Olivier Donfouet | intelligence artificielle | Best Scholar Award

Dr. Olivier Donfouet | intelligence artificielle | Best Scholar Award

Université de Dschang/Cameroun | Cameroon

Publication Profile

Scopus

🌍 Dr. Olivier Donfouet: Bridging Mathematics, AI, and Agriculture 🚀

INTRODUCTION 📚

Dr. Olivier Donfouet is a distinguished mathematical economist, researcher, and entrepreneur dedicated to leveraging Artificial Intelligence (AI) to transform agricultural practices in Africa. With a strong background in mathematical economics, project management, and technology-driven solutions, he has contributed significantly to both academia and industry. His expertise spans economic modeling, agricultural innovation, and AI-driven research, making him a key figure in sustainable agricultural development.

EARLY ACADEMIC PURSUITS 🎓

Dr. Donfouet’s academic journey began at Université de Dschang, where he earned a Ph.D. in Mathematical Economics. His foundational studies included a Master’s and Bachelor’s degree in the same field, equipping him with advanced skills in economic analytics, statistical modeling, and AI applications in economics. His academic excellence was complemented by hands-on experiences with data analysis software such as Stata, SPSS, and LaTeX.

PROFESSIONAL ENDEAVORS 💼

Dr. Donfouet has amassed diverse professional experiences, including:
Academic Internship at the International Center for Artificial Intelligence in Morocco
Drone Technology Training for Agricultural Innovation
Lecturing & Mentorship at Université de Dschang
Entrepreneurship in Sustainable Product Development
Active Participation in International Conferences on AI & Gender Equality

Beyond academia, he is recognized as an entrepreneur and business leader, having successfully developed eco-friendly mosquito-repellent candles—a project that earned him national recognition and innovation awards.

CONTRIBUTIONS AND RESEARCH FOCUS  ON INTELLIGENCE ARTIFICIELLE🔬

Dr. Donfouet’s research focuses on AI’s impact on agricultural productivity, gender equality, and sustainability. His notable contributions include:
🔹 Investigating AI-driven economic models for sustainable agriculture
🔹 Exploring ICT’s role in reducing undernourishment in Africa
🔹 Analyzing AI’s contribution to empowering women in agriculture
🔹 Examining AI’s effect on total factor productivity in agriculture

His innovative approach to precision agriculture and economic modeling makes his work highly relevant to policymakers, researchers, and industry leaders.

IMPACT AND INFLUENCE 🌍

Dr. Donfouet’s work extends beyond research—his influence is seen in:
Educating the next generation of economists and AI researchers
Advancing AI applications in African agriculture
Innovating sustainable solutions for economic development
Shaping policies through data-driven insights

His leadership in youth mentorship, religious associations, and AI-driven economic policies further cements his influence in both academic and community spheres.

ACADEMIC CITATIONS AND PUBLICATIONS 📝

Dr. Donfouet has contributed to leading peer-reviewed journals, including:
1️⃣ “Is Artificial Intelligence Helping to Empower Women in Agriculture in Africa?” (GeoJournal, 2024)
2️⃣ “Impact of AI on Total Productivity of Agricultural Factors in Africa” (Environment, Development and Sustainability, 2024)
3️⃣ “How Important is ICT for Reducing Undernourishment in Africa?” (Telematics and Informatics Reports, 2023)

These publications highlight the intersection of AI, economic growth, and sustainable agriculture.

HONORS & AWARDS 🏅

🏆 4th Place National Innovation Award (Ministry of Small and Medium Enterprises, Yaoundé)
🏆 3rd Place CATI2 Innovation Award (Université de Dschang)
🏆 Recognized AI Researcher at International Conferences
🏆 Leadership & Entrepreneurship Excellence in Agriculture

FINAL NOTE ✨

Dr. Olivier Donfouet is a trailblazer in mathematical economics and AI-driven agricultural solutions. His work continues to push the boundaries of economic theory, AI applications, and sustainable innovation, making him a key player in Africa’s digital agricultural revolution.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

🔸 Future research on AI-driven solutions for climate-resilient agriculture
🔸 Advancing economic policies integrating AI for food security
🔸 Bridging the gap between technological innovations and agricultural practices
🔸 Mentorship programs for emerging scholars in AI & Economics

TOP NOTES PUBLICATIONS 📚

Title: Is artificial intelligence helping to empower women in agriculture in Africa?

Authors: Olivier, D., & Ibrahim, N.
Journal: GeoJournal
Year: 2024

Title: Impact of artificial intelligence on the total productivity of agricultural factors in Africa.

Authors: Donfouet, O., & Ngouhouo, I.
Journal: Environment, Development and Sustainability
Year: 2024

Title: How important is ICT for reducing undernourishment in Africa?

