Dr. Lin Li | AI in Networking | Best Researcher Award

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Dr. Lin Li | AI in Networking | Best Researcher Award

Dr. Lin Li, upm, Malaysia

Lin Li, born in Wuhan, China, is an accomplished academic and researcher specializing in the convergence of Artificial Intelligence and Public Art, with a focus on intelligent interaction and restorative therapeutic perspectives. She earned her Ph.D. in Landscape Architecture from Universiti Putra Malaysia and her Master’s in Design Studies from Hubei University of Technology. Lin Li serves as a Lecturer at the Wuhan Institute of Design and Sciences, where she has been dedicated to enhancing the design curriculum and mentoring students since 2008. Her work emphasizes the therapeutic potential of public art, blending technology with traditional design to create interactive experiences that positively impact public spaces. Lin Li’s expertise spans advertising creativity, corporate branding, and digital marketing, contributing significantly to the fields of design and landscape architecture through her innovative research, teaching, and active involvement in workshops and seminars.

Professional Profile

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Suitability for the Best Researcher Award

Lin Li stands out as a compelling candidate for the Best Researcher Award due to her unique blend of academic excellence, practical experience, and a strong focus on innovative research areas within landscape architecture and design. Her Ph.D. in Landscape Architecture from Universiti Putra Malaysia, complemented by her Master’s in Design Studies from Hubei University of Technology, underscores her robust academic foundation. Her research specialization in Artificial Intelligence and Public Art, particularly in intelligent interaction and restorative therapeutic perspectives, positions her at the forefront of interdisciplinary research that merges technology, design, and mental well-being.

🎓  Education 

Lin Li holds a Ph.D. in Landscape Architecture from Universiti Putra Malaysia, where she focused on integrating Artificial Intelligence into public art to explore its therapeutic potential and applications in intelligent interaction. Her research investigates how AI can create restorative environments that enhance public well-being, contributing new insights to the fields of landscape architecture and public art. Previously, she completed a Master’s in Design Studies at Hubei University of Technology, China (2012–2015), where she concentrated on foundational design principles and creative methodologies. Lin Li’s academic journey is marked by her interdisciplinary approach, linking design theory with advanced AI technologies to develop sustainable and meaningful public art experiences. Her educational background supports her ongoing exploration into the intersections of creativity, technology, and public engagement, establishing her as a thought leader in therapeutic art and innovative design strategies.

💼   Experience 

Lin Li has been a Lecturer at the Wuhan Institute of Design and Sciences, China, since 2008, where she delivers courses in advertising creativity, brand marketing communication, and corporate image design. Her role involves not only teaching but also shaping the institution’s design curriculum and mentoring students in their professional development. Lin organizes workshops and seminars, fostering a dynamic learning environment where students can deepen their understanding of design principles. Her experience in academia is complemented by her professional expertise in creative content and digital marketing, particularly within interactive art and corporate branding. Lin Li’s innovative approach combines her deep understanding of design theory with a practical focus on media applications, making her an influential figure in the Chinese design education landscape. She has contributed significantly to advancing public art’s therapeutic and communicative aspects through her teaching and research initiatives.

🏅Awards and Honors 

Lin Li has earned recognition for her contributions to design education and her research in public art. She has received multiple awards for her innovative approaches to integrating Artificial Intelligence within public art, underscoring her dedication to advancing restorative and interactive public spaces. Her accolades include the Excellence in Design Education Award from the Wuhan Institute of Design and Sciences, which celebrates her commitment to student mentorship and curriculum development. Additionally, she has been honored at international design forums for her impactful research on the therapeutic effects of public art, gaining recognition from both academic and professional communities. Lin’s awards reflect her vision of blending technology and creativity to benefit public spaces and her ongoing contribution to enriching the fields of design and landscape architecture through a forward-thinking approach.

