💼

Dr. Lee began his academic career as a part-time lecturer at Korea Maritime and Ocean University and Youngsan University. From 2008 to 2014, he served as a professor at the Korea Port Training Institute before joining the Korea Institute of Maritime and Fisheries Technology in 2014. Simultaneously, he has been an adjunct professor at Korea Maritime and Ocean University since 2015. His practical experience includes spearheading innovative research projects and consulting for industry collaborations. ⚙️🛳️

Awards and Honors 🏅

Dr. Lee’s outstanding achievements have been recognized through numerous awards, including the Albert Nelson Marquis Lifetime Achievement Award (2018) and the Young Researcher Award from the Korean Society of Marine Engineering (2015). He has also been honored for his contributions to education and research with awards such as the Best Paper Award by the Korean Federation of Science and Technology Societies (2006) and the Citation for Excellence in Lecturing by Korea Maritime and Ocean University (2008). 🌟🎖️

Research Focus 🔬

Dr. Lee’s research encompasses control engineering, marine electric systems, genetic algorithms, fuzzy control, and PID control. His studies aim to enhance the safety, efficiency, and reliability of marine propulsion systems and other maritime technologies. Through numerous research projects and innovative solutions, he has significantly advanced the field of marine and fisheries technology. 🌊⚡

Conclusion 🌟

Dr. Yunhyung Lee’s exceptional career reflects his dedication to advancing marine and maritime technology through research, education, and industry collaboration. His passion for innovation and his unwavering commitment to excellence make him a leading figure in his field. 🌏✨

Publications 📚

Application of Real-Coded Genetic Algorithm–PID Cascade Speed Controller to Marine Gas Turbine Engine Based on Sensitivity Function Analysis
Mathematics, 2025 – Cited by: 5

Development of Hull Care for Warships Based on a Manned-Unmanned Hybrid System: Focusing on the Underwater Hull Plate
Journal of the KNST, 2024 – Cited by: 3

Modeling and Parameter Estimation of a 2DOF Ball Balancer System
Journal of the Korea Academia-Industrial Cooperation Society, 2024 – Cited by: 4

Ground-Fault Recognition in Low-Voltage Ships Based on Variation Analysis of Phase-to-Ground Voltage and Neutral-Point Voltage
IEEE Access, 2024 – Cited by: 8

Speed Control for Low Voltage Propulsion Electric Motor of Green Ship through DTC Application
Journal of the Korea Academia-Industrial Cooperation Society, 2023 – Cited by: 6

RCGA-PID Controller Based on ITAE for Gas Turbine Engine in the Marine Field
The Journal of Fisheries and Marine Sciences Education, 2023 – Cited by: 3

PID Controller Design Based on Direct Synthesis for Set Point Speed Control of Gas Turbine Engine in Warships
Journal of the Korean Society of Fisheries Technology, 2023 – Cited by: 2

Study on Speed Control of LM-2500 Engine Using IMC-LPID Controller
Journal of the Korea Academia-Industrial Cooperation Society, 2022 – Cited by: 7

A Study on the Training Contents of AC DRIVE of the HV Electrical Propulsion Ships
Journal of Fisheries and Marine Sciences Education, 2021 – Cited by: 4

Cyruss Tsurgeon | Data Visualization | Bioinformatics Contribution Award

Mr. Cyruss Tsurgeon | Data Visualization | Bioinformatics Contribution Award

PhD Student, Meharry Medical College, United States

🌟 Cyruss Tsurgeon is a dedicated Biomedical Data Science graduate student and seasoned clinical scientist based in Rancho Cucamonga, CA. With a wealth of experience in diagnostic data interpretation and clinical medicine, Cyruss combines his technical acumen with a passion for advancing healthcare through data science. His impressive journey spans decades of leadership, research, and healthcare administration, making him a valuable contributor to the scientific and medical communities.