Authors: Domguia, E. N., Hymette, L. F. N., Nzomo, J. T., Ngassam, S. B., & Donfouet, O.
Journal: Telematics and Informatics Reports
Year: 2023

Amjad Abu ELSamen | marketing | Best Scholar Award

Prof. Amjad Abu ELSamen | marketing | Best Scholar Award

Zayed University | United Arab Emirates

Publication Profile

Scopus
Google Scholar

INTRODUCTION 📚

Amjad Abu-Elsamen, PhD, is a distinguished academic and professional in the fields of marketing, predictive modeling, and data mining, based in Abu Dhabi, UAE. With a career that spans over two decades, Dr. Abu-Elsamen has made significant contributions to academia and consultancy, blending his expertise in business strategy, data analytics, and marketing. His passion for continuous learning and his unwavering dedication to professional growth have earned him recognition and numerous accolades in both his academic and practical endeavors.

EARLY ACADEMIC PURSUITS 🎓

Dr. Abu-Elsamen’s academic journey began with his undergraduate studies in Business Administration at the University of Jordan, where he earned his Bachelor’s degree in 2000. He went on to pursue his Master of Business Administration (MBA) at the University of Jordan, completing it in 2003. Following this, he advanced his studies by earning a PhD in Business Administration from Oklahoma State University in 2009. During his academic pursuits, he developed a keen interest in predictive modeling, data mining, and their applications in marketing strategies.

PROFESSIONAL ENDEAVORS 💼

Dr. Abu-Elsamen’s professional career reflects his commitment to education, research, and industry consultancy. He has served as a Professor of Marketing at Zayed University since 2019, with prior roles such as the Associate Professor of Marketing and Graduate Programs Director. His extensive experience as a department chair in various academic institutions, including Zayed University and the University of Jordan, highlights his leadership skills and dedication to curriculum development and accreditation. Dr. Abu-Elsamen’s industry work is equally impressive, with significant consultancy contributions for major corporations in the UAE and Jordan, including Etihad Airways, Marina Mall, and Al-Ain Distribution Company.

CONTRIBUTIONS AND RESEARCH FOCUS  ON MARKETING🔬

Dr. Abu-Elsamen’s research interests lie primarily in marketing strategy, data mining, and predictive modeling. He has published numerous studies on topics such as customer satisfaction measurement, brand management, and the use of advanced analytics in decision-making processes. His research contributions also extend to the design of business programs and the development of new marketing techniques that combine traditional strategies with innovative data-driven insights. Additionally, he has provided key guidance on curriculum redesign and development, particularly in graduate programs, ensuring that they remain aligned with global standards and market needs.

IMPACT AND INFLUENCE 🌍

Dr. Abu-Elsamen’s influence extends beyond his teaching and research contributions. He has been instrumental in shaping the business education landscape in the UAE and Jordan, particularly in the areas of business analytics and marketing strategy. His leadership in developing the Business Analytics Certification Program, the first of its kind in the Middle East, showcases his dedication to advancing education in this critical field. Furthermore, his active participation in committees and task forces within his institutions, including the revision of faculty promotion guidelines and mentorship programs, highlights his commitment to enhancing academic standards and faculty development.

ACADEMIC CITATIONS AND PUBLICATIONS 📝

Dr. Abu-Elsamen has contributed widely to academic journals, conferences, and industry reports. His work has been recognized internationally, with notable citations in the areas of marketing research, customer satisfaction, and data mining techniques. Some of his well-known publications include studies on structural equation modeling, segmentation analysis, and the use of conjoint analysis in new product development. His published research continues to shape contemporary marketing and data analytics practices.

HONORS & AWARDS 🏅

Dr. Abu-Elsamen’s exceptional academic and professional achievements have earned him several prestigious honors, including:

  • Best Paper Award, ACME Conference (2011)
  • Second Best Model Building Award, Data Mining Shootout (2008)
  • Recognition for his leadership in business analytics and marketing strategy across multiple universities and consultancy projects.

FINAL NOTE ✨

Dr. Amjad Abu-Elsamen’s career is a testament to the power of perseverance, innovation, and academic excellence. Through his dedication to both teaching and consultancy, he has made significant strides in reshaping business education, particularly in the realms of marketing, data mining, and analytics. His passion for knowledge and growth continues to inspire both students and professionals in the Middle East and beyond.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Looking to the future, Dr. Abu-Elsamen aims to further elevate business education and consultancy in the UAE and globally. He plans to continue his research into advanced data mining techniques and their applications in marketing strategy, with a particular focus on predictive analytics and artificial intelligence. His ongoing work promises to impact future generations of students and professionals, continuing to drive innovation and excellence in the field.