🌍 Research Focus 

Lin Li’s research centers on the application of Artificial Intelligence within Public Art, specifically exploring intelligent interaction and restorative, therapeutic perspectives. Her work investigates how AI-driven designs can transform public spaces into interactive, healing environments, providing sensory and emotional benefits to visitors. Lin’s approach combines traditional art forms with digital interactivity, creating art installations that respond to audience engagement. Her studies in landscape architecture have led her to focus on the therapeutic potential of AI-enabled public art in promoting mental well-being, as well as how intelligent design elements can foster community connection and reflection in urban spaces. Lin Li’s research interest in public art communication and restorative effects aligns with her aim to blend AI technologies with art, pioneering a new frontier in both therapeutic design and sustainable public engagement.

📖 Publication Top Notes

  • Title: The Impact of Virtual Immersive Public Art on the Restorative Experience of Urban Residents

 

Prof. Arturo Benayas Ayuso | AI in Networking | Best Researcher Award

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Prof. Arturo Benayas Ayuso | AI in Networking | Best Researcher Award

Prof. Arturo Benayas Ayuso, Universidad Politécnica de Madrid, Spain

Arturo Benayas Ayuso is a highly skilled Naval Architect with an MSc from Universidad Politécnica de Madrid, currently pursuing a Ph.D. focusing on IoT applications in ship design and management. As the Integration Lead for NAVANTIA’s “El Cano” platform, he leads the digital transformation of naval shipbuilding, harnessing Industry 4.0 principles. Arturo has held pivotal roles across major projects, such as the Spanish S80P submarine and multi-national shipbuilding collaborations. His expertise encompasses platform integration, project management, and overseeing PLM (Product Lifecycle Management) systems, contributing significantly to modernizing naval architecture and ship design through digitization. Additionally, Arturo has co-authored influential publications and presented at global conferences on smart ship technology, IoT, and cybersecurity, marking him as an innovative force in the naval engineering field.

Professional Profile

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suitable for this Research for Best Researcher Award

Arturo Benayas Ayuso demonstrates significant qualifications for the “Best Researcher Award,” particularly in fields related to Industry 4.0 applications, IoT integration in naval architecture, and advanced project management in the shipbuilding industry. With an academic foundation in naval architecture and an ongoing Ph.D. focusing on IoT in ship design and management, Arturo brings both specialized knowledge and continuous research activity, which align well with the award’s requirements for impactful and progressive research contributions.

🎓 Education

Arturo holds an MSc in Naval Architecture from Universidad Politécnica de Madrid, with a specialization in marine motors. He is also a Ph.D. researcher focusing on IoT applications in naval engineering, particularly in ship design, shipbuilding, and management. His advanced studies delve into integrating IoT technologies within the naval architecture industry, emphasizing innovations in Industry 4.0, smart ship design, and naval automation. Arturo has undertaken extensive training in critical industry software, such as Siemens Teamcenter PLM and PTC Windchill PLM, equipping him with sophisticated skills to address the complex challenges of modern shipbuilding. His ongoing academic pursuits and certifications, including machine learning from Stanford and advanced system administration for PLM platforms, underscore his dedication to continuous learning and technological advancement in naval architecture.

💼   Experience 

Arturo Benayas Ayuso serves as the Integration Lead for NAVANTIA’s “El Cano” platform, orchestrating comprehensive integration efforts for advanced naval shipbuilding, which involves embracing Industry 4.0 digitalization. His previous roles as Technical Account Manager and Solution Architect have seen him shape FORAN-PLM integration for high-profile naval projects, like the Spanish Navy’s S80P submarine. With extensive experience in PLM systems (Windchill, Teamcenter), Arturo leads a dynamic team to deliver custom integrations for NAVANTIA’s global naval operations, ensuring optimal functionality and efficient lifecycle management. His career also includes work at SENER Ingeniería y Sistemas, managing multi-national shipbuilding collaborations, from the Royal Navy’s CVF project to offshore platform developments in Dubai. Beyond integration, Arturo contributes strategic oversight for project tenders, technical specifications, and economic forecasting.