Publication Profile

Education

🎓 Cyruss holds an MS in Biomedical Data Science (2022–2023) from Meharry Medical College, Nashville, TN. He also earned an MS in Molecular Biotechnology (2000–2003) from Johns Hopkins University and dual BS degrees in Biochemistry and Microbiology (1987–1992) from the University of Washington, Seattle. Additionally, he has completed certifications such as the Google Data Analytics Professional Certificate and the Executive Data Science Specialization from Coursera, equipping him with expertise in data analytics, R programming, and visualization tools.

Experience

💼 Cyruss boasts a diverse professional background, including over a decade as a Clinical Laboratory Manager/Scientific Director in the US Army, where he led medical laboratories and implemented protocols for risk management and quality improvement. His tenure as a Biologist/Research Scientist at the NIH involved DNA sequencing and genome analysis. Earlier in his career, he served as a Healthcare Administrator in the US Army and a Research Associate at prominent institutions, contributing to molecular biology and comparative genomic studies.

Awards and Honors

🏆 Cyruss has achieved prestigious laboratory certifications, including DLM(ASCP)CM and MLS(ASCP)CM, showcasing his expertise in laboratory medicine. His contributions to clinical data science and diagnostics have been recognized through impactful research and publications in leading journals like Nature and Genome Research.

Research Focus

🔬 Cyruss’s research interests lie at the intersection of biomedical data science, molecular biology, and clinical medicine. He focuses on leveraging data visualization techniques, RNA-Seq analysis, and genome sequencing for clinical applications. His work emphasizes addressing real-world healthcare challenges, including multidrug-resistance surveillance and comparative genomic analyses.

Conclusion

✨ As a lifelong learner and experienced scientist, Cyruss Tsurgeon is committed to advancing healthcare innovation through data science and clinical research. His blend of expertise, leadership, and passion makes him a key player in the biomedical field, shaping the future of medicine and science.

Publications

Exploring RNA-Seq Data Analysis Through Visualization Techniques and Tools: A Systematic Review of Opportunities and Limitations for Clinical Applications
Bioengineering, 2025-01-12
DOI: 10.3390/bioengineering12010056

A Multidrug-Resistance Surveillance Network: 1 Year On
The Lancet Infectious Diseases, 2012-08
DOI: 10.1016/s1473-3099(12)70149-4

An Intermediate Grade of Finished Genomic Sequence Suitable for Comparative Analyses
Genome Research, 2004-10-12
DOI: 10.1101/gr.2648404

Comparative Analyses of Multi-Species Sequences from Targeted Genomic Regions
Nature, 2003-08-14
DOI: 10.1038/nature01858

 

 

Maged Al-Barashi | Electrical Engineering | Best Researcher Award

Assoc. Prof. Dr. Maged Al-Barashi | Electrical Engineering | Best Researcher Award

Aircraft quality and reliability, Guilin University of Aerospace Technology, China

🌟 Dr. Maged Manea Manea Al-Barashi is an accomplished academic, researcher, and engineer specializing in power systems and electrical engineering. Currently an Associate Professor and full-time teacher of Aircraft Quality and Reliability at the Guilin Institute of Aerospace Technology, Dr. Maged has made significant contributions to the fields of high-speed railway and aircraft power systems. With an extensive academic background and global research exposure, he is recognized for his innovative approaches to improving power quality and efficiency.

Publication Profile

Education

🎓 Dr. Maged holds a Ph.D. in Power System and Automation Engineering from Southwest Jiaotong University (2018–2023). He completed his Master’s in Power and Mechanical Engineering from Cairo University (2012–2015) and earned a Bachelor’s degree in Power System Engineering from Aleppo University (2003–2009).

Experience

💼 Dr. Maged has held various roles, including Senior Technical Engineer at NEDCO, Sales Support Engineer at MAM International, and Lecturer at the Institute of Industrial Technology. Since August 2023, he has been a full-time teacher at the Guilin Institute of Aerospace Technology, where he was promoted to Associate Professor in March 2024. He also serves as a research assistant and is actively involved in reviewing for prestigious journals like IEEE JESTPE, ISA Transactions, and IET Power Electronics.

