Prof. Mohammed Almulla | Machine Learning | Best Researcher Award

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Prof. Mohammed Almulla | Machine Learning | Best Researcher Award

VP Academic Affairs, Kuwait University, Kuwait

Professor Mohammed Ali Almulla is a distinguished Kuwaiti academic and researcher. With a career spanning over three decades, he has significantly contributed to the field of computer science, particularly in areas such as web services, emotion recognition, and fuzzy logic techniques. He is currently a Professor at Kuwait University and has held various leadership positions, including Chairman of the Department of Computer Science. His work has garnered recognition through several publications, research awards, and innovations in the realm of machine learning, artificial intelligence, and medical expert systems. Professor Almulla is known for his comprehensive research approach and deep engagement with emerging technologies, bridging academia and industry. His scholarly contributions are frequently cited, underlining his influence within the academic community.

Profile

Education

Professor Almulla completed his B.Sc. (1986), M.Sc. (1990), and Ph.D. (1995) in Computer Science from McGill University, Canada. His Ph.D. thesis, titled “Analysis of the Use of Semantic Trees in Automated Theorem Proving”, laid the foundation for his future research endeavors. With a deep understanding of theoretical and applied computer science, he has focused on machine learning, fuzzy systems, and semantic analysis. His education from McGill University, a globally recognized institution, has helped him build a solid academic foundation. Additionally, he possesses a comprehensive grasp of Arabic and English, enabling him to communicate and collaborate across cultures and academic circles.

Experience

Professor Almulla’s career at Kuwait University started in 1986 when he began as an Instructor. He progressed to Assistant Professor (1995–2006), then Associate Professor (2006–2021), and is currently serving as a Professor (2021–present). He has also been actively involved in departmental administration, having served as Chairman (2015–2020) and Graduate Program Director (2010–2013). Under his leadership, the Department of Computer Science achieved ABET accreditation, an outstanding accomplishment. His role as Acting Chairman in Mathematics and Computer Science in various periods further exemplifies his leadership skills. His dedication to advancing higher education and research has been integral to the development of the computer science field in Kuwait.

Awards and Honors

Professor Almulla’s academic excellence has been recognized through several Incentive Rewards for Unfunded Research in 2014, 2015, and 2017, with impactful papers published in journals such as Knowledge-Based Systems. His work on service trust behaviors, web services ranking, and fuzzy techniques has earned him significant recognition. He was also honored with Distinctive Teaching Awards in both the College of Computer Science and Engineering (2011/2012) and the Faculty of Science (2001/2002). These awards underscore his excellence in teaching, his commitment to innovative research, and his positive impact on student education.

Research Focus

Professor Almulla’s research focuses on a wide array of cutting-edge topics in computer science. Key areas of expertise include machine learning, fuzzy systems, service trust behaviors, and medical expert systems. His recent work explores emotion recognition systems, federated learning, and web services ranking. In addition, he has contributed to advancements in semantic similarity, automated theorem proving, and healthcare applications. With an eye toward the future, his research continues to bridge the gap between theoretical models and real-world applications, particularly in healthcare and artificial intelligence.

Publication top Notes

  • A Trust-based Global Expert System for Disease Diagnosis Using Hierarchical Federated Learning 🏥🤖
  • A Novel CLIPS-based Medical Expert System for Migraine Diagnosis and Treatment Recommendation 💡🧠
  • On the Effect of Prior Knowledge in Text-Based Emotion Recognition 🧠💬
  • A Multimodal Emotion Recognition System Using Deep Convolution Neural Networks 🖥️🔍
  • Location-based Expert System for Diabetes Diagnosis and Medication Recommendation 🏥💊
  • Measuring Semantic Similarity between Services Using Hypergraphs 🧠🌐
  • Specification and Recognition of Service Trust Behaviors 💻✅
  • Next-Generation Sequencing in Familial Breast Cancer Patients from Lebanon 🧬🎗️
  • A New Framework for the Verification of Service Trust Behaviors 🛡️💡
  • GeoCover: An Efficient Sparse Coverage Protocol for RSU Deployment over Urban VANETs 🚗🌍
  • A New Fuzzy Hybrid Technique for Ranking Real World Web Services 🌐🔍

 

 

 

Duaa Mehiar | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr Duaa Mehiar | Artificial Intelligence | Best Researcher Award

Assistant Professor, Middle East University, Jordan

Duaa Mehiar is an expert in Artificial Intelligence and Robotics, currently part of the Department of IT at Middle East University. She has a strong background in developing intelligent robotic systems, optimizing robotic swarm behaviors, and exploring AI applications in education and healthcare. Duaa is passionate about the intersection of technology and practical solutions, particularly in enhancing robot autonomy and improving human-robot interactions. She has contributed significantly to research in robotic optimization and AI systems, with numerous publications in international journals.

Professional Profile

Google Scholar

Orcid

Scopus

Strengths for the Award

Duaa Mehiar is an accomplished researcher in the fields of Artificial Intelligence (AI) and Robotics. With a PhD in AI from the University of Malaya, her extensive academic background, demonstrated by her impactful research on optimization methods in robot swarm behaviors, makes her a prime candidate for the Best Researcher Award. Her published works in high-impact journals and international conferences, including contributions to cloud-based frameworks for social robotics and AI-based systems for education, have received recognition in academia. Duaa’s research on dynamic task distribution in drone swarms and deep fake image detection also highlights her broad expertise in both practical applications and cutting-edge AI research.

Areas for Improvement

Although Duaa has made significant strides in her research, further collaboration with interdisciplinary teams in the fields of neuroscience and psychology could enhance the human-robot interaction aspects of her work, especially with virtual agents. Expanding the scope of her research to explore more industry-based applications of her findings, particularly in education and healthcare, would also make her work more impactful. Additionally, more emphasis on real-world robotic deployments could demonstrate her research’s practical outcomes.

Education

  • Ph.D. in Artificial Intelligence – University of Malaya, 2016–2021
    Thesis: Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication
  • MSc in Computer Science – Al Balqa Applied University, Jordan, 2007–2009
    Thesis: The Multi-Robot Cooperative System for Objects Detection
  • B.Sc. in Computer Science – Al Zaytoona University, Jordan, 1998–2002
    Graduation Project: Production System for Oriental Arabs using Oracle Language

Experience

Duaa Mehiar has a wealth of experience in the field of robotics and AI. She has trained teachers and school supervisors on integrating AI into education, including using metaverse and robots. Duaa was involved in numerous training programs with institutions like EduTech and Ishraq Institute. She has contributed to robotic research and development, from swarm optimization algorithms to practical applications like controlling robots using various protocols. Her expertise includes IoT projects and robot building using Arduino technology.

Awards and Honors

Duaa has received multiple honors for her work in robotics and AI. She was nominated as a trainer for the Ministry of Education in Dubai and Ras Al Khaima for teaching robotic theory and practice. She has also been part of the Arab Robotics Association and has served as a judge for the Arab Robotics Competition. Her research in AI and robotics has been recognized by international platforms, earning her citations and respect within the scientific community.

Research Focus

Duaa’s research primarily focuses on AI and robotics, particularly in optimization algorithms for swarm robots, human-robot interaction, and AI applications in education and healthcare. She has developed quantum-behaved swarm optimization methods for robot exploration and communication. Her interests include improving robotic autonomy, integrating robots in educational environments, and exploring AI systems in healthcare, such as asthma management and rehabilitation. She is dedicated to advancing AI technologies to benefit society.

Publication Top Notes

  • Revolutionizing Social Robotics: A Cloud-Based Framework for Enhancing the Intelligence and Autonomy of Social Robots 🤖
  • Towards Renewable Urban Landscapes: Exploring Photovoltaic Panel Integration – A Case Study 🌍
  • Chatbots in Classrooms: Tailoring Education and Boosting Engagement 🎓
  • QRDPSO: A New Optimization Method for Swarm Robot Searching and Obstacle Avoidance in Dynamic Environments 🤖
  • Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections 🎥
  • Report on Optimization for Efficient Dynamic Task Distribution in Drone Swarms Using QRDPSO Algorithm 🚁
  • Linguistic and Gender Factors in User Engagement with Arabic LLM-Based Virtual Agents for Rehabilitation 🧑‍💻
  • Real-Time Student Attention Evaluation and Engagement Recommendation System Using AI-Based Behavior Analysis 📚
  • Personalized Alarming System for Asthma Management Based on Lung Functionality 🫁
  • Reducing Interrupts Among Robots in Quantum-Behaved Swarm Exploration with MR-LEACH 🤖
  • Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication 🔍
  • Multi-Robot Cooperative System for Object Detection 🤖
  • QRDPSO Equation: A New Optimization Method for Swarm Robot 🏎
  • Multi-Agent Cooperative System for Object Detection 🛠
  • Multi-Robot System for Search and Rescue Operations 🚑

Conclusion

Duaa Mehiar stands out for her contributions to the fields of AI and Robotics, with a focus on innovative solutions to enhance autonomous robotic systems and optimize AI-driven tasks. She demonstrates strong academic potential, with a portfolio of research that is not only technically sound but also socially relevant, particularly in education and healthcare. For the Best Researcher Award, her continued growth in interdisciplinary collaboration and real-world applications would solidify her place as a leading researcher in her field.

Rihab Mâaloul Abid – Computer science – Best Researcher Award

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Rihab Mâaloul Abid - Computer science - Best Researcher Award

isima - Tunisia

AUTHOR PROFILE

SCOPUS

🔬 CURRENT POSITION

Rihab Mâaloul Abid is a prominent member of the LT2S (Laboratoire des Technologies des Systèmes Smart) at the Centre de Recherche en Numérique de Sfax, Technopôle. She also serves as a Maître Assistant at the Institut Supérieur d'Informatique et de Multimédia de Mahdia (ISIMa), where she contributes to both teaching and research in the field of computer science and multimedia.

🎓 ACADEMIC BACKGROUND

Dr. Mâaloul Abid earned her Doctorate in Engineering of Computer Systems in April 2018 from ENIS, Université de Sfax, Tunisia. Her doctoral research focused on energy-aware routing in carrier-grade Ethernet networks, under the supervision of Prof. Lamia Chaari Fourati at LT2S. She also holds a Master’s degree in Computer Science and Multimedia from the Institut Supérieur d'Informatique et de Multimédia de Sfax, where she conducted in-depth analysis of scheduling mechanisms for WiMAX networks, receiving a "Très bien" distinction.

💻 RESEARCH INTERESTS

Dr. Mâaloul Abid's research is primarily focused on innovative networking technologies and energy efficiency in communication systems. Her work on energy-aware routing and scheduling mechanisms for networks, including WiMAX, reflects her dedication to advancing the efficiency and sustainability of digital infrastructures. Her academic journey began with a Bachelor’s degree in Computer Science and Multimedia, where her project on automatic brain tissue segmentation for tumor detection laid the groundwork for her future research endeavors.

📚 TEACHING AND PEDAGOGICAL ACTIVITIES

As an educator, Dr. Mâaloul Abid has been actively involved in teaching a variety of courses at ISIMS. During the 2021-2022 academic year, she taught courses on network services, operational research, and programming workshops to students pursuing degrees in computer science. Her commitment to education extends beyond traditional lectures, as she is deeply involved in developing practical skills in her students, ensuring they are well-prepared for careers in technology and multimedia.

🌍 CONTRIBUTION TO NETWORK SERVICES

Throughout her career, Dr. Mâaloul Abid has made significant contributions to the study and development of network services. Her expertise in foundational and advanced network topics has been shared with her students, helping to shape the next generation of computer scientists. Her work in this area is recognized for its practical applications and relevance to the evolving needs of digital communication systems.

🔧 INNOVATION IN COMPUTER SCIENCE

Innovation is at the heart of Dr. Mâaloul Abid’s research. Her focus on energy-aware technologies and system optimization highlights her commitment to creating more efficient and sustainable computing environments. Her ongoing research in smart systems and her role in the LT2S laboratory position her as a key player in the field of computer science innovation.

🏅 ACADEMIC EXCELLENCE

Throughout her academic career, Dr. Mâaloul Abid has consistently demonstrated excellence, receiving honors and distinctions for her work. From her undergraduate studies to her doctoral research, her dedication to her field has been evident, earning her respect and recognition within the academic community.

Senbagavalli – Artificial Intelligence – Best Researcher Award

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Senbagavalli - Artificial Intelligence - Best Researcher Award

Alliance University - India

AUTHOR PROFILE

SCOPUS

EXPERT IN OPINION MINING AND FEATURE SELECTION

Senbagavalli's groundbreaking research in opinion mining of health data for cardiovascular disease diagnosis using an unsupervised feature selection algorithm spans five years. Her Ph.D. work is a testament to her dedication to leveraging data for medical advancements.

FACIAL RECOGNITION INNOVATOR

With a master's degree in engineering, Senbagavalli developed a face recognition system using Laplacian faces, showcasing her expertise in computer vision and pattern recognition. This project exemplified her ability to apply complex algorithms to practical applications within six months.

PIONEER IN UNICODE FILE SYSTEMS

During her undergraduate studies, Senbagavalli created a file system using the Unicode character set, a project completed in just six months. Her work in this area highlights her proficiency in software development and system design.

CREATOR OF GRAPHIC GAMING SYSTEMS

In her mini-project as an undergraduate, she developed a gaming system using graphics within three months. This early project laid the foundation for her interest in interactive and visual computing systems.

SEASONED ACADEMIC AND PROFESSOR

With 18 years and 7 months of teaching experience, Senbagavalli has held positions at prestigious institutions, including Alliance University and Kuppam Engineering College. Her extensive experience has made her a respected figure in the academic community.

VERSATILE SUBJECT EXPERT

Senbagavalli has taught a wide range of subjects to undergraduate, postgraduate, and Ph.D. students, including Data Modeling and Optimization, Object-Oriented Programming, and Software Engineering. Her comprehensive knowledge spans multiple domains of computer science.

ACTIVE RESEARCHER AND REVIEWER

An active member of various academic councils and editorial boards, Senbagavalli reviews for renowned publishers like Bentham Science and Elsevier. Her involvement in curriculum development, project evaluation, and seminar organization reflects her commitment to academic excellence and continuous learning.

NOTABLE PUBLICATION

Identification of Biomarker for Autism Spectrum Disorder Using EEG: A Review.
Authors: K. Lalli, M. Senbagavalli
Year: 2023
Conference: Proceedings - 2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023, pp. 45–50

Facemask Detection System Using CNN Model.
Authors: M. Senbagavalli, S. Debnath, R. Rajagopal, K. Ghildial
Year: 2023
Conference: International Conference on Recent Advances in Science and Engineering Technology, ICRASET 2023

An Evaluation of Machine Learning Techniques for Detecting Banking Frauds.
Authors: R. Rajagopal, M. Senbagavalli, S. Debnath, K. Darshan, K.S. Varun Tejas
Year: 2023
Conference: International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 359–365

Deep Learning Model for Flood Estimate and Relief Management System Using Hybrid Algorithm.
Authors: M. Senbagavalli, V. Sathiyamoorthi, S.K. Manju Bargavi, S. Shekarappa G., T. Jesudas
Year: 2023
Book: Artificial Intelligence and Machine Learning in Smart City Planning, pp. 29–44

An Effective Model for Predicting Agricultural Crop Yield on Remote Sensing Hyper-Spectral Images Using Adaptive Logistic Regression Classifier.
Authors: V. Sathiyamoorthi, P. Harshavardhanan, H. Azath, A.M. Viswa Bharathy, B.S. Chokkalingam
Year: 2022
Journal: Concurrency and Computation: Practice and Experience, 34(25), e7242

Everton – Artificial Intelligence – Best Researcher Award

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Everton - Artificial Intelligence - Best Researcher Award

Universidade Federal da Grande Dourados - Brazil

AUTHOR PROFILE

SCOPUS

ACADEMIC AFFILIATION

Everton is associated with Universidade Católica Dom Bosco, where he contributes to cutting-edge research in computer vision and its applications in agriculture and urban studies.

PRECISION AGRICULTURE RESEARCH

His research in precision agriculture includes the integration of UAV technology and machine learning to optimize farming practices. By improving weed and pest detection methods, his work supports sustainable agriculture and food security.

COMPUTER VISION IN AGRICULTURE

Everton's expertise in computer vision extends to various agricultural applications, from crop monitoring to automated harvesting systems. His innovative solutions help in increasing agricultural productivity and efficiency.

REAL-TIME WEED DETECTION IN SOYBEAN USING UAV IMAGES

Everton Castelão Tetila specializes in the real-time detection of weeds in soybean fields through the innovative use of UAV (Unmanned Aerial Vehicle) images. His work significantly contributes to precision agriculture, enabling farmers to identify and manage weeds more efficiently.

YOLO PERFORMANCE ANALYSIS FOR SOYBEAN PEST DETECTION

Everton has conducted extensive performance analysis of the YOLO (You Only Look Once) algorithm for the real-time detection of soybean pests. His research enhances pest management practices, ensuring timely interventions and reducing crop damage.

URBAN AREA CLASSIFICATION AND MONITORING USING COMPUTER VISION

He applies advanced computer vision techniques for the classification and monitoring of urbanized areas. This work aids in urban planning and development, providing detailed and accurate assessments of urban growth and infrastructure.

EDUCATIONAL CONTRIBUTIONS

He is dedicated to advancing education in his field, sharing his knowledge and findings through publications and presentations. His contributions help train the next generation of researchers and professionals in computer vision and its agricultural applications.

NOTABLE PUBLICATION

YOLO performance analysis for real-time detection of soybean pests
Authors: E.C. Tetila, F.A.G. da Silveira, A.B. da Costa, H. Pistori, J.G.A. Barbedo