🏅 Awards & Honors 

Arturo Benayas Ayuso has received industry recognition for his innovative contributions to naval architecture and ship design. Notably, his leadership in NAVANTIA’s “El Cano” platform exemplifies his commitment to advancing naval engineering with cutting-edge digital solutions and IoT integration. Arturo has been honored for his technical expertise, particularly in integrating PLM systems like Windchill and Teamcenter, which has significantly optimized NAVANTIA’s digital transformation. His presentations and publications, such as those at the RINA Smart Ship Technology conference, have won acclaim, further establishing his role as a thought leader in naval engineering. Additionally, Arturo’s contributions to pioneering the modernization of naval architecture through the FORAN-PLM platform have been acknowledged by peers in both industry and academia, marking his impact on the future of naval design and management.

🌍 Research Focus 

Arturo’s research emphasizes IoT applications within naval architecture, particularly in ship design, shipbuilding, and management. His Ph.D. work explores innovative IoT integrations for smart ship technology, aiming to advance ship management efficiency and safety. His research also delves into PLM system integrations, with a focus on optimizing Product Lifecycle Management for the naval industry, bridging the gap between physical and digital shipbuilding processes. Arturo is passionate about cybersecurity within IoT networks, exploring how blockchain can serve as a foundational security layer, especially for IoT-dependent naval platforms. His scholarly work, including conference presentations and journal articles, provides insights into Industry 4.0 applications, smart ships, and data management strategies for efficient maritime operations. His work positions him at the forefront of applying IoT and digital solutions in naval engineering, setting new standards for smart and secure shipbuilding.

📖 Publication Top Notes

  • CAD Sensitization, an Easy Way to Integrate Artificial Intelligence in Shipbuilding
  • Internet of Things Cybersecurity – Blockchain as First Securitization Layer of an IoT Network
  • Automated/Controlled Storage for an Efficient MBOM Process in Shipbuilding Managing IoT Technology
  • Data Management for Smart Ship or How to Reduce Machine Learning Cost in IoS Applications
  • RFID Tagging for a Connected Shipyard

Dr. Zhigang Tu | AI in Networking | Best Researcher Award

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Dr. Zhigang Tu | AI in Networking | Best Researcher Award

Dr. Zhigang Tu, Wuhan University, China

👨‍🏫 Zhigang Tu is a distinguished Professor at Wuhan University, China, with extensive experience in computer vision and artificial intelligence. He earned his Master’s in image processing from Wuhan University and his Ph.D. in Computer Science from Utrecht University. His career includes postdoctoral research at Arizona State University and a research fellowship at Nanyang Technological University. He has authored over 70 papers and is known for his contributions to video analytics and human behavior recognition.

Profile

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Zhigang Tu is an impressive candidate for the “Best Researcher Award,” given his substantial contributions to the field of computer vision and artificial intelligence. Here’s an analysis of his strengths, areas for improvement, and a concluding evaluation regarding his suitability for the award:

Strengths for the Award:

Extensive Research Output:

Zhigang Tu has authored or co-authored over 70 papers in prestigious journals and conferences, including top venues like IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Image Processing (TIP). This extensive publication record demonstrates his significant contributions to the field.

High-Quality Publications:

Many of his papers have appeared in high-impact journals and conferences. Notably, his recent work on 3D hand reconstruction and motion stylization reflects cutting-edge research in computer vision.

Recognition and Awards:

He has received notable awards, such as the Best Student Paper Award and the Best Reviewer Award from IEEE T-CSVT, highlighting his excellence both in research and in contributing to the academic community.

Leadership and Editorial Roles:

Tu’s roles as Area Chair for AAAI and VCIP, and as an Associate Editor for several SCI-indexed journals, underscore his leadership and influence in the field. His involvement in organizing workshops and special issues further reflects his active engagement with the research community.