Awards and Honors

🏆 Dr. Maged has received numerous certificates of excellence throughout his academic journey, alongside recognition for his international contributions, such as being a member of the Executive Committee of the Yemeni Students Association in China (2021–2022). He has been honored by the Yemeni Embassy for his exceptional academic achievements and service.

Research Focus

🔬 Dr. Maged’s research is focused on improving power quality in high-speed railway systems, aircraft power systems, and grid-connected converters. His expertise lies in developing innovative filtering techniques to mitigate current harmonics, enhance energy efficiency, and ensure reliability in modern power systems.

Conclusion

🌍 Dr. Maged Manea Manea Al-Barashi is a dedicated academic and researcher whose work bridges the gap between theoretical advancements and practical applications in power systems. His passion for improving power quality and reliability continues to drive impactful contributions to the fields of electrical and aerospace engineering.

Publications

High-Frequency Harmonics Suppression in High-Speed Railway Through Magnetic Integrated LLCL Filter – PLOS ONE, June 2024. DOI: 10.1371/journal.pone.0304464. Cited by 12.

Magnetic Integrated Double-Trap Filter Utilizing the Mutual Inductance for Reducing Current Harmonics in High-Speed Railway Traction Inverters – Scientific Reports, May 2024. DOI: 10.1038/S41598-024-60877-Y. Cited by 15.

Enhancing Power Quality of High-Speed Railway Traction Converters by Fully Integrated T-LCL Filter – IET Power Electronics, April 2023. DOI: 10.1049/pel2.12415. Cited by 8.

Magnetic Integrated LLCL Filter with Resonant Frequency Above Nyquist Frequency IET Power Electronics, October 2022. DOI: 10.1049/pel2.12313. Cited by 10.

Optimizing Solar Power Efficiency in Smart Grids Using Hybrid Machine Learning Models for Accurate Energy Generation Prediction – Scientific Reports, July 2024. DOI: 10.1038/s41598-024-68030-5. Cited by 18.

Review of Recent Control Strategies for the Traction Converters in High-Speed Train – IEEE Transactions on Transportation Electrification, June 2022. DOI: 10.1109/TTE.2022.3140470. Cited by 22.

Improving Power Quality in Aircraft Systems: Usage of Integrated LLCL Filter for Harmonic Mitigation – IEEE 3rd International Conference on Energy and Electrical Power Systems (ICEEPS), July 2024. DOI: 10.1109/ICEEPS62542.2024.10693264.

Fully Integrated TL-C-L Filter for Grid-Connected Converters to Reduce Current Harmonics – IEEE 12th Energy Conversion Congress and Exposition – Asia (ECCE-Asia), May 2021. DOI: 10.1109/ECCEAsia49820.2021.9479097.

A Novel Window Function for Memristor Model with Short-Term and Long-Term Memory Behavior – IEEE 7th International Conference on Electronic Information and Communication Technology (ICEICT), July 2024. DOI: 10.1109/ICEICT61637.2024.10671129.

Evaluating the Energy System in YemenJournal of Electrical Engineering (JEE), January 2016.

Evaluating Connecting Al-Mukha New Wind Farm to Yemen Power System – International Journal of Electrical Energy (IJOEE), June 2015. DOI: 10.12720/ijoee.3.2.57-67.

Chrysoula Florou | computer programming | Best Researcher Award

Ms. Chrysoula Florou | computer programming | Best Researcher Award

PHD Doctor, University of Thessaly, Greece

👩‍💻 Chrysoula Florou is a dedicated researcher and educator specializing in the intersection of education and programming concepts. With a strong background in computer engineering and a passion for enhancing primary education through innovative tools, she has made significant contributions to improving self-assessment practices for young learners. Beyond academia, she serves as an Officer in the Hellenic Coast Guard, showcasing her versatile professional capabilities.

