Xin Su | Temporal Data Patterns | Best Researcher Award

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Assoc Prof Dr. Xin Su | Temporal Data Patterns | Best Researcher Award

Wuhan University | China

Publication Profile

Google Scholar

EARLY ACADEMIC PURSUITS 📚

Dr. Xin Su’s academic journey began with his pursuit of a Ph.D. at TĂ©lĂ©com ParisTech, where his foundational work in remote sensing and computer vision laid the groundwork for his later breakthroughs. His early research on multi-temporal image processing set the stage for his significant contributions in the field.

PROFESSIONAL ENDEAVORS đŸ’Œ

Following his postdoctoral research at INRIA, Dr. Su took on the role of Associate Professor at Wuhan University. Over the years, his research has expanded into disaster management and urban development, where he has actively led projects with direct applications for societal benefit.

CONTRIBUTIONS AND RESEARCH FOCUS  ON Temporal Data Patterns🌍

Dr. Su’s most significant contributions are in multi-temporal remote sensing change detection and classification mapping. His research has had tangible effects in managing natural disasters, such as mapping the 2022 Henan flood and the 2023 Turkey earthquake. His focus on extracting actionable information from remote sensing data has provided critical insights for emergency responses and urban development.

IMPACT AND INFLUENCE 🌏

Dr. Su’s research has influenced not only academic thought but also practical applications in various industries. His involvement in projects funded by the National Natural Science Foundation of China has provided the government with tools for urban monitoring, disaster management, and land-use planning.

ACADEMIC CITATIONS 📈

With over 1,000 citations to his work, Dr. Su has garnered recognition for his research, with more than 40 SCI papers published in top-tier journals. His research contributions have significantly advanced the fields of remote sensing and computer vision, ensuring their practical use in tackling global challenges.

LEGACY AND FUTURE CONTRIBUTIONS 🔼

Dr. Xin Su is poised to leave a lasting legacy in the fields of remote sensing and artificial intelligence. His ongoing research, particularly in urban development and disaster management, will continue to shape the future of environmental monitoring and response strategies.

KEY RESEARCH FOCUS 🔍

  • Remote sensing image processing
  • Multi-temporal remote sensing information extraction
  • Computer vision applications in disaster response and urban planning

COLLABORATIONS AND PARTNERSHIPS đŸ€

Dr. Su collaborates with esteemed researchers like Prof. Florence TUPIN (Telecom ParisTech), Prof. Christine GUILLEMOT (INRIA), and others at Wuhan University, including Prof. Liangpei Zhang and Prof. Qiangqiang Yuan, to push the boundaries of remote sensing research.

PROFESSIONAL MEMBERSHIPS 🏅

  • IEEE Member
  • CSIG (China Society of Image and Graphics) Member

AWARD CATEGORY PREFERENCE 🏆

Dr. Su has applied for the Best Researcher Award, underscoring his groundbreaking contributions to remote sensing and AI-driven applications in environmental monitoring and urban planning.

TOP NOTES PUBLICATIONS 📚

Satellite video super-resolution via multiscale deformable convolution alignment and temporal grouping projection
    • Authors: Y Xiao, X Su, Q Yuan, D Liu, H Shen, L Zhang
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Year: 2021
Cloud removal with fusion of high resolution optical and SAR images using generative adversarial networks
    • Authors: J Gao, Q Yuan, J Li, H Zhang, X Su
    • Journal: Remote Sensing
    • Year: 2020
A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery
    • Authors: H Guo, B Du, L Zhang, X Su
    • Journal: ISPRS Journal of Photogrammetry and Remote Sensing
    • Year: 2022
Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer
    • Authors: Y Xiao, Q Yuan, J He, Q Zhang, J Sun, X Su, J Wu, L Zhang
    • Journal: International Journal of Applied Earth Observation and Geoinformation
    • Year: 2022
Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images
    • Authors: X Su, CA Deledalle, F Tupin, H Sun
    • Journal: Geoscience and Remote Sensing, IEEE Transactions on
    • Year: 2014
DymSLAM: 4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation
    • Authors: C Wang, B Luo, Y Zhang, Q Zhao, L Yin, W Wang, X Su, Y Wang, C Li
    • Journal: IEEE Robotics and Automation Letters
    • Year: 2020