Diverse Research Interests:

His research spans various aspects of computer vision and AI, including motion capture, human behavior recognition, and video analytics. This breadth of research indicates a deep and comprehensive understanding of his domain.

International Experience:

His international experience, with positions at universities in China, the Netherlands, the US, and Singapore, demonstrates a broad perspective and the ability to collaborate across different research environments.

Areas for Improvement:

Broader Impact Evaluation:

While Tu’s research output is extensive, the broader societal impact of his work could be more explicitly highlighted. This includes how his research addresses real-world problems or contributes to industry advancements.

Interdisciplinary Research:

Although his work is highly specialized, further interdisciplinary collaborations could enhance the applicability and reach of his research. Exploring intersections with other fields like robotics or cognitive science might provide new dimensions to his work.

Public Engagement:

Increased efforts in public engagement or science communication could further enhance his profile. This could include popular science articles, public lectures, or community outreach programs.

Education

🎓 Professor Tu completed his Master’s degree in Image Processing at Wuhan University in 2008. He pursued his Ph.D. in Computer Science at Utrecht University, Netherlands, graduating in 2015. His academic journey also includes a postdoctoral stint at Arizona State University (2015-2016) and a research fellowship at Nanyang Technological University (2016-2018).

Experience

💼 Dr. Tu’s professional experience spans various prestigious institutions. After his Ph.D., he was a postdoctoral researcher at Arizona State University and then served as a research fellow at Nanyang Technological University. Since 2018, he has been a professor at Wuhan University, continuing his impactful work in computer vision and AI.

Research Interests

🔍 Professor Tu’s research interests encompass Computer Vision (motion estimation, human action analysis, hand/human pose estimation, anomaly detection) and Artificial Intelligence (deep learning, CNN, GCN, transformer architectures). His work focuses on enhancing video analytics and human behavior recognition technologies.

Awards

🏆 Professor Tu has received notable accolades including the Best Student Paper Award at the 4th Asian Conference on Artificial Intelligence Technology and the Best Reviewer Award from IEEE Transactions on Circuits and Systems for Video Technology (IEEE T-CSVT) in 2022. These awards recognize his outstanding contributions to the field and his peer-review excellence.

Publication Top Notes

📚 Here are some of Professor Tu’s significant publications:

A Modular Neural Motion Retargeting System Decoupling Skeleton and Shape Perception, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Generative Motion Stylization of Cross-structure Characters within Canonical Motion Space, ACM Multimedia, 2024.

TapMo: Shape-aware Motion Generation of Skeleton-free Characters, ICLR, 2024.

Patch Similarity Self-Knowledge Distillation for Cross-view Geo-localization, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024.

Consistent 3D Hand Reconstruction in Video via Self-Supervised Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.

Conclusion:

Zhigang Tu is highly suitable for the “Best Researcher Award” based on his substantial research contributions, recognition within the academic community, and leadership roles. His extensive publication record, high-impact research, and active involvement in organizing and reviewing for top conferences and journals strongly support his candidacy.

To further strengthen his application, emphasizing the broader societal impact of his research and exploring interdisciplinary collaborations could be beneficial. Overall, his achievements and influence make him a standout candidate for the award.

Prof. Reza Ghaderi | AI in Networking | Best Faculty Award

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Prof. Reza Ghaderi | AI in Networking | Best Faculty Award

Prof.  Reza Ghaderil, Shahid Beheshti University, Iran

Reza Ghaderi’s extensive achievements in education, research, and academic leadership make him an exemplary candidate for the Research for Best Researcher Award. His educational background, specialized research expertise, and significant academic contributions reflect a career dedicated to advancing electrical engineering and technology. His innovative research projects further illustrate his ability to address complex challenges and drive progress in his field. With a proven track record of impactful work and leadership, Dr. Ghaderi embodies the qualities sought for this prestigious award.