Publication Profile

Scopus

Education

🎓 Chrysoula’s academic journey reflects her commitment to excellence, earning a Ph.D. (2010–2025) in Electrical and Computer Engineering from the University of Thessaly with a thesis on self-assessment in programming education (“Excellent”). She holds two master’s degrees: one in Informatics focusing on Security and Big Data (2016–2018, “Excellent”) and another in Computer Science and Technology (2009–2011, “Excellent”). Additionally, she completed a diploma in Computer Engineering (2004–2009, “Very Good”) and a certified program in E-Learning Training (2012).

Experience

🧑‍🏫 Chrysoula has extensive teaching experience in programming, database applications, and multimedia at institutions like the University of Thessaly, TEI of Lamia, and DIEK Volos. In parallel, she contributed to European research projects like “cMinds” and worked in IT roles for the Ministry of Health and National Bank of Greece. Since 2011, she has served as an Officer in the Hellenic Coast Guard, balancing her technical expertise with public service.

Awards and Honors

🏆 Chrysoula has earned numerous accolades for her academic excellence, including distinctions for her master’s theses and diploma projects. Her research outcomes have been recognized by leading journals and conferences in the education and programming domains.

Research Focus

🔬 Chrysoula’s research centers on the integration of educational technologies in programming pedagogy, particularly for primary education. She explores self-assessment tools, enhancing teacher facilitation roles, and leveraging innovative software like Scratch for fostering computational thinking in young learners.

Conclusion

🌟 Chrysoula Florou exemplifies the harmony between academia, research, and public service. Her impactful work in education technology and programming continues to inspire both educators and students, shaping the future of learning in primary education.

Publications

The Role of Educators in Facilitating Students’ Self-Assessment in Learning Computer Programming Concepts: Addressing Students’ Challenges and Enhancing Learning.  Journal of Education and Information Technologies, Springer Nature Educ. DOI: 10.1007/s10639-024-13172-2

An autodidactic programming curriculum application for early education: Pilot studies and improvement suggestions.  Proceedings of the 40th SEFI Annual Conference 2012 – Engineering Education 2020: Meet the Future.

3rd graders’ experience on using an autodidactic programming software: A phenomenological perspective. Conference Paper.

 

 

Sihwan Kim | Biomedical Engineering | Best Researcher Award

Dr. Sihwan Kim | Biomedical Engineering | Best Researcher Award

Ph.D., Seoul National University, South Korea

🌟 Dr. Sihwan Kim is a dedicated researcher specializing in medical image processing, artificial intelligence, and medical physics. He is currently associated with Seoul National University, where his innovative work combines machine learning and advanced imaging techniques to revolutionize healthcare solutions. With a strong academic background and extensive professional experience, Dr. Kim is recognized as an emerging leader in his field.

Publication Profile

Education

🎓 Dr. Kim earned his Ph.D. in Applied Bioengineering from Seoul National University, Republic of Korea, in February 2025. He holds a dual Bachelor of Science degree in Manufacturing Systems and Design Engineering from the University of Northumbria at Newcastle (UK) and Seoul National University of Science and Technology (Korea), obtained in 2018.

Experience

🔬 Dr. Kim has contributed significantly as a Research Scientist at the Biomedical Research Institute, Seoul National University Hospital. His expertise spans medical imaging with machine learning and deep learning applications, focusing on CT, MRI, and nano-biological imaging. He has also completed five Korean government research projects and one industry-sponsored project.

Awards and Honors

🏆 Dr. Kim is a valued member of prestigious organizations such as the Radiological Society of North America (RSNA), the International Commission on Radiological Protection (ICRP), and the Korean Society of Imaging Informatics in Medicine (KSIIM). His groundbreaking contributions, particularly in AI-driven segmentation workflows, have earned him accolades across the scientific community.

Research Focus

💡 Dr. Kim’s research revolves around medical image processing, leveraging artificial intelligence to enhance the efficiency and accuracy of diagnostic tools. His recent work introduced a novel fully-automated audit and self-correction algorithm using MeshCNN and generative AI, significantly impacting clinical applications through innovative segmentation techniques.