Zuleika Suliman | Artificial Intelligence | Best Researcher Award

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Ms. Zuleika Suliman | Artificial Intelligence | Best Researcher Award

University of South Africa | South Africa

BIOGRAPHY OF MS. ZULEIKA SULIMAN đŸ“šđŸ‘©â€đŸ«

INTRODUCTION

Ms. Zuleika Suliman is a dynamic and passionate educator, deeply committed to enhancing the learning experience through innovative teaching strategies, student-centered approaches, and cutting-edge technology. She holds an MA in English Studies from the University of South Africa (UNISA), where she also completed a wide array of specialized training programs. Ms. Suliman’s career in academia spans over a decade, marked by her significant contributions to teaching, research, and student mentorship in the fields of English studies, education, and e-learning.

EARLY ACADEMIC PURSUITS 🎓

Ms. Suliman’s academic journey began at the University of Pretoria, where she earned her Bachelor’s Degree in English Studies, specializing in Arabic, Journalism, TESOL, and Language Editing. Building on her academic foundation, she later pursued her Honours Degree in English Literature and Language at the University of South Africa (UNISA), culminating in her current studies for a Master’s Degree in English Studies, which she is set to complete in 2025. Her early years were marked by a fervent passion for education, as she excelled in mathematics, science, Arabic, and language arts during her school years at Pretoria Muslim School.

PROFESSIONAL ENDEAVORS đŸ«

Ms. Suliman’s professional career includes her current role as a Junior Lecturer at UNISA, where she not only teaches various English courses but also leads several significant academic projects, including an AI research initiative with publications. She has a proven track record of success, managing large groups of students—over 5000 students for first-year courses and 600 for postgraduate modules. Her role as a mentor, editor of departmental newspapers, and active member of various academic committees showcases her dedication to the academic community.

Ms. Suliman has a vast experience with the development of curriculum materials, tutorials, assessments, and online resources for her students. Her efforts extend beyond traditional teaching to creating dynamic, virtual learning environments using tools like Microsoft Teams, Moodle, podcasts, and other digital resources.

CONTRIBUTIONS AND RESEARCH FOCUS ON  ARTIFICIAL INTELLIGENCE🔬

Her research focuses on exploring innovative e-learning strategies to improve workplace English competence, specifically within Open Distance and eLearning (ODeL) environments in South Africa. As she continues her PhD in Applied English Language Studies, her research aims to influence the way online education is delivered, providing valuable insights into student engagement, experience, and learning outcomes in digital learning platforms.

Her contributions to education include mentoring research projects, supporting student academic progress, and reviewing journal articles. She has been instrumental in shaping programs that improve student retention and success in online learning contexts.

IMPACT AND INFLUENCE 🌍

Ms. Suliman’s student-centered approach and focus on leveraging e-learning technologies have significantly impacted her students’ educational journeys. Through her development of online content, tutorials, livestream sessions, and the creation of interactive learning experiences, she has enhanced student engagement, knowledge retention, and overall academic success. She promotes collaboration, teamwork, and open communication, both with her students and peers.

Her mentorship extends to various projects, including the Can Themba Festival and a student support initiative, where she has worked tirelessly to promote student well-being, academic excellence, and career development.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Ms. Suliman has contributed to the academic community with numerous research papers and publications. Her research on the integration of AI in education and its impact on student performance has been well-received in both academic circles and professional networks. She continues to collaborate with colleagues to publish findings and present at academic conferences, focusing on the advancement of educational methodologies in the 21st century.

HONORS & AWARDS 🏆

Ms. Suliman’s achievements have not gone unnoticed. She has received several accolades throughout her career, including:

  • Scholarship Program at the University of Pretoria for the BSc undergraduate course “Up with Science” Program.
  • Mont Blanc Award for Writing – Explorer Program in Literature.
  • Sunday Times Rising Star Achievement – Youth Development.
  • Graduate of the Mentorship Program at UNISA.