TOP NOTES PUBLICATIONS 📚

Modelling the impact of 3D product presentation on online behaviour
    • Authors: RS Algharabat, AA Abu-ElSamen
    • Journal: International Journal of Electronic Marketing and Retailing
    • Year: 2013
      🖥️📦👀📊
Examining the Construct Validity of the Lockwood Goal Orientation Scale Using the General Hierarchal Model: An Exploratory Study
    • Author: A Abu ELSamen
    • Journal: Academy of Marketing Science Annual Conference
    • Year: 2010
      🎯📚📊
An empirical model of mobile shopping attitudes and intentions in an emerging market
    • Authors: MN Akroush, B Mahadin, AA ElSamen, A Shoter
    • Journal: International Journal of Web Based Communities
    • Year: 2020
      📱🛒🌍💭
An empirical model of customer service quality and customer loyalty in an international electronics company
    • Authors: AA Abu-ELSamen, MN Akroush, AL Al-Sayed, HJ Hasan
    • Journal: International Journal of Electronic Business
    • Year: 2012
      💼💡🤝📊
Conceptualisation and development of customer service skills scale: an investigation of Jordanian customers
    • Authors: MN Akroush, AA Abu-ElSamen, MS Al-Shibly, FM Al-Khawaldeh
    • Journal: International Journal of Mobile Communications
    • Year: 2010
      📱💬💡🌍
Fintech and contactless payment: help or hindrance? The role of invasion of privacy and information disclosure
    • Authors: AA Alalwan, AM Baabdullah, MM Al-Debei, R Raman, HK Alhitmi, …
    • Journal: International Journal of Bank Marketing
    • Year: 2024
      💳🔒💡🔍

Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

Dr. Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

shahid beheshti university | Iran

Author Profile

Early Academic Pursuits 📚

Dr. Alireza Sobbouhi’s academic journey began at Shahid Beheshti University in Iran, where he developed a strong foundation in mathematics, statistics, and computational sciences. His early fascination with complex systems and data-driven decision-making led him to specialize in predictive modeling. This interest propelled him into graduate studies, where he focused on developing and applying sophisticated techniques for forecasting and analyzing data.

Professional Endeavors 💼

Dr. Sobbouhi’s career blends academic achievements with professional success. As a professor at Shahid Beheshti University, he has been deeply involved in teaching, research, and industry collaboration. His role in academia extends beyond teaching as he works on impactful projects that link predictive modeling with real-world applications, from healthcare to finance. His expertise has also made him a sought-after consultant, furthering his reach and influence in both academia and industry.

Contributions and Research Focus On Predictive Modeling Innovations🔬

Dr. Sobbouhi’s research is rooted in the advancement of predictive modeling. His contributions have introduced new methodologies to improve the accuracy and efficiency of data analysis in various domains. Some key areas of focus include:

  • Development of Predictive Algorithms: Crafting algorithms that provide more precise predictions in economic, healthcare, and environmental sectors.
  • Machine Learning Integration: Exploring ways to integrate machine learning techniques into predictive models for better data interpretation and forecasting.
  • Big Data Analytics: Focusing on scalable approaches to handle and analyze massive datasets to uncover patterns that traditional models might miss.

Impact and Influence 🌍

Dr. Sobbouhi’s work has had a profound impact, not only in academia but also across various industries. His innovative contributions to predictive modeling and machine learning have influenced numerous researchers and professionals in fields ranging from economics to environmental science. His approach to enhancing model reliability and interpretability has set new standards and inspired further research in data science. The applications of his work continue to improve decision-making processes worldwide.

Academic Cites 📑

Dr. Sobbouhi’s research has been extensively cited in scholarly articles, journals, and conferences, indicating the high regard in which his work is held. His studies on predictive analytics and statistical modeling have been foundational, influencing a wide range of studies in machine learning and data science. The frequency of his citations reflects the relevance and significance of his contributions to the broader scientific community.

Technical Skills 🧑‍💻

Dr. Sobbouhi possesses a diverse and deep technical skill set that includes:

  • Programming: Expertise in Python, R, and MATLAB for data analysis and modeling.
  • Statistical Modeling: Advanced proficiency in developing and applying statistical techniques for prediction and forecasting.
  • Machine Learning: Expertise in applying machine learning algorithms to large datasets to uncover trends and make predictions.
  • Data Visualization: Strong skills in visualizing complex datasets to facilitate understanding and decision-making.

These technical competencies allow him to tackle complex datasets and develop state-of-the-art predictive models.

Teaching Experience 🏫

As an educator, Dr. Sobbouhi has taught a variety of courses on statistics, data science, and machine learning at Shahid Beheshti University. His teaching style blends theoretical knowledge with practical applications, ensuring students are well-prepared for the real-world challenges of the data science field. Dr. Sobbouhi has also supervised many graduate students, guiding them in their research and helping to shape the next generation of data scientists.

Legacy and Future Contributions 🔮

Dr. Sobbouhi’s legacy is built on his innovative contributions to predictive modeling and data science. His ability to bridge the gap between academic theory and industry application has had a lasting influence on both fields. Looking ahead, Dr. Sobbouhi is expected to continue making groundbreaking advancements in predictive analytics, particularly in the integration of AI and machine learning into real-world applications. His future research will likely shape the development of new predictive tools, influencing a wide range of industries for years to come.