Conclusion

🌐 Dr. Sihwan Kim is a trailblazer in applying artificial intelligence to medical imaging, with his work poised to improve healthcare practices globally. His dedication to research excellence and groundbreaking contributions exemplify his potential as a transformative figure in the field.

Publications

Advanced AI Techniqes for Automated Segmentation in Medical Imaging, Bioengineering, MDPI.

Cited by: 8

MeshCNN Applications in 3D Topology Analysis,  Journal of Medical Physics Research.

Cited by: 5

Uncertainty Measurement in 3D-Mesh Surfaces, Korean Journal of Radiological Science.

Cited by: 3

Hybrid Models in Medical Imaging,  Journal of AI-Driven Healthcare Research.

Cited by: 4

Deep Learning in Nano-Biological Imaging,  International Journal of Biomedical Research.

Cited by: 1

Huiping Dai | Plant Science | Best Scholar Award

Ms. Huiping Dai | Plant Science | Best Scholar Award

Professor, Shaanxi University of Technology, China

👩‍🔬 Huiping Dai is a professor at Shaanxi University of Technology, where she specializes in bioremediation and selenium resource development. With extensive experience in environmental science, she has led numerous research projects funded by the Ministry of Science and Technology and provincial agencies, accumulating over 5 million yuan in funding. A renowned academic, she has published 50 SCI papers in top-tier journals and holds three national invention patents. Her contributions to the field have made a significant impact, with her work cited by hundreds of scholars.

Publication Profile

Scopus

Education:

🎓 Huiping Dai earned her academic credentials in environmental science and engineering, laying the foundation for her future research in bioremediation, plant ecology, and pollution control technologies. She has a long-standing commitment to developing sustainable solutions for environmental challenges, particularly in relation to heavy metal pollution and resource utilization.

Experience:

💼 Huiping Dai has presided over six Ministry of Science and Technology projects and managed 10 provincial and ministerial projects, leading innovations in environmental science. Her work spans across the development of AI solutions for pollution control and phytoremediation technologies. She is an expert in plant-microbe joint remediation of polluted environments and the safe utilization of agricultural products impacted by pollution.

Awards and Honors:

🏅 Throughout her career, Huiping Dai has earned several prestigious awards, including recognition from the Ministry of Science and Technology, as well as provincial honors for her pioneering work in bioremediation. Her achievements in developing smart platforms for environmental pollution control have been groundbreaking, earning her accolades both nationally and internationally.

Research Focus:

🌱 Huiping Dai’s research primarily focuses on mechanisms of selenium and cadmium accumulation in plants, resource utilization, and the remediation of heavy metal-contaminated soils. She is committed to advancing phytoremediation efficiency through innovative techniques such as the use of hyperaccumulator plants and AI-enhanced environmental management tools. Her work in this area is designed to improve the safety and sustainability of agricultural and industrial land.

Conclusion:

🌍 Huiping Dai continues to make strides in environmental science, particularly in the field of pollution control and sustainable resource development. Her leadership in both academic and practical applications of bioremediation technology positions her as a key figure in the fight against environmental degradation, particularly in areas affected by heavy metals.

Publications:

Remediation of Heavy Metal Contaminated Soils Using Hyperaccumulator Plants: Mechanisms and Applications,  Journal of Hazardous Materials.
Link to publication
Cited by: 112

Phytoremediation of Selenium and Cadmium Contamination: A Joint Plant-Microbe Approach, Chemosphere.
Link to publication
Cited by: 98

Development of Smart Platforms for Pollution Control in Agricultural Zones, Environmental Pollution.
Link to publication
Cited by: 75

Innovative Methods for Improving Phytoremediation Efficiency of Cadmium-Contaminated Soils, Journal of Agro-Environment Science.
Link to publication
Cited by: 65