Her passion and dedication to her work have earned her recognition within both the academic and professional realms.

FINAL NOTE 📝

As a trailblazer in the field of education, Ms. Zuleika Suliman continues to inspire and impact the lives of countless students. Her journey, from a young learner to an accomplished academic, reflects her unwavering commitment to education. Through her innovative teaching methods, research, and mentoring, she is shaping the future of education in South Africa and beyond.

LEGACY AND FUTURE CONTRIBUTIONS 🌟

Looking ahead, Ms. Suliman is determined to leave a lasting legacy in the field of education by further enhancing online learning strategies, improving digital literacy, and fostering a global academic community that is both inclusive and engaging. Her future contributions will continue to focus on research in applied English language studies, the integration of technology in education, and the development of future generations of learners and educators.

TOP NOTES PUBLICATIONS 📚

Advancing students’ academic excellence in distance education: Exploring the potential of generative AI integration to improve academic writing skills
    • Authors: KB Maphoto, K Sevnarayan, NE Mohale, Z Suliman, TJ Ntsopi
    • Journal: Open Praxis
    • Year: 2024
Continuing professional development (CPD): a necessary component in the workplace or not?
    • Authors: Z Suliman, W Kruger, JA Pienaar
    • Journal: The Journal of Medical Laboratory Science and Technology of South Africa
    • Year: 2020
The interconnectedness between Ubuntu principles and generative artificial intelligence in distance higher education institutions
    • Authors: Z Suliman, NE Mohale, KB Maphoto, K Sevnarayan
    • Journal: Discover Education
    • Year: 2024
Exploring the Impact of E-Learning Strategies on Enhancing Workplace English Competence at an Open Distance E-Learning (ODeL) University in South Africa
    • Authors: KB Maphoto, Z Suliman
    • Journal: Research in Social Sciences and Technology
    • Year: 2024
Artificial intelligence or augmented intelligence? Experiences of lecturers and students in an ODeL university
    • Authors: NE Mohale, Z Suliman, K Maphoto, K Sevnarayan, D Mokoena, TJ Ntsopi
    • Journal: Acitya: Journal of Teaching and Education
    • Year: 2024
The Nexus of Business English and the Fourth Industrial Revolution: Leveraging Moodle’s Potential to Augment Lecturers’ Pedagogies for Student Support
    • Authors: K Sevnarayan, Z Suliman
    • Journal: Scrutiny2
    • Year: 2024

Omar Haddad | Artificial Intelligence | Best Researcher Award

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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.

đŸ’Œ 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.

đŸ› ïž 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.

đŸ‘šâ€đŸ« 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.

đŸ›ïž 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

Aleksey Tashkinov | Educational Data Analysis | Best Researcher Award

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Mr. Aleksey Tashkinov l Educational Data Analysis | Best Researcher Award

Perm National Research Polytechnic University, Russia

Author Profile

Google Scholar

Early Academic Pursuits 🎓

Mr. Tashkinov Aleksey began his academic journey with a strong foundation in economic sciences, ultimately earning his designation as a Candidate of Economic Sciences. His early academic pursuits focused on developing theoretical models and conceptual approaches to economic systems, particularly in production management and organizational change in the digital era. This initial exploration laid the groundwork for his ongoing contributions to the academic field, with a focus on integrating traditional economic concepts with emerging technological advancements like digital transformation and lean manufacturing.

Professional Endeavors đŸ’Œ

As an Associate Professor at Perm National Research Polytechnic University, Mr. Tashkinov has demonstrated his professional expertise through teaching and research. His role extends beyond just academia, having been directly involved in consultancy and industry projects that bridge the gap between theoretical knowledge and real-world application. His experience in the implementation of lean methodologies, digital production systems, and project management techniques has been pivotal in shaping the strategies of numerous enterprises in the industrial sector, particularly in the context of digital transformation.