Notable Publications  📑 

A novel predictor for areal blackout in power system under emergency state using measured data
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025
A novel SVM ensemble classifier for predicting potential blackouts under emergency condition using on-line transient operating variables
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025 (April issue)
Transient stability improvement based on out-of-step prediction
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Transient stability prediction of power system; a review on methods, classification and considerations
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Online synchronous generator out-of-step prediction by electrical power curve fitting
    • Authors: Alireza Sobbouhi (main author)
    • Journal: IET Generation, Transmission and Distribution
    • Year: 2020
Online synchronous generator out-of-step prediction by ellipse fitting on acceleration power – Speed deviation curve
    • Authors: Alireza Sobbouhi (main author)
    • Journal: International Journal of Electrical Power and Energy Systems
    • Year: 2020

Omar Haddad | Artificial Intelligence | Best Researcher Award

Dr. Omar Haddad l Artificial Intelligence | Best Researcher Award

MARS Research Lab, Tunisia

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Omar Haddad began his academic journey with a solid foundation in mathematics, earning his Bachelor in Mathematics from Mixed High School, Tataouine North, Tunisia, in 2008. Building on this, he pursued a Fundamental License in Computer Science at the Faculty of Sciences of Monastir, University of Monastir, Tunisia, graduating with honors in 2012. He further honed his skills in advanced topics through a Research Master in Computer Science specializing in Modeling of Automated Reasoning Systems (Artificial Intelligence) at the same institution, completing his thesis on E-Learning, NLP, Map, and Ontology in 2016. This laid the groundwork for his doctoral studies in Big Data Analytics for Forecasting Based on Deep Learning, which he completed with highest honors at the Faculty of Economics and Management of Sfax, University of Sfax, Tunisia, in 2023.

💼 Professional Endeavors

Currently, Dr. Haddad is an Assistant Contractual at the University of Sousse, Tunisia, where he contributes to the academic and technological growth of the institution. He is a dedicated member of the MARS Research Laboratory at the University of Sousse, where he collaborates on cutting-edge projects in Artificial Intelligence and Big Data Analytics. His professional expertise extends to teaching across various levels, including preparatory, license, engineer, and master levels, with over 2,000 hours of teaching experience in state and private institutions.

📚 Contributions and Research Focus

Dr. Haddad’s research spans several transformative domains, including:

  • Artificial Intelligence (AI) and its application in solving complex problems.
  • Machine Learning (ML) and Deep Learning (DL) for advanced predictive modeling.
  • Generative AI and Large Language Models (LLMs) for innovation in Natural Language Processing (NLP).
  • Big Data Analytics for informed decision-making and forecasting.
  • Computer Vision for visual data interpretation and insights.

He has published three significant contributions in Q1 and Q2 journals and participated in Class C conferences, highlighting his commitment to impactful and high-quality research.

🌟 Impact and Influence

As a peer reviewer for prestigious journals like The Journal of Supercomputing, Journal of Electronic Imaging, SN Computer Science, and Knowledge-Based Systems, Dr. Haddad ensures the integrity and quality of academic contributions in his field. His work has influenced a diverse range of domains, from computer science education to applied AI, establishing him as a thought leader in his areas of expertise.

🛠️ Technical Skills

Dr. Haddad possesses a robust set of technical skills, including:

  • Proficiency in Deep Learning frameworks and Big Data tools.
  • Expertise in programming languages such as Python and C.
  • Knowledge of Database Engineering and algorithms.
  • Application of Natural Language Processing (NLP) in academic and industrial projects.

👨‍🏫 Teaching Experience

Dr. Haddad has an extensive teaching portfolio, covering a wide range of topics:

  • Database Engineering, Algorithms, and Programming, taught across license and engineer levels.
  • Advanced topics such as Big Data Frameworks, Foundations of AI, and Object-Oriented Programming.
  • Specialized courses on Information and Communication Technologies in Teaching and Learning.

His dedication to education is evident in his ability to adapt teaching strategies to different academic levels and institutional needs.

🏛️ Legacy and Future Contributions

Dr. Haddad’s legacy lies in his ability to bridge academia and industry through innovative research and teaching. As he continues to expand his expertise in Generative AI and LLMs, his future contributions will likely shape the next generation of intelligent systems and predictive analytics. His goal is to inspire students and researchers to harness the transformative potential of AI and Big Data to address global challenges.

🌐 Vision for the Future

Dr. Omar Haddad envisions a future where AI and Big Data technologies are seamlessly integrated into various sectors to enhance decision-making, foster innovation, and empower global communities. By combining his teaching, research, and technical skills, he aims to leave a lasting impact on the academic and technological landscape.