New Green Activators for Phytoremediation of Cadmium: Enhancing Efficiency in Hyperaccumulating Plants,”Chinese Journal of Applied Ecology.
Link to publication
Cited by: 50

 

Rabha Ibrahim | Quantum Science | Best Researcher Award

Prof. Dr. Rabha Ibrahim | Quantum Science | Best Researcher Award

Alayen University, United States

Rabha Waell Ibrahim (Rabha W. Ibrahim) is a distinguished researcher and academic in the fields of complex, computing, and cloud systems, with a focus on mathematical modeling, image processing, geometric function theory, fractional calculus, and quantum computing. She holds a Ph.D. in Complex Systems from Universiti Kebangsaan Malaysia (UKM) and has completed postdoctoral research at the Cloud Computing Center, University Malaya. With a career spanning multiple international institutions, Rabha has been recognized among the world’s top 2% scientists by Stanford University and Elsevier across multiple years. She currently serves as a Professor at Istanbul Okan University, Turkey, contributing to the advancement of mathematical and computing sciences. Her research is recognized globally, and she actively contributes to various prestigious journals. 📚🌐

Publication Profile

Education

Rabha Waell Ibrahim completed her Ph.D. in Complex Systems at the Centre of Modelling and Data Sciences, University Kebangsaan Malaysia (UKM), in 2011. She furthered her expertise with postdoctoral research at the Cloud Computing Center, University Malaya, in 2016. Additionally, she holds a Google Data Analytics Certificate from Coursera, earned in May 2022. 🎓📖

Experience

Rabha has held several academic and research positions in renowned universities and institutions across the world. She began her career as a Senior Lecturer at University Malaya, Malaysia, from 2011 to 2015, followed by a role as Senior Researcher at the same university until 2016. She was an Associate Professor at Modern College of Business and Science in Oman from 2017 to 2019, and later worked as a Senior Researcher at Ton Duc Thang University, Vietnam, from 2019 to 2021. Rabha has also contributed as a researcher at Lebanese American University, Lebanon, and Near East University, Cyprus, and is currently a Professor at Istanbul Okan University, Turkey. 🏫🌍

Awards and Honors

Rabha’s significant contributions to science have earned her recognition in the form of listings among the world’s top 2% scientists by Stanford University and Elsevier over several years (2019–2024). Additionally, she has a remarkable H-index, with values of 28 in Web of Science, 31 in Scopus, and 33 in ResearchGate. These achievements reflect her ongoing influence in her fields of expertise. 🏅🌟

Research Focus

Rabha’s research spans a broad array of topics, including complex systems, computing, cloud systems, and mathematical modeling. She has made substantial contributions to image processing, geometric function theory, fractional calculus, and quantum computing. Her work also delves into the intersection of fractals and fractional calculus, with applications in various scientific domains. Her research continues to impact theoretical and applied mathematics, influencing both academia and industry. 🔬💻

Conclusion

Rabha W. Ibrahim is a globally recognized expert in mathematical sciences, whose work spans numerous cutting-edge topics, including cloud computing, fractional calculus, and quantum computing. Her consistent presence in the global scientific community, coupled with her prestigious academic appointments and research achievements, makes her a leading figure in her field. 🌍💡

Publications

Quantum–Fractal–Fractional Operator in a Complex Domain

Published: 2025

Journal: Axioms

DOI: 10.3390/axioms14010057

Cited by: Crossref

The Essential Gronwall Inequality Demands the (ρ,φ)(\rho, \varphi)-Fractional Operator with Applications in Economic Studies

Published: 2024

Journal: Universal Journal of Mathematics and Applications

DOI: 10.32323/ujma.1425363

Cited by: Crossref

A New Self-Organization of Complex Networks Structure Generalized by a New Class of Fractional Differential Equations Generated by 3D-Gamma Function

Published: 2024

Journal: Journal of King Saud University – Science

DOI: 10.1016/j.jksus.2024.103512

Cited by: Crossref

Classification of Tomato Leaf Images for Detection of Plant Disease Using Conformable Polynomials Image Features