Contributions and Research Focus 🔍

Mr. Tashkinov’s research focus is centered around enterprise management, lean manufacturing, and the economics of digital transformation. He explores how industries can adapt to modern challenges through the implementation of Industry 4.0 principles and digital tools. His work on digital transformation strategies, quality systems, and active manufacturing systems is of particular significance in understanding how enterprises can thrive in a rapidly changing technological landscape. Through his collaborative efforts with students, faculty, and industry leaders, he continues to make notable contributions to the academic community and beyond.

Impact and Influence 🌍

Mr. Tashkinov’s contributions have a wide-reaching impact on both academic theory and industrial practice. His research on lean manufacturing and digital production has influenced the strategies adopted by many enterprises, helping them transition to more efficient, innovative, and sustainable business models. By providing actionable insights into the integration of digital tools and manufacturing technologies, he has positively affected the operational efficiency and management practices within a variety of industries.

Academic Cites 📚

With a Hirsch index of 7, Mr. Tashkinov’s work has been cited extensively in academic journals and industry publications. His notable papers on the role of artificial intelligence in lean manufacturing, the development of digital strategies for industrial enterprises, and the transformation of production management systems highlight his academic impact. His published works in leading journals like Discover Artificial Intelligence and International Journal of Management Trends underscore the significance of his research in the evolving field of industrial economics and management.

Technical Skills ⚙

Mr. Tashkinov has honed an impressive array of technical skills that complement his academic expertise. He is proficient in digital manufacturing, lean technologies, and project management tools that are vital in guiding enterprises through digital transformation. His knowledge extends to cutting-edge technologies such as artificial intelligence and virtual reality, which he integrates into real-world management solutions. These technical skills are essential for his work in academia, consultancy, and industry projects, where he leads initiatives aimed at enhancing operational efficiency through digital means.

Teaching Experience đŸ‘šâ€đŸ«

With years of teaching experience, Mr. Tashkinov has become a key educator at Perm National Research Polytechnic University. He plays an integral role in mentoring students, helping them develop the skills and critical thinking necessary for success in the field of economics and industrial management. His pedagogical approach is rooted in practical experience, often involving students in real-world projects and case studies to provide them with a comprehensive understanding of the challenges and opportunities in digital transformation and enterprise management.

Legacy and Future Contributions đŸŒ±

As an academic and researcher, Mr. Tashkinov is committed to leaving a lasting legacy in the fields of economics and industrial production management. His future contributions will likely focus on the further integration of digital tools in enterprise management, especially as industries continue to evolve in response to digital transformation. He envisions a future where his work continues to inspire the next generation of researchers, practitioners, and industry leaders to explore new ways to enhance productivity, innovation, and sustainability in industrial settings.

Collaboration and Industry Engagement đŸ€

Mr. Tashkinov is dedicated to fostering collaborations with both academic peers and industry leaders. His research is highly collaborative, with numerous joint projects involving students, faculty, and professionals from diverse sectors. These collaborations are critical to ensuring that his research addresses real-world challenges and remains relevant to current industry needs. His active engagement with the industrial sector also provides valuable opportunities for knowledge transfer, ensuring that the latest research findings are effectively applied to improve operational performance.

Professional Memberships and Recognition 🏅

Mr. Tashkinov’s professional standing is further bolstered by his membership in several prestigious academic and professional organizations related to economics, industrial production, and digital transformation. These memberships provide him with access to a global network of experts and a platform to share his research with an international audience. His contributions have been recognized by various academic and industry bodies, affirming his reputation as a leader in his field.