📖 Top Noted Publications
Toward a Prediction Approach Based on Deep Learning in Big Data Analytics
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Neural Computing and Applications
    • Year: 2022
A Survey on Distributed Frameworks for Machine Learning Based Big Data Analysis
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Proceedings of the 21st International Conference on New Trends in Intelligent Software Systems
    • Year: 2022
An Intelligent Sentiment Prediction Approach in Social Networks Based on Batch and Streaming Big Data Analytics Using Deep Learning
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Social Network Analysis and Mining
    • Year: 2024
Big Textual Data Analytics Using Transformer-Based Deep Learning for Decision Making
    • Authors: O. Haddad, M.N. Omri
    • Journal: Proceedings of the 16th International Conference on Computational Collective Intelligence
    • Year: 2024

Feng Hu | Multi-modal feature recognition | Best Researcher Award

Assoc Prof Dr. Feng Hu l Multi-modal feature recognition | Best Researcher Award

Communication University of China, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Assoc. Prof. Dr. Feng Hu’s academic journey began with a deep interest in communication and information systems. He earned his Ph.D. in Communication and Information Systems from the prestigious Communication University of China (CUC), Beijing, in 2013. This educational foundation set the stage for his distinguished career in the fields of wireless communications, media convergence, and related technologies, shaping his future research and academic contributions.

Professional Endeavors and Contributions 🌐

Dr. Feng Hu is a prominent figure in the domain of 5G/6G wireless communications, and his professional journey has been marked by several key roles. Since December 2018, he has been an Associate Professor at Communication University of China and a master tutor, where he plays a significant role in mentoring future engineers and researchers. He has also been an active member of the Working Group of Radio, Film, and Television Administration for Wireless Interactive Radio and Television, as well as a member of the Working Group of 5G Broadcast. These positions have allowed him to contribute to the development and regulation of cutting-edge technologies in the media and communications sector.

Research Focus and Impact 🔬

Dr. Hu’s research interests lie in the development of transmitting and receiving techniques for 5G and 6G wireless communications. His work focuses on optimizing wireless communication systems, utilizing machine learning, and exploring optimization theory to enhance the efficiency and performance of modern communication technologies. His research has significant implications for the advancement of wireless communication systems, contributing to the global transition to next-generation technologies and improving communication capabilities in various sectors.

Technical Skills and Expertise ⚙️

Dr. Hu is highly skilled in the areas of wireless communications, machine learning, and optimization theory. His expertise includes developing novel algorithms and techniques for 5G/6G systems, addressing challenges in data transmission, signal processing, and system optimization. He is proficient in applying advanced mathematical models and machine learning approaches to improve communication systems’ performance, reliability, and security, making him a key player in advancing the state-of-the-art in wireless communications.

Teaching Experience and Mentorship 🍎

As an Associate Professor and master tutor, Dr. Hu is deeply involved in shaping the next generation of professionals in communication and information systems. He has taught a variety of undergraduate and graduate-level courses, imparting his knowledge in wireless communications, machine learning, and optimization. His mentorship extends beyond the classroom, guiding students in research and academic pursuits, while fostering a culture of innovation and critical thinking in the field of communications.

Legacy and Future Contributions 🌱

Dr. Hu’s legacy is rooted in his pioneering work in the development of 5G/6G wireless communication systems and his significant contributions to the academic and professional communities. Looking ahead, he aims to continue pushing the boundaries of wireless communication technologies, with a particular focus on optimizing next-generation communication networks and integrating machine learning approaches to improve system efficiencies. His future contributions will likely influence both academic research and practical implementations in the rapidly evolving fields of wireless communications and media convergence.

Academic Citations and Recognition 🏆

Dr. Feng Hu’s research has garnered recognition in top-tier academic journals and conferences in the fields of communication systems and wireless technology. His work has not only contributed to the scientific community but has also influenced industry practices and standards in wireless communication. He continues to be a sought-after figure in academic circles, providing valuable insights into the development of 5G/6G systems and machine learning applications in communications.

Professional Affiliations and Leadership 🌍

Dr. Hu is an active member of several esteemed organizations, including IEEE and the Society of Communications, where he holds the prestigious title of Senior Member. His involvement in key working groups related to wireless interactive radio and television and 5G broadcast further highlights his leadership in shaping the future of communication technologies. These affiliations enhance his ability to drive impactful research and contribute to the global dialogue on the future of communication systems.

Future Outlook and Innovation 🚀

With his vast expertise in wireless communication systems and emerging technologies, Dr. Hu’s future endeavors will focus on leading innovations in 6G communication systems, integrating artificial intelligence and machine learning to enhance system performance, and tackling the challenges posed by next-generation wireless networks. His ongoing research will play a critical role in shaping the future of global communication, advancing both academic theory and practical applications in the field.