Professional Profile:

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Suitability for the Award

Prof. Reza Ghaderi is highly suitable for the Research for Best Faculty Award. His extensive academic and research experience, combined with his leadership roles in both educational institutions and national projects, make him a distinguished figure in the field of electrical engineering. His contributions to research, particularly in neural networks, nanoelectronics, and particle accelerators, have had a significant impact on both the academic community and the broader technological landscape.

Educational Achievements:

Reza Ghaderi’s educational background is marked by significant accomplishments, reflecting his deep knowledge and commitment to the field of electrical engineering. He earned his Bachelor’s and Master’s degrees in Electrical Engineering – Electronics from Ferdowsi University of Mashhad and Tarbiat Modares University, respectively. His academic journey culminated in a Ph.D. from the University of Surrey, Guildford, where he specialized in electrical engineering. His strong educational foundation has provided him with the skills and insights necessary for groundbreaking research and leadership in his field.

Specialized Research Expertise:

Dr. Ghaderi’s research expertise spans a wide array of topics within electrical engineering, showcasing his versatility and depth of knowledge. His work includes the design and development of advanced technological systems such as high-voltage generators and digital autopilot systems. He has made significant contributions to neural networks, face recognition systems, and hydraulic servo systems, highlighting his ability to tackle complex problems and innovate solutions in various research areas.

Significant Academic Contributions:

Reza Ghaderi has made notable academic contributions through his roles as a faculty member and administrator at prestigious institutions. His leadership positions at the University of Mazandaran and Shahid Beheshti University, including his current role as Dean of the Faculty of Electrical Engineering, underscore his influence in shaping academic programs and research initiatives. His involvement in the development of national technology and IT strategies further emphasizes his impact on advancing educational and technological standards.

Innovative Research Projects:

Dr. Ghaderi’s innovative research projects have addressed a range of technological and scientific challenges. His work on designing high-voltage generators and AC motor speed controllers, along with his research on neural networks and particle accelerators, demonstrates his ability to lead and execute complex projects. His contributions to national projects, such as the development of sonar strategies and energy strategy documents, highlight his commitment to advancing technology and its applications on a broader scale.

Professional Experience and Impact:

Reza Ghaderi’s professional experience encompasses a broad range of roles and responsibilities that highlight his profound impact on the field of electrical engineering and academia. His career trajectory demonstrates a commitment to both advancing technological innovations and shaping educational practices.

Publication Top Notes:

  • Publication Topic: “A Practical Approach to Tracking Estimation Using Object Trajectory Linearization”
    • Year: 2024
  • Publication Topic: “Rapid and Accurate Predictions of Perfect and Defective Material Properties in Atomistic Simulation Using the Power of 3D CNN-Based Trained Artificial Neural Networks”
    • Year: 2024
  • Publication Topic: “Solving a Class of Thomas–Fermi Equations: A New Solution Concept Based on Physics-Informed Machine Learning”
    • Year: 2024
  • Publication Topic: “Salinity and Flow Pattern Independent Flow Rate Measurement in a Gas-Liquid Flow with Optimum Feature Selection and Novel Detection Geometry Using ANNs”
    • Year: 2024
  • Publication Topic: “An IoT-Based Packet Aggregation Mechanism for the SDN-Based Wide Area Networks”
    • Year: 2024

 

 

Dr. Adnene Arbi | AI in Networking | Excellence in Research

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Dr. Adnene Arbi | AI in Networking | Excellence in Research

Dr adnene arbi , EPT, Tunisia

Dr. Adnene Arbi, an Assistant Professor at the National School of Advanced Sciences and Technologies at Borj Cedria and a member of the Laboratory of Engineering Mathematics at Polytechnic School of Tunisia, is a prominent researcher in applied mathematics. His work is recognized for its depth in areas such as robust control, synchronization, time scale spaces, and dynamical systems. With more than 26 peer-reviewed publications, he is a distinguished figure in his field, contributing to both academic and practical advancements in mathematics.

Professional Profile:

Scopus
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Suitability for the Research for Best Researcher Award

Dr. Adnene Arbi is exceptionally well-suited for a Research Excellence Award due to his comprehensive expertise, innovative contributions, and significant impact in the field of applied mathematics. His research encompasses a broad range of complex topics, including robust control, synchronization of neural networks, and time scale spaces, demonstrating a deep understanding of both theoretical and practical aspects of mathematics.

Dr. Arbi’s work is distinguished by his innovative methodologies and solutions to challenging mathematical problems. For instance, his development of a new technique for optimizing parameters in Support Vector Machines (SVM) during his Master’s studies highlights his capacity for pioneering research that addresses critical issues in computational mathematics. His subsequent research on the stability of Hopfield-type neural networks and his exploration of oscillatory systems and delayed differential equations further underscore his innovative approach and expertise.

Academic Background 📚

Dr. Arbi’s academic journey is marked by excellence. He achieved his Habilitation in Applied Mathematics from the Preparatory Institute for Scientific and Technical Studies, University of Carthage in 2023, with a focus on functional spaces of oscillatory type and delayed dynamical models. His Ph.D. from the Faculty of Sciences of Bizerta in 2014 concentrated on the stability of Hopfield-type neural network models. Earlier, he earned a Master’s in Engineering of Mathematics and a Bachelor’s in Applied Mathematics, both from the University of Carthage, showcasing a strong foundation in mathematical theory and application.

Professional Experience 💼

Dr. Arbi is an Assistant Professor at the National School of Advanced Sciences and Technologies at Borj Cedria and serves as a member of the Laboratory of Engineering Mathematics at the Polytechnic School of Tunisia. His professional roles include teaching various mathematics modules, ranging from analysis and numerical methods to data mining and simulation. He also holds editorial positions with several international journals, demonstrating his influence in the field.

Research Interests and Contributions 🔬

Dr. Arbi’s research interests are broad and impactful, encompassing robust control, time scale spaces, stochastic and time-delay systems, and neural networks. His work often explores the dynamics of complex systems and their optimization, contributing to the theoretical and practical advancements in these areas. His research also delves into algorithm development and artificial intelligence, further broadening his impact.

Awards and Recognitions 🏆

Dr. Adnene Arbi has garnered significant recognition throughout his academic career, reflecting his exceptional contributions to the field of applied mathematics. Notable among his accolades is the very honorable mention for his Habilitation in Applied Mathematics, awarded in 2023, which highlights his significant contributions to the study of functional spaces of oscillatory types and delayed dynamical models. Additionally, Dr. Arbi has received commendations for his doctoral research, which explored the stability of Hopfield-type neural networks, underscoring his expertise in both theoretical and applied mathematics. His role as a reviewer and editor for numerous high-impact journals also illustrates the esteem in which he is held by the academic community. These honors collectively underscore Dr. Arbi’s excellence in research and his influential role in advancing mathematical sciences.

Innovations and Impact 🚀

Dr. Adnene Arbi’s innovation is highlighted by his development of novel techniques in parameter optimization for Support Vector Machines (SVM), enhancing machine learning efficiency. His work on oscillatory systems and time scale spaces introduces new analytical methods for dynamical systems. This innovation not only advances theoretical understanding but also has practical implications in control systems and artificial intelligence. Dr. Arbi’s contributions are widely recognized through his extensive publications and editorial roles, reflecting his significant impact on both academic research and real-world applications.

Publication Top Notes:

  1. Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models
    • Year: 2024
    • Journal: Journal of Risk and Financial Management
  2. Robust Model Predictive Control for Fractional-Order Descriptor Systems with Uncertainty
    • Year: 2024
    • Journal: Fractional Calculus and Applied Analysis
  3. Synchronization Analysis of Novel Delayed Dynamical Clifford-Valued Neural Networks on Timescales
    • Year: 2024
    • Journal: Journal of Algorithms and Computational Technology
  4. Morlet Wavelet Neural Network Investigations to Present the Numerical Investigations of the Prediction Differential Model
    • Year: 2023
    • Journal: Mathematics
  5. Designing a Bayesian Regularization Approach to Solve the Fractional Layla and Majnun System
    • Year: 2023
    • Journal: Mathematics
  6. Stability Analysis of Inertial Neural Networks: A Case of Almost Anti-Periodic Environment
    • Year: 2022
    • Journal: Mathematical Methods in the Applied Sciences
  7. Dynamics of Delayed Cellular Neural Networks in the Stepanov Pseudo Almost Automorphic Space
    • Year: 2022
    • Journal: Discrete and Continuous Dynamical Systems – Series S

Dr. Abdulsamad Yahya | AI in Network | Excellence in Research

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Dr. Abdulsamad Yahya | AI in Network | Excellence in Research

Dr. Abdulsamad Yahya, Northern Border University, Saudi Arabia

Dr. Abdulsamad Yahya, an Assistant Professor at Northern Border University, Saudi Arabia, holds a Ph.D. in Computer Science from the National University of Malaysia (UKM) and a Diploma in Computer Engineering from the Higher Institute of Mechanical and Electrical Engineering, Sofia. With over 16 years of academic experience, he has significantly impacted the IT Department through his roles as Head of the IT Department and Deputy Dean of Postgraduate Studies. Dr. Yahya’s research expertise includes Artificial Intelligence, Computer Vision, and Biometrics, with notable contributions to deep learning and big data visualization. Recognized with scholarships from Yemen’s Ministry of Education and Ministry of Higher Education, his career is distinguished by a strong blend of research excellence and administrative leadership.

Professional Profile:

Scopus

Suitability for the Research for Best Researcher Award

Dr. Abdulsamad Yahya is a strong contender for the Research for Best Researcher Award based on his extensive experience in academia, significant contributions to the field of computer science, and his leadership roles. His qualifications and research interests highlight his exceptional suitability for this recognition.

🎓 Academic Expertise:

Dr. Abdulsamad Yahya, Ph.D. in Computer Science from National University of Malaysia (UKM), brings over 16 years of academic experience. His qualifications also include a Diploma in Computer Engineering from the Higher Institute of Mechanical and Electrical Engineering, Sofia.

 

📚 Distinguished Educator:

As an Assistant Professor at Northern Border University, Saudi Arabia, Dr. Yahya has significantly impacted the Information Technology Department. His past roles include Head of the IT Department and Deputy Dean of Postgraduate Studies, showcasing his leadership in academia.

🔬 Research Leader:

Dr. Yahya’s research focuses on Artificial Intelligence, Computer Vision, and Biometrics. His conference papers on deep learning and big data visualization reflect his active contribution to advancing these fields.

🏆 Award-Winning Scholar:

Honored with scholarships from Yemen’s Ministry of Education and Ministry of Higher Education, Dr. Yahya’s academic journey is marked by his commitment to research and education.

🗂️ Administrative Excellence:

Dr. Yahya has served as the Head of the IT Department and Chairperson of the Senior Project Committee at Northern Border University, demonstrating his strong administrative and project management skills.

Publication Top Notes:

  • Title: Deep-Ensemble and Multifaceted Behavioral Malware Variant Detection Model
    • Citations: 13
    • Year: 2022
  • Title: A Genetic Algorithm-Based Grey Model Combined with Fourier Series for Forecasting Tourism Arrivals in Langkawi Island Malaysia
    • Citations: 3
    • Year: 2020
  • Title: Drought Forecasting Using Gaussian Process Regression (GPR) and Empirical Wavelet Transform (EWT)-GPR in Gua Musang
    • Citations: 2
    • Year: 2020
  • Title: Inflectional Review of Deep Learning on Natural Language Processing
    • Citations: 35
    • Year: 2018
  • Title: Big Data Visualization: Allotting by R and Python with GUI Tools
    • Citations: 17
    • Year: 2018