Yen-Liang Chen | deep learning | Best Researcher Award

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Prof. Dr. Yen-Liang Chen | deep learning | Best Researcher Award

Chair Professor, National Central University, Taiwan

Professor Yan-Liang Chen is a distinguished Chair Professor in the Department of Information Management at National Central University, Taiwan. He holds a Ph.D. in Information Science from National Tsing Hua University. With over four decades of academic experience, Professor Chen has led several significant projects, advancing the understanding of e-commerce systems, data analytics, and machine learning. His interdisciplinary research focuses on integrating business systems with information technology to drive digital transformation. In addition to his academic responsibilities, he has served as an advisor to the Ministry of Science and Technology and as Editor-in-Chief for renowned journals like the Journal of Electronic Commerce Research. Professor Chen has been recognized globally for his impactful work, making substantial contributions to the field of data analysis, decision support systems, and business intelligence.

Profile:

Scopus

Education:

Professor Yan-Liang Chen earned his Ph.D. in Information Science from National Tsing Hua University, one of Taiwan’s top academic institutions. His educational foundation in Information Science provided the perfect platform for his future research endeavors in e-commerce systems, data analysis, and machine learning. The focus of his doctoral research laid the groundwork for his long-standing contributions to various critical areas such as decision support systems, business intelligence, and sentiment analysis. His academic journey has continuously pushed the boundaries of knowledge, driving advancements in both the theoretical and practical aspects of information management. This foundation, alongside years of extensive teaching and research, has established Professor Chen as a leader in his field, shaping the next generation of scholars and professionals in e-commerce and data analytics.

Experience:

Professor Yan-Liang Chen has a rich academic career that spans over 40 years at National Central University in Taiwan. He began his tenure in 1978 as an Associate Professor, eventually rising to the position of Chair Professor in the Department of Information Management. From 2004 to 2007, he served as the Director of the Department of Information Management and was also the Director of the University Library from 2009 to 2011. Throughout his career, Professor Chen has led numerous research projects and has significantly contributed to the development of Taiwan’s academic and technological landscape. He has also held key advisory roles in various government bodies, such as the Ministry of Science and Technology and National Science Council, helping shape policies on information technology and e-commerce. His extensive leadership roles have made him a prominent figure in both academic and professional spheres.

Awards and Honors:

Professor Yan-Liang Chen has received numerous prestigious awards throughout his career. Notably, he has been honored with the Ministry of Science and Technology Distinguished Research Award in both 2003 and 2009, recognizing his groundbreaking contributions to e-commerce and information technology. In 2015, he was awarded the National Science Council Academic Award for his sustained excellence in research. From 2018 to 2024, he was named a Merit MOST Research Fellow, and in 2024, he received the esteemed MOST Distinguished Special Research Fellow honor. His exceptional research output has earned him a spot in the Global Top 2% Scientist Lifetime and Annual Rankings (2020-2024). Professor Chen’s remarkable academic career and continued impact have been recognized globally, solidifying his reputation as one of the leading scientists in his field.

Research Focus:

Professor Yan-Liang Chen’s research focuses primarily on E-commerce Systems and the integration of information technology with business systems. His areas of expertise include data analysis, machine learning, business intelligence, decision support systems, and sentiment analysis. He is particularly interested in understanding and optimizing the dynamics of e-commerce logistics, consumer behavior, and personalized marketing strategies. His work on basket analysis, cross-selling, and customer purchase sequence analysis has significantly advanced the understanding of consumer purchasing patterns, which are crucial for targeted marketing and enhancing customer retention. Additionally, Professor Chen has worked on text mining and social network analysis, applying these techniques to improve recommendation systems and predictive analytics in the digital commerce environment. His interdisciplinary approach has allowed him to bridge the gap between information technology and practical business applications, leading to innovations in digital transformation.

Publications:

  1. A Novel Ensemble Model for Link Prediction in Social Network 🤖📱
  2. G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction ⏳💡
  3. Using Personalized Next Session to Improve Session-Based Recommender Systems 🔄📊
  4. A Deep Recommendation Model Considering the Impact of Time and Individual Diversity ⏰🔍
  5. A Novel Virtual-Communicated Evolution Learning Recommendation 💻🧠
  6. A Deep Multi-Embedding Model for Mobile Application Recommendation 📱🔗
  7. New Information Search Model for Online Reviews with the Perspective of User Requirements 🌐🔍
  8. A Cross-Platform Recommendation System from Facebook to Instagram 📘📸
  9. Aspect-Based Sentiment Analysis with Component Focusing Multi-Head Co-Attention Networks 🧠💬
  10. An Ensemble Model for Link Prediction Based on Graph Embedding 🔗📉

Saad Alqithami | Artificial Intelligence | Sustainable Engineering Award

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Assoc. Prof. Dr. Saad Alqithami | Artificial Intelligence | Sustainable Engineering Award

Associate Professor, ALBAHA UNIVERSITY, Saudi Arabia

Saad Alqithami is an Associate Professor in the Department of Computer Science at Albaha University, Saudi Arabia. With a strong background in computer science, he completed his Ph.D. at Southern Illinois University, USA, in 2016. Alqithami has contributed significantly to the fields of social network analysis, AI, and healthcare technology, particularly in the context of Attention Deficit Hyperactivity Disorder (ADHD). His work also extends to network organizations and pandemic modeling. In addition to his teaching role, he has held leadership positions in various administrative capacities at Albaha University, including General Director of Scholarships and University Relations. Alqithami is also a reviewer and program committee member for several academic conferences, contributing to the academic community’s growth. His interdisciplinary approach and commitment to impactful research make him a notable figure in AI and computational science.

Profile

Education

Saad Alqithami holds a Ph.D. in Computer Science from Southern Illinois University, Carbondale, USA, which he completed in December 2016. Prior to that, he earned his Master’s degree in Computer Science from the same institution in August 2012. His foundational education began with a Bachelor’s degree in Computer Science from Taif University, Saudi Arabia, in July 2008. Throughout his academic journey, Alqithami focused on advanced computational intelligence, AI modeling, and networked systems. His doctoral research focused on network organizations and the use of computational models for complex systems. With a deep interest in both theoretical and applied computer science, Alqithami has consistently pursued research that bridges gaps between AI, healthcare, and social systems. His education has provided a robust foundation for his distinguished career in academia and research.

Experience

Dr. Saad Alqithami has over a decade of experience in academia, beginning as a Lecturer in 2015 at Albaha University in Saudi Arabia. He has progressed through various roles, becoming an Assistant Professor in 2017 and later an Associate Professor in 2022. Alqithami has also held significant leadership positions, including Head of the Department of Computer Information Systems and General Director of Scholarships and University Relations at Albaha University. His administrative expertise spans graduate studies, scientific research, and university relations. He has contributed to enhancing the university’s strategic initiatives, especially in research and development. Furthermore, Alqithami has actively engaged in international collaborations, providing expertise in social networks, machine learning, and computational intelligence. He has worked as a Social Networks Analyst and Programmer at Southern Illinois University, where he gained hands-on experience in social network modeling and data analysis, helping shape his interdisciplinary research approach.

Awards and Honors

Dr. Saad Alqithami’s academic journey has been marked by numerous accolades. He was nominated for an outstanding paper award at the 29th AAAI Conference on Artificial Intelligence. As a co-founder, he played a key role in the launch of the “Square-2: The Intelligent Consultant Agent” project, funded by King Abdulaziz City for Science and Technology (KACST). Alqithami also received research funding from Albaha University for two major projects: “Understanding Social Contagion and Viral Spreading of COVID-19” and “An Intelligent Cognitive Modeling for Enhancing the Behavior of Children with ADHD Using a Mixed Reality Environment.” Additionally, he has been honored as a Rosalind Member by the London Journals Press. His work has not only advanced computational intelligence but has also contributed significantly to social good, especially in healthcare and public health contexts, earning him recognition from both academic and scientific communities.

Research Focus

Dr. Saad Alqithami’s research primarily focuses on the application of artificial intelligence, machine learning, and computational models to real-world problems. His work spans several areas, including social network analysis, healthcare technology, and the development of innovative solutions for behavioral health issues like ADHD. Alqithami has contributed to the design of augmented reality environments for therapeutic interventions and has modeled pandemic dynamics in social networks using AI techniques. His interdisciplinary research is aimed at bridging the gap between AI-driven insights and practical applications, particularly in healthcare and networked systems. He is also keen on exploring the implications of social capital in network organizations and improving communication protocols in industrial systems. Alqithami’s work has led to significant publications in peer-reviewed journals and conferences, showcasing his contributions to advancing AI research, particularly its integration into healthcare and societal applications.

Publication Top Notes

  1. Smart Tree Health Assessment Model using Advanced Computer Vision Techniques 🌳📊
  2. A Serious-Gamification Blueprint Towards a Normalized Attention 🧠🎮
  3. Securing Industrial Communication with Software-Defined Networking 🔐🖧
  4. A Generic Encapsulation to Unravel Social Spreading of a Pandemic 🌍💉
  5. Towards Social Capital in a Network Organization 🌐💡
  6. An External Client-Based Approach for Extract Class Refactoring 🔄📚
  7. AR-Therapist: Design and Simulation of an AR-Game for ADHD Patients 🕹️👦
  8. Fluid Dynamics of a Pandemic in a Spatial Social Network 🌍💻
  9. Modeling an AR Serious Game to Increase Attention of ADHD Patients 🎮🧑‍⚕️
  10. Modeling an Augmented Reality Game to Enhance ADHD Behavior 🧠👾

 

 

Mathieu Chartier | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Mathieu Chartier | Computer Science and Artificial Intelligence | Best Researcher Award

PhD student, Poitiers University, France 

Mathieu Chartier is a digital humanities researcher, educator, and web professional based in Buxerolles, France. With expertise in natural language processing (NLP) and information retrieval, he bridges technology and history. Mathieu is an independent consultant at Internet-Formation, specializing in digital training, web marketing, and development. A multilingual scholar, he holds a strong academic background in humanities and digital tools, delivering courses on SEO, AI, and digital communication. As a prolific author, Mathieu has written several books and articles about web technologies and marketing. His current PhD research focuses on improving historical data analysis using AI.

Profile

Orcid

Education

Mathieu Chartier earned a Research Master’s in Ancient and Medieval Archaeology (2008) and a Professional Master’s in Information and Communication, Web Editorial Specialization (2009) from Poitiers University. Currently, he is pursuing a PhD in Digital Humanities, focusing on improving information retrieval in historical research through advanced NLP and large language models. Over the years, Mathieu has also acquired certifications in Google Ads and Google Analytics, enhancing his expertise in digital marketing. His interdisciplinary education combines humanities, web technology, and artificial intelligence.

Experience

With a career spanning over 15 years, Mathieu Chartier has held several key roles in academia and industry. As a freelancer, he leads Internet-Formation, providing training in web marketing, SEO, and digital communication. He has been an adjunct lecturer at institutions like the University of Poitiers and Paris-Sorbonne, teaching digital skills, including web marketing, SEO/SEA, and AI. Mathieu has authored multiple books on SEO and Google Ads and has worked as a web editor for the CNED. He has a deep understanding of web technologies, programming, and digital marketing.

Research Focus

Mathieu Chartier’s research in Digital Humanities focuses on enhancing historical data retrieval using Natural Language Processing (NLP) and Large Language Models (LLM). His work aims to develop innovative methods for historical inquiry, applying cutting-edge AI techniques to optimize information retrieval in history. Mathieu’s interdisciplinary approach blends technology and history, making significant contributions to both fields. His current research project, HiBenchLLM, investigates how to benchmark historical inquiries using LLMs, pushing the boundaries of digital history and artificial intelligence.

Publications

  • HiBenchLLM: Historical Inquiry Benchmarking for Large Language Models (2024) 📜🤖
  • Techniques de référencement web : audit et suivi SEO – 5th edition (2024) 📚💻
  • Google Ads : 60 fiches pour obtenir les certifications officielles (2022) 📘📈
  • Guide complet des réseaux sociaux (2013) 🌐📱
  • Le guide du référencement web (2013) 🔍🌍
  • Du bon usage des réseaux sociaux (BioContact n°313) 🗣️💬
  • Vie privée, l’enjeu du moment (BioContact n°272) 🔐📚
  • Media queries CSS3 pour le web mobile (Oracom, WebDesign magazine) 📱💻

Zdzislaw Kowalczuk | Artificial Intelligence Award | Best Researcher Award

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Prof Zdzislaw Kowalczuk | Artificial Intelligence Award | Best Researcher Award

Prof Zdzislaw Kowalczuk , Gdansk University of Technology , Poland

Zdzisław Kowalczuk, Senior Member of IEEE, has been a Full Professor in automatic control and robotics at Gdańsk University of Technology since 1978. He has held visiting positions at University of Oulu, Australian National University, Technische Hochschule Darmstadt, and George Mason University. His research interests include robotics, control theory, AI, and system diagnostics. Kowalczuk has authored 30 books, over 120 journal papers, and 350+ conference publications, with over 3,300 Google Scholar citations and an H-index of 21. He is President of the Polish Consultants Society and founder of PWNT publishing house, receiving numerous awards, including the SEP Medal in 2014. 🎓📚🏅

 

Publication profile 

Google scholar

Academic Background 🎓

Zdzisław Kowalczuk (Senior Member, IEEE) has been with the Faculty of Electronics, Telecomm., and Informatics at Gdańsk University of Technology since 1978. He is a Full Professor in automatic control and robotics and the Chair of the Dept. of Robotics and Decision Systems. He has held visiting appointments at universities including Oulu, Australian National University, Technische Hochschule Darmstadt, and George Mason University.

Scientific Contributions 

His main scientific interests include robotics, control theory, system modeling, diagnostics, artificial intelligence, and control engineering. Kowalczuk has authored/co-authored about 30 books, over 120 journal papers, and over 350 conference publications. His Google Scholar citation index exceeds 3,300, with an H-index of 21.

Research Focus

Zdzisław Kowalczuk’s research focuses on several key areas within engineering and computer science. His primary interests include fault diagnosis and detection, particularly for automotive engines, and the development of intelligent systems for autonomous decision-making. He also explores system modeling and control theory, including the application of artificial intelligence and neural networks. Kowalczuk’s work extends to robotics, adaptive systems, and signal processing, with a notable focus on practical applications like leak detection in pipelines and thermal management in buildings. His contributions span theoretical foundations to real-world implementations, demonstrating a versatile and impactful research portfolio. 🚗🤖📊🔧

 

Publication Top Notes

Fault diagnicial intelligence, applications – J Korbicz, JM Koscielny, Z Kowalczuk, W Cholewa, Springer Science & Business Media, 2012, cited by 1064 📚osis: models, artif

Diagnostyka procesów: modele: metody sztucznej inteligencji: zastosowania – J Korbicz, JM Kościelny, Z Kowalczuk, W Cholewa, Wydawnictwa Naukowo-Techniczne, 2002, cited by 345 📘

Model based diagnosis for automotive engines-algorithm development and testing on a production vehicle – J Gerler, M Costin, X Fang, Z Kowalczuk, M Kunwer, R Monajemy, IEEE Transactions on Control Systems Technology, 1995, cited by 148 🚗

Thermal Barrier as a technique of indirect heating and cooling for residential buildings – M Krzaczek, Z Kowalczuk, Energy and Buildings, 2011, cited by 107 🏠

Model-based on-board fault detection and diagnosis for automotive engines – JJ Gertler, M Costin, X Fang, R Hira, Z Kowalczuk, Q Luo, Control Engineering Practice, 1993, cited by 100 🚗

Autonomous driver based on an intelligent system of decision-making – M Czubenko, Z Kowalczuk, A Ordys, Cognitive computation, 2015, cited by 98 🚘

Discrete approximation of continuous-time systems: a survey – Z Kowalczuk, IEE Proceedings G (Circuits, Devices and Systems), 1993, cited by 84 📈

Computational approaches to modeling artificial emotion–an overview of the proposed solutions – Z Kowalczuk, M Czubenko, Frontiers in Robotics and AI, 2016, cited by 75 🤖

Continuous-time approaches to identification of continuous-time systems – Z Kowalczuk, J Kozłowski, Automatica, 2000, cited by 49 ⏱️

Intelligent decision-making system for autonomous robots – Z Kowalczuk, M Czubenko, Uniwersytet Zielonogórski, 2011, cited by 38 🤖

Detecting and locating leaks in transmission pipelines – Z Kowalczuk, K Gunawickrama, Fault Diagnosis: Models, Artificial Intelligence, Applications, 2004, cited by 36 🛠️📈