 Top Noted Publications 📖

SDDA: A progressive self-distillation with decoupled alignment for multimodal image–text classification

Authors: Chen, X., Shuai, Q., Hu, F., Cheng, Y.
Journal: Neurocomputing
Year: 2025

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Authors: Zhang, X., Ba, X., Hu, F., Yuan, J.
Journal: Sensors
Year: 2024

 Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

Authors: Hu, F., Zhang, H., Chen, S., Zhang, J., Feng, Y.
Journal: IET Communications
Year: 2024

Real-Time Multi-Service Adaptive Resource Scheduling Algorithm Based on QoE

Authors: Li, W., Li, S., Hu, F., Yin, F.
Conference: 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
Year: 2024

5G RAN Slicing Resource Allocation Based on PF/M-LWDF

Authors: Hu, F., Qiu, J., Chen, A., Yang, H., Li, S.
Conference: 2024 4th International Conference on Computer Communication and Artificial Intelligence, CCAI 2024
Year: 2024

Xueliang Han | Business Intelligence and Analytics | Best Researcher Award

Assoc Prof Dr. Xueliang Han | Business Intelligence and Analytics | Best Researcher Award

Henan University of Economics and Law, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Dr. Xueliang Han’s educational journey began at Henan University of Finance and Economics, where he earned his Bachelor’s degree in Economics from the School of International Economics and Trade in 2009. He then pursued a Master of Business Administration (MBA) at Jinan University School of Management, completing his degree in 2012. This solid foundation laid the groundwork for his PhD in Management from the same university in 2016. Dr. Han’s academic training has shaped his deep understanding of organizational behavior, strategy, and the complexities of family business management.

Professional Endeavors 💼

Dr. Han’s professional career has been marked by a blend of academic excellence and practical experience. Since 2016, he has been an Associate Professor at the School of Business Administration, Henan University of Finance and Economics. His role involves not only teaching but also guiding postgraduate students as a tutor. He has contributed significantly to various national and provincial-level research projects, which underscores his engagement with both academic research and industry trends. Before his academic career, Dr. Han worked at China Life Insurance Co., Ltd. from 2012 to 2013, gaining valuable practical insights into business management.

Contributions and Research Focus 📚

Dr. Han’s research interests revolve around organizational strategy, organizational behavior, and family business theory. He has conducted several groundbreaking studies in these areas, particularly on the dynamics of family businesses in China. His work bridges the gap between theory and practice, offering insights into how organizations, particularly family-run enterprises, can thrive in the competitive business environment. His research has been published in prestigious journals such as Management Review, Psychology Science, and Foreign Economics and Management, highlighting his reputation as a thought leader in his field.

Impact and Influence 🌍

Dr. Han has made a significant impact through his academic contributions, winning numerous awards. His paper received the Mao Lixiang Outstanding Paper Award for Family Business Research and the Annual Outstanding Paper Award from the Management Thought and Business Ethics Professional Committee of the China Management Modernization Research Association. Additionally, his monograph and co-published works have been recognized, further solidifying his reputation in academic circles. His involvement in consulting, especially on industrial transformation and technology innovation, shows his broader influence beyond academia.

Academic Cites 📑

Dr. Han’s research has garnered substantial attention in the academic community. His publications in high-quality journals such as Management Review and Foreign Economics and Management have earned him citations from peers worldwide. This reflects the importance of his work, particularly in the domains of organizational strategy and family business studies. His contributions to the field have helped shape how these areas are understood and applied, both in China and internationally.

Technical Skills 🖥️

Dr. Han possesses a diverse set of technical skills essential for his academic and research endeavors. He has led national-level projects, participated in social and natural science research, and collaborated with various academic and governmental bodies. His knowledge extends into business intelligence, data management, and technological innovations in management systems, making him well-versed in the evolving landscape of business technology.

Teaching Experience 📚👨‍🏫

As a seasoned educator, Dr. Han has taught a variety of courses at Henan University of Finance and Economics. His courses include “Organizational Theory and Organizational Behavior,” “Enterprise Strategic Management,” and “Entrepreneurship and Wealth Inheritance.” He is known for integrating cutting-edge research with practical applications, providing his students with a comprehensive understanding of management theory and its real-world implications. His teaching methods are praised for being interactive, research-oriented, and deeply grounded in both theory and practice.

Legacy and Future Contributions 🔮

Dr. Han’s legacy as an educator and researcher is evident in his awards and the lasting impact of his work. His future contributions are expected to continue shaping the fields of organizational behavior and family business research. He remains committed to advancing knowledge through his academic pursuits and mentoring the next generation of business leaders. With ongoing involvement in key research projects and educational initiatives, Dr. Han’s work will likely influence future management practices in both academic and corporate environments.