Top Noted Publications 📖

Theoretical and methodological foundations of the process approach to management in an industrial enterprise
    • Authors: AG Tashkinov
    • Journal: Bulletin of Perm University. Series: Economics
    • Year: 2014
Strategically Oriented Budgeting in an Industrial Enterprise: A Methodological Approach
    • Authors: AG Tashkinov
    • Journal: Bulletin of Perm University. Series: Economics
    • Year: 2013
The Impact of Integrated Lean Manufacturing Implementation on the Efficiency of Enterprise Production System Development
    • Authors: AG Tashkinov
    • Journal: Bulletin of Perm National Research Polytechnic University
    • Year: 2022
Change management mechanism in the development of production systems
    • Authors: VL Popov, AG Tashkinov
    • Journal: Economics and Entrepreneurship
    • Year: 2015
Development of a methodology for assessing the effectiveness of projects for developing an enterprise production system within the framework of an integrated management technology
    • Authors: NB Akatov, VL Popov, AG Tashkinov
    • Journal: Economics and Entrepreneurship
    • Year: 2016
Improving the mechanism of industrial enterprise management
    • Authors: VL Popov, AG Tashkinov
    • Journal: Bulletin of Perm National Research Polytechnic University
    • Year: 2016

yunhao zhao | Data Analysis Innovation | Best Researcher Award

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Assoc Prof Dr. yunhao zhao | Data Analysis Innovation | Best Researcher Award

Qingdao Huanghai University, China

Author Profile

Orcid 

🧑‍🎓 Early Academic Pursuits

Yunhao Zhao was Shandong, P.R. China. His academic journey began with a strong foundation in International Economics and Social Security studies, setting the stage for his future research. After completing his undergraduate education, he became an associate professor at Qingdao Huanghai University, where he also supervises undergraduate students. His quest for further knowledge continues as he pursues a Ph.D. at The Catholic University of Korea, focusing on the evolving fields of economics and social security.

đŸ‘šâ€đŸ« Professional Endeavors

Dr. Zhao’s academic career has been marked by significant contributions in the realms of data analysis and economic research. As an All-Media Operator and Associate Professor, he actively engages in both teaching and research at Qingdao Huanghai University. His dedication to advancing knowledge in the academic sphere extends to overseeing the academic progress of undergraduate students, ensuring they are equipped with the necessary skills and insights to excel in their respective fields.

📊 Contributions and Research Focus

Dr. Zhao’s primary research areas are data analysis, internet of things (IoT), and auction theory. His most notable work focuses on congestion control in IoT systems, where he applied auction theory to improve performance and efficiency. His research contributions are significant in their potential to drive forward the development of smarter and more efficient IoT networks. Furthermore, his work on energy consumption reduction demonstrates the real-world impact of his methods, achieving a remarkable 24.13% reduction in energy usage in experimental scenarios.

🌍 Impact and Influence

Dr. Zhao’s work has already made notable contributions to the global research community, evidenced by his publication in Scientific Reports (SCI) and recognition in high-impact journals. His research on IoT and auction theory has contributed to solving critical issues in technology and energy efficiency, impacting industries reliant on smart technology. His scholarly output has the potential to influence policy and innovation in areas such as network management and resource optimization.

🔧 Technical Skills

Dr. Zhao possesses advanced technical skills in data analysis, machine learning, and network optimization, particularly within the context of IoT systems. His expertise in auction theory and its applications in real-world scenarios is a testament to his depth of understanding and innovation in these areas. He is also adept at utilizing advanced analytical tools and methods to derive actionable insights from complex datasets.

đŸ‘©â€đŸ« Teaching Experience

As an Associate Professor at Qingdao Huanghai University, Dr. Zhao has extensive experience in educating the next generation of scholars and professionals. His role as a supervisor for undergraduate students allows him to nurture young talent and help shape their academic journeys. His commitment to teaching is evident through his personalized mentorship approach, guiding students to succeed in both their academic and professional aspirations.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Zhao aims to continue contributing to the field of International Economics and Social Security Studies, with a strong emphasis on data-driven solutions. His work has already proven impactful, and he intends to further refine his methodologies to solve pressing global issues such as economic inequality, social security systems, and technological advancements in IoT. His legacy will undoubtedly inspire future researchers and practitioners in these fields, and his work has the potential to pave the way for groundbreaking solutions in economic policy and technological development.