Published: 2024

Journal: MethodsX

DOI: 10.1016/j.mex.2024.102844

Cited by: Crossref

Studies in Fractal–Fractional Operators with Examples

Published: 2024

Journal: Examples and Counterexamples

DOI: 10.1016/j.exco.2024.100148

Cited by: Crossref

K-Symbol Fractional Order Discrete-Time Models of Lozi System

Published: 2024

Journal: Book Chapter

DOI: 10.1201/9781003568643-11

Cited by: Crossref

Properties and Applications of Complex Fractal–Fractional Operators in the Open Unit Disk

Published: 2024

Journal: Fractal and Fractional

DOI: 10.3390/fractalfract8100584

Cited by: Crossref

Analysis of a Normalized Structure of a Complex Fractal–Fractional Integral Transform Using Special Functions

Published: 2024

Journal: Axioms

DOI: 10.3390/axioms13080522

Cited by: Crossref

Generalized Fractional Integral Operator in a Complex Domain

Published: 2024

Journal: Studia Universitatis Babes-Bolyai Matematica

DOI: 10.24193/subbmath.2024.2.03

Cited by: Crossref

Mathematical Modeling and Performance Evaluation of Ducted Horizontal-Axis Helical Wind Turbines: Insights into Aerodynamics and Efficiency

Published: 2024

Journal: PLOS ONE

DOI: 10.1371/journal.pone.0303526

Cited by: Crossref

 

Juan Tian | Fault Diagnosis | Best Dissertation Award

Dr. Juan Tian | Fault Diagnosis | Best Dissertation Award

Senior experimentalist, Taiyuan University of Science and Technology, China

Juan Tian is a Senior Experimentalist currently working towards his Ph.D. in Control Science and Engineering at Taiyuan University of Science and Technology, China. His career spans across research and development in intelligent fault diagnosis and prognostics. Specializing in deep learning, transfer learning, and meta-learning, Juan has made significant contributions to industrial fault diagnostics. He has co-authored numerous research papers and actively participated in global academic conferences 🌍. His expertise lies in leveraging advanced machine learning techniques to solve real-world problems in fault diagnosis and health management of machinery ⚙️.

Publication Profile

Education

Juan Tian holds a Bachelor’s degree in Control Science and Engineering from Taiyuan University of Technology, which he completed in 2009. He is currently pursuing his Ph.D. in Control Science and Engineering at Taiyuan University of Science and Technology, China 📚.

Experience

Juan Tian has been actively involved in several research projects focused on fault diagnosis, health management, and predictive maintenance systems. His work is particularly prominent in the field of industrial equipment diagnostics, with ongoing projects funded by the National Natural Science Foundation of China and the Shanxi Provincial government 🛠️. His expertise extends to consultancy and industry projects, including his work on intelligent fault diagnosis for wind turbines 🌬️.

Awards and Honors

Juan Tian has contributed to several pioneering research projects, such as X-ray image segmentation for welding defects and cross-domain fault diagnosis for wind turbines. His publications have garnered international recognition, with his work being cited by leading journals in the field of engineering 🔬. He is also a reviewer for various prestigious journals, underlining his recognition in the academic community 🏅.

Research Focus

Juan Tian’s research focuses on intelligent fault diagnosis and prognostics, utilizing advanced machine learning techniques like deep learning and transfer learning. His work addresses key challenges such as diagnosing rotating machinery with incomplete data, particularly in complex industrial settings. His research has led to innovations in predictive maintenance and fault diagnosis systems for various industries 🧠🔧.

Conclusion

Juan Tian is a rising expert in the field of intelligent fault diagnosis, combining advanced machine learning methods to tackle industrial challenges. His academic and research contributions have shaped the development of practical diagnostic solutions, making him a leading figure in his field 🌟.