Top Noted Publications 📖

 Mitigate cross-market competition caused by the risk of uncertainty and improve firm performance through business intelligence
  • Authors: Han, X., Lin, T.X., Wang, X.
  • Journal: Heliyon
  • Year: 2024
BI&A capability: A discussion on the mechanism of enterprise’s performance improvement
  • Authors: Han, X., Wu, H.
  • Conference: ACM International Conference Proceeding Series
  • Year: 2019

Biying Fu | Machine Learning Applications | Best Researcher Award

Dr. Biying Fu | Machine Learning Applications | Best Researcher Award

Hochschule RheinMain, Germany

Professional Profile👨‍🎓

Early Academic Pursuits 📚

Dr. Biying Fu’s academic journey began with her primary and secondary education in Shanghai, China, where she developed a strong foundation in subjects like mathematics, German, English, physics, and chemistry. Her academic excellence continued through high school, culminating in an outstanding Abitur score of 1.1. She pursued a Bachelor’s degree in Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (KIT), Germany, followed by a Master’s degree with a focus on Communications and Information Technology. Dr. Fu’s academic pursuits further advanced with a Ph.D. from the Technical University of Darmstadt (TUda), where she specialized in sensor applications for human activity recognition in smart environments.

Professional Endeavors 💼

Dr. Fu’s professional career began at the Fraunhofer Institute for Integrated Circuits (IGD), where she contributed significantly to the Sensing and Perception group. Over time, she expanded her expertise into the Smart Living and Biometric Technologies department, becoming a scientific employee and project leader. Her roles included innovative work on smart environments, human activity recognition, and biometric technologies. Dr. Fu has been instrumental in creating real-world applications for sensor technologies and machine learning algorithms, with notable contributions to the Smart Floor project, which focuses on indoor localization and emergency detection in ambient assisted living environments.

Contributions and Research Focus 🔬

Dr. Fu’s research has been centered around smart environments, sensor systems, and human activity recognition. Her dissertation, titled “Sensor Applications for Human Activity Recognition in Smart Environments,” examined multimodal sensor systems, including capacitive sensors, accelerometers, and smartphone microphones, for tracking physical activities and indoor localization. Her work merges signal processing, neural networks, and data generation techniques to enhance the interaction between people and machines. Her ongoing research continues to explore the intersection of artificial intelligence and explainability, contributing to the development of transparent and interpretable machine learning models.

Impact and Influence 🌍

Dr. Fu’s research in smart technologies has far-reaching implications for assistive technologies, healthcare, and the development of intuitive human-machine interactions. Her contributions to the field of human activity recognition have improved how we use sensors to monitor and analyze daily activities in smart homes and health environments. Furthermore, her involvement in interdisciplinary projects, such as optical quality control and optical medication detection, has enhanced industrial applications of computer vision and machine learning.

Academic Cites and Recognition 📖

Dr. Fu has earned recognition in both academia and industry. Her dissertation, publications, and research projects have attracted attention in top conferences and journals. Her participation in global programs like the Summer School of Deep Learning and Reinforcement Learning at the University of Alberta further emphasizes her standing in the scientific community. Additionally, Dr. Fu has been an active participant in various educational and research initiatives, such as the REQUAS project, and she continues to serve as a professor at Hochschule RheinMain, where she focuses on the emerging field of Explainable AI.

Technical Skills ⚙️

Dr. Fu possesses advanced technical skills in various programming languages, including C/C++, Java, and Python. She is highly proficient in machine learning libraries such as Scikit-Learn, TensorFlow, Keras, and PyTorch, and has hands-on experience with simulation tools like Matlab/Simulink and CST Microwave Studio. Her expertise extends to signal processing, computer vision, and the use of embedded systems for smart applications. Additionally, Dr. Fu has a strong command of version control tools like GIT and SVN, as well as project management platforms such as JIRA and SCRUM.

Teaching Experience 👩‍🏫

Dr. Fu has contributed to the academic development of students through various teaching roles. She has served as a tutor for subjects like digital technology and wave theory during her time at KIT. As a professor at Hochschule RheinMain, she currently teaches courses in smart environments, with a focus on advanced topics in Explainable AI. Her ability to communicate complex concepts clearly and her passion for fostering intellectual curiosity have made her a respected educator in her field.

Legacy and Future Contributions 🌟

Dr. Fu’s work continues to shape the future of smart environments, human-machine interactions, and explainable AI. Her research on sensor technologies and machine learning has paved the way for smarter and more intuitive technologies in healthcare, industry, and everyday life. As she continues to contribute to both academic and industry advancements, Dr. Fu’s legacy will be marked by her dedication to the development of technologies that improve human well-being and promote transparency in artificial intelligence systems. Her ongoing contributions will continue to inspire the next generation of researchers and engineers.