🏆 Recognition and Awards

Dr. Zhao’s academic achievements have garnered recognition within the research community. He is a strong candidate for the Best Researcher Award for his ongoing contributions to data analysis and IoT research. His ability to surpass existing methodologies, particularly in terms of energy efficiency, sets him apart as an innovator in his field. His commitment to advancing knowledge and solving real-world problems makes him a deserving nominee for such accolades.

 

📖 Top Noted Publications

Congestion control in internet of things (IoT) using auction theory
    • Authors: Zhenlong Li; Yunhao Zhao
    • Journal: Scientific Reports
    • Year: 2024
Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling
    • Authors: Nasi Wang; Yunhao Zhao; Jun Li; Guanfeng Cai
    • Journal: Scientific Reports
    • Year: 2024
Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC)
    • Authors: Yunhao Zhao; Xiaoqing Shu
    • Journal: Scientific Reports
    • Year: 2023

Akram Bennour | Biometrics | Outstanding Scientist Award

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Dr. Akram Bennour | Biometrics | Outstanding Scientist Award

Echahid cheikh Larbi Tebessi University, Algeria

👹‍🎓Professional Profile

đŸ« Current Position and Academic Leadership

Dr. Akram Bennour has been an Associate Professor in the Computer Science Department at the University of Tebessa, Algeria, since 2009. Throughout his tenure, he has led several academic and research initiatives, significantly shaping the university’s research output. Notably, he has served as the Vice-Rector in charge of Scientific Research and International Cooperation (2012-2014) and Deputy Vice-Rector for higher education and continuing education (2019). Additionally, he holds leadership roles in various committees, including scientific and disciplinary bodies, reflecting his influence within the academic governance structure of the university.

📚 Early Academic Pursuits and Education

Dr. Bennour’s academic journey began with his Bachelor’s degree in Computer Science (2004) from the University of Mantouri, Constantine. He then completed a Magistere in Computer Science at the University of Tebessa in 2009, followed by a Doctorate in Computer Science from the University of Annaba in 2015. His commitment to advanced research led him to earn his Habilitation degree in 2019 from the University of Oum-el-Bouaghi, Algeria, marking a pivotal moment in his academic career.

🔍 Contributions and Research Focus

Dr. Bennour’s research spans across multiple areas, emphasizing nature-inspired metaheuristics, evolutionary computation, machine learning, artificial intelligence, and pattern recognition. His work delves deeply into image processing, especially in the contexts of satellite imagery, handwriting, and medical imaging. His contributions have significantly impacted AI and computational methods applied to medical diagnostics, such as his recent focus on early detection of neural diseases through handwriting analysis (2022-2025) and pulmonary disease diagnosis (2023-2026).

He has been actively involved in various research projects, including:

  • Multi-Temporal Analysis of Images and Data Processing (2010-2013)
  • Knowledge Extraction and Analysis (2013-2016)
  • Data Protection within Electronic Administration (2020-2023)

🌍 Professional Endeavors and Global Impact

Dr. Bennour’s influence extends beyond academia. He serves as an editorial leader and guest editor for several prestigious journals, including Springer’s Pattern Recognition Letters and SNCS Special Issues, focusing on machine learning and pattern recognition. His editorial leadership has contributed to advancing research in these fields and providing a platform for global research collaborations.

Additionally, he plays an instrumental role in organizing international conferences, such as the Springer International Conference on Intelligent Systems and Pattern Recognition (ISPR), where he has served as General Chair multiple times. These roles underscore his commitment to fostering global research dialogues and knowledge exchange.

📖 Teaching Experience and Mentorship

Dr. Bennour has an extensive teaching portfolio, reflecting his dedication to educating the next generation of computer scientists. His teaching spans various critical topics, including:

  • Artificial Intelligence
  • Computer Vision
  • Data Structures and Algorithms
  • Operating Systems and Security

He has taught both undergraduate and graduate courses since 2009, with his courses focusing on hands-on programming languages (e.g., Python, C++, MATLAB) and technical areas such as machine learning, image processing, and network security. His passion for teaching is evident in his role as Head of Master’s and Bachelor’s programs at the University of Tebessa, where he has shaped the curriculum to align with current industry needs.