Publications

Fault Diagnosis With Robustness and Lightweight Synergy Under Noisy Environment, IEEE Sensors Journal, 2023 (SCI Indexed)

A Review of Rotation Mechanical Fault Diagnosis Research Based on Deep Domain Adaptation, 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications, 2023 (Scopus Indexed)

Multi-sensor Based Graph Convolution Fault Diagnosis Method, 2024 36th Chinese Control and Decision Conference, 2024 (Scopus Indexed)

A Multi-Source Domain Adaptation Method for Bearing Fault Diagnosis with Dynamically Similarity Guidance on Incomplete Data, Actuators, 2025 (SCI Indexed)

NI Tongyuan | Concrete Materials | Excellence in Research

Prof. Dr. NI Tongyuan | Concrete Materials | Excellence in Research

Zhejiang University of Technology, Civil Engineering College, China

Dr. Tongyuan Ni is a Senior Engineer in the College of Civil Engineering at Zhejiang University of Technology. He holds a Doctorate in Engineering from the College of Materials at the same university and has more than two decades of experience in civil engineering and materials science. He specializes in high-performance concrete materials, green building materials, and concrete crack detection. 🌍🏗️

Publication Profile

Education

Dr. Ni’s academic journey began at Zhejiang University of Technology, where he graduated in 1994 with a degree in Road and Bridge Engineering. He later earned a Master’s degree in Civil and Architectural Engineering in 2005 from the same institution. In 2020, he obtained his PhD in Engineering from the College of Materials at Zhejiang University of Technology. 🎓📚

Experience

Dr. Ni has worked extensively in the field of civil engineering, leading projects related to the development of ecological paving materials, as well as advanced crack detection technologies. His projects include the development of permeable ecological paving materials and technologies for sludge ceramsite and innovations in crack detection in bridge structures. He currently contributes to both academic research and industry applications. 🔧🔍

Awards and Honors

Dr. Ni has received several prestigious awards, including recognition for his work in developing environmentally friendly building materials and technologies. His research contributions in the areas of concrete materials and crack detection have earned him numerous accolades within academic and engineering communities. 🏆🎖️

Research Focus

Dr. Ni’s research focuses on high-performance concrete materials, green building materials, and concrete crack detection and control. He has been involved in numerous projects, including the development of smart technologies for structural monitoring and sustainable materials. 🌱🏗️

Conclusion

Dr. Ni’s extensive experience and innovative research in the field of civil engineering, particularly in concrete technology, make him a leading expert in the development of sustainable and high-performance building materials. His contributions continue to advance the understanding and application of ecological and smart materials in construction. 🏙️📈

Publications

Chemical activation of pozzolanic activity of sludge incineration ash and application as raw bonding materials for pervious ecological brick (2022), Construction and Building Materials, IF=6.141

Study on Properties of Composite Cementitious Materials Compounded with Cement and Sludge Incineration Ash (2022), Journal of Building Materials, EI

Measurement of concrete crack feature with android smartphone APP based on digital image processing techniques (2020), Measurement, IF=3.927

Research on Detection of Concrete Surface Cracks Based on Smartphone Image (2021), Acta Metrologica Sinica

Research progress of bridge fracture detection technology based on image processing technology (2019), Urban Roads and Bridges and Flood Control

Interface reinforcement and a new characterization method for pore structure of pervious concrete (2021), Construction and Building Materials, IF=6.141

Influences of Environmental Conditions on the Cracking Tendency of Dry-Mixed Plastering Mortar (2018), Advances in Materials Science and Engineering, SCI, JCR Q4

Experimental Study on Early-Age Tensile Creep of High Strength Concrete under Different Curing Temperature (2018), Journal of Building Materials

Early-Age Tensile Basic Creep Behavioral Characteristics of High-Strength Concrete Containing Admixtures (2019), Advances in Civil Engineering, SCI, Q3

An Investigation of the Influence of Paste’s Rheological Characteristics on the Tensile Creep of HVFAC at Early Ages (2025), Materials, IF=3.257