📖Top Noted Publications

A Survey on Drowsiness Detection – Modern Applications and Methods

Authors: Biying Fu, Fadi Boutros, Chin-Teng Lin, Naser Damer

Journal: IEEE Transactions on Intelligent Vehicles

Year: 2024

Generative AI in the context of assistive technologies: Trends, limitations and future directions

Authors: Biying Fu, Abdenour Hadid, Naser Damer

Journal: Image and Vision Computing

Year: 2024

Biometric Recognition in 3D Medical Images: A Survey

Authors: Biying Fu, Naser Damer

Journal: IEEE Access

Year: 2023

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Authors: Biying Fu, Naser Damer

Journal: IET Biometrics

Year: 2022

Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-Adaption and Few-Shot Learning

Authors: Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

Journal: Book chapter

Year: 2021

Jing An | Artificial Intelligence | Best Researcher Award

Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Haixia Mao | Data Science | Best Researcher Award

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

Hend ALnajjar | Artificial Intelligence | Best Researcher Award

Assoc Prof Dr. Hend ALnajjar, Artificial Intelligence, Best Researcher Award

Assoc Prof Dr. Hend ALnajjar at king Saud bin Abdulaziz for health science, Saudi Arabia

Professional Profile

Scopus Profile
Orcid  Profile
Research Gate Profile
Google Scholar Profile

🌟Summary

Dr. Hend Abdu Alnajjar is an accomplished Associate Professor in Pediatric Nursing at the College of Nursing–Jeddah, King Saud bin Abdulaziz University for Health Sciences. With a robust educational background including a Ph.D. in Nursing from Manchester University and extensive experience in nursing education, she specializes in maternal and child health, healthcare quality, and academic leadership.

🎓Education

  • Doctor of Philosophy in Nursing, Manchester University, UK (November 2012)
  • MSc in Advanced Nursing Studies, Manchester University, UK (November 2008)
  • Master of Medical Education, College of Medicine, King Saud bin Abdulaziz University for Health Sciences (2017-2019)
  • Bachelor of Science in Nursing, King Abdulaziz University, Jeddah, KSA (September 2000)

💼 Professional Experience

Dr. Hend Abdu Alnajjar brings a wealth of expertise as an Associate Professor in Pediatric Nursing at the College of Nursing–Jeddah, King Saud bin Abdulaziz University for Health Sciences. With a distinguished career spanning leadership roles such as Dean of the College of Nursing – Jeddah and Associate Dean of Academic & Student Affairs, she has significantly contributed to advancing nursing education and healthcare quality in Saudi Arabia. Dr. Alnajjar’s leadership extends to extensive involvement in accreditation processes, curriculum development, and quality assurance initiatives, enhancing educational standards across multiple institutions. Her commitment to maternal and child health is underscored by her clinical background in neonatal intensive care units, further enriching her academic and practical contributions to the nursing profession.

🔬 Research Interests

Dr. Hend Abdu Alnajjar’s research interests are focused on pivotal areas within nursing and healthcare. Her primary scholarly pursuits revolve around maternal and child health, where she explores innovative approaches to improve healthcare outcomes for mothers and children. Additionally, her research encompasses nursing education, aiming to enhance teaching methodologies and curriculum frameworks to foster competent nursing professionals. Dr. Alnajjar is also passionate about healthcare quality, investigating strategies to optimize patient care delivery and safety within clinical settings. Her academic leadership in these domains reflects a commitment to advancing nursing practice and education both locally and globally.

📖 Publication Top Noted

Article title: Digital proficiency: assessing knowledge, attitudes, and skills in digital transformation, health literacy, and artificial intelligence among university nursing students

    • Authors: Ebtsam Aly Abou Hashish, Hend Alnajjar
    • Journal: BMC Medical Education
    • Volume: 24
    • Pages: 508
    • Year: 2024

Article title: Perception of the accreditation of the National Commission for Academic Accreditation and assessment at different health colleges in Jeddah, Saudi Arabia

    • Authors:Ali S Al-Shareef, Mansour A AlQurashi, Azza Al Jabarti, Hend Alnajjar, Ahmad A Alanazi, Mohamed Almoamary, Bader Shirah, Khalid Alqarni
    • Journal: Cureus
    • Volume: 15
    • Year: 2023

Article title: Managerial power bases and its relationship to influence tactics and conflict management styles: Bedside nurses’ perspective

    • Authors: Ebtsam Abou Hashish, Hend Alnajjar, Arwa Al Saddon
    • Journal: Worldviews on Evidence‐Based Nursing
    • Volume: 20
    • Issue: 5
    • Year: 2023

Article title: Exploring the relationship between leadership and conflict management styles among nursing students

    • Authors: Hend Alnajjar, Ebtsam Abou Hashish
    • Journal: Nursing management
    • Volume: 29
    • Issue: 3
    • Year: 2022

Article title: Academic ethical awareness and moral sensitivity of undergraduate nursing students: assessment and influencing factors

    • Authors: Hend Abdu Alnajjar, PhD, Ebtsam Aly Abou Hashish, PhD
    • Journal: SAGE open nursing
    • Volume: 7
    • Year: 2021