Saad Alqithami | Artificial Intelligence | Sustainable Engineering Award

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 🧠👾

 

 

Zdzislaw Kowalczuk | Artificial Intelligence Award | Best Researcher Award

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 🛠️📈