⚙ Technical Skills and Expertise

Dr. Bennour is highly skilled in a range of technical areas, including:

  • Programming Languages: SQL Server, MATLAB, Python, C++, PHP/MySQL, Pascal
  • AI & Machine Learning: Expertise in pattern recognition, image analysis, and biometrics
  • System Administration: Proficient in Windows, Unix, and VMware environments
  • Data Protection & Security: Advanced skills in backup systems, Exchange servers, and Active Directory management

His interdisciplinary expertise positions him as an authority in combining AI technologies with practical applications, especially in medical diagnostics and cybersecurity.

🌟 Legacy and Future Contributions

Dr. Bennour’s contributions to both academia and industry are profound, particularly in the application of AI for real-world problems. His research continues to shape the landscape of intelligent systems, and his leadership in international conferences and journals ensures that his influence remains global. As he continues his work on early disease detection and advanced AI applications, his future contributions are likely to have significant societal impacts, particularly in healthcare and medical technology.

📈 Academic Influence and Citations

Dr. Bennour’s extensive body of research has contributed to the growing body of literature in his fields of expertise. Through his publications and editorial roles, he has advanced the academic discourse surrounding AI, machine learning, image processing, and pattern recognition. His work on pattern recognition, especially in medical contexts, is frequently cited and serves as a foundation for other scholars in related fields.

🌐 Professional Memberships and Global Networks

Dr. Bennour is an active member of several international academic communities. His roles as General Chair for the ISPR conferences and his participation in organizing multiple international conferences demonstrate his commitment to fostering global collaboration and advancing research in intelligent systems and pattern recognition. His editorial work further solidifies his position as a key figure in the academic and research community.

📖Top Noted Publications

Channel and Spatial Attention in Chest X-Ray Radiographs: Advancing Person Identification and Verification with Self-Residual Attention Network
    • Authors: H. Farah, A. Bennour, N. A. Kurdi, S. Hammami, M. Al-Sarem
    • Journal: Diagnostics
    • Year: 2024
An innovative framework to securely transfer data through the Internet of Things using advanced generative adversarial networks
    • Authors: A. Bennour, M. Elhoseny, B. D. Veerasamy, R. Bhatt, A. Agrawal, P. K. Shukla, et al.
    • Journal: Journal of High Speed Networks
    • Year: 2024
Unveiling Parkinson’s: Handwriting Symptoms with Explainable and Interpretable CNN Model
    • Authors: A. Zemmar, A. Bennour, M. Tahar, F. Ghabban, M. Al-Sarem
    • Journal: International Journal of Pattern Recognition and Artificial Intelligence
    • Year: 2024
Park-Net: A Deep Model for Early Detection of Parkinson’s Disease Through Automatic Analysis of Handwriting
    • Authors: A. Bennour, T. Mekhaznia
    • Journal: SN Computer Science
    • Year: 2024
Beyond Traditional Biometrics: Harnessing Chest X-Ray Features for Robust Person Identification
  • Authors: F. Hazem, B. Akram, T. Mekhaznia, F. Ghabban, A. Alsaeedi, B. Goyal
  • Journal: Acta Informatica Pragensia
  • Year: 2024

Biying Fu | Machine Learning Applications | Best Researcher Award

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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 đŸ’Œ

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 đŸ‘©â€đŸ«

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

Sogand Dehghan | social network analysis | Best Innovation Award

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Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👹‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

đŸ‘©â€đŸ’» Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

đŸ’Œ Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

đŸ‘šâ€đŸ« Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.

 

Antonio Palacios-RodrĂ­guez | Educational Technology | Most Cited Paper Award

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Prof. Dr. Antonio Palacios-RodrĂ­guez | Educational Technology | Most Cited Paper Award

Prof. Dr. Antonio Palacios-RodrĂ­guez at University of Seville, Spain

👹‍🎓  Profiles

🌟 Summary

Prof. Dr. Antonio Palacios-RodrĂ­guez is an Assistant Professor at the University of Seville, specializing in educational technology, digital competence, and teacher training. With a PhD in Education, he focuses on developing digital skills among educators, contributing significantly to the field through numerous publications and presentations.

🎓 Education

He earned his PhD in Education with an Outstanding Cum Laude from the University of Seville in 2022. Prior to that, he completed a Master’s in Management, Evaluation, and Quality of Training Institutions in 2018 and a Bachelor’s in Primary Education in 2017, receiving an Extraordinary Award.

đŸ’Œ Professional Experience

Currently, he serves as an Assistant Professor in the Department of Didactics and Educational Organization at the University of Seville. He has previously held positions as a Postdoctoral Researcher at the University of Malaga and as an Interim Substitute Professor at the University of Seville.

🏆 Accolades and Recognition

Prof. Palacios-RodrĂ­guez has been recognized with the Award for Best Scientific Article from the Faculty of Education Sciences at the University of Seville and the UNIA-DIGITAL Award for Research from the International University of Andalusia. He has authored 67 high-impact research articles and actively participates in national and international conferences.

🔍 Research Interests

His research interests include the integration of educational technology in teaching, the development of digital competence in educators, and innovative approaches to teacher training and professional development.

📖 Top Noted Publications

Diagnosis of TPACK in Elementary School Teachers: A Case Study in the Colombian Caribbean
    • Authors: JimĂ©nez Sierra, Á., Ortega Iglesias, J., Palacios-RodrĂ­guez, A.
    • Journal: Education Sciences
    • Volume: 14
    • Issue: 9
    • Pages: 1013
    • Year: 2024
Acceptance of Educational Artificial Intelligence by Teachers and Its Relationship with Some Variables and Pedagogical Beliefs
    • Authors: Cabero-Almenara, J., Palacios-RodrĂ­guez, A., Loaiza-Aguirre, M.I., Rivas-Manzano, M.D.R.D.
    • Journal: Education Sciences
    • Volume: 14
    • Issue: 7
    • Pages: 740
    • Year: 2024
Digital Innovation in Language Teaching—Analysis of the Digital Competence of Teachers according to the DigCompEdu Framework
    • Authors: Rubio-Gragera, M., Cabero-Almenara, J., Palacios-RodrĂ­guez, A.
    • Journal: Education Sciences
    • Volume: 13
    • Issue: 4
    • Pages: 336
    • Year: 2023
Medical Education and Cognitive Load: Study of the Interaction with Learning Objects in Virtual Reality and 360Âș Video
    • Authors: Palacios-RodrĂ­guez, A., Cabero-Almenara, J., Serrano-Hidalgo, M.
    • Journal: Revista de EducaciĂłn a Distancia
    • Volume: 24
    • Issue: 79
    • Pages: 3
    • Year: 2024
Microlearning in the University Classroom: Use of Virtual Simulator in Biology
    • Authors: Romero-Saritama, J.M., Llorente-Cejudo, C., RodrĂ­guez, A.P., Kalinhoff, C.
    • Journal: Edutec
    • Volume: 88
    • Pages: 24–41
    • Year: 2024
Validation Using Structural Equations of the “Cursa-T” Scale to Measure Research and Digital Competencies in Undergraduate Students
    • Authors: Duarte Ayala, R.E., Palacios-RodrĂ­guez, A., GuzmĂĄn-Cedillo, Y.I., Segura, L.R.
    • Journal: Societies
    • Volume: 14
    • Issue: 2
    • Pages: 22
    • Year: 2024
Technological and Sustainable Security: A Longitudinal Study on Teacher Training
    • Authors: Cabero-Almenara, J., BarragĂĄn-SĂĄnchez, R., Llorente-Cejudo, C., Palacios-RodrĂ­guez, A.
    • Journal: Computers in the Schools
    • Volume: 41
    • Issue: 3
    • Pages: 263–280
    • Year: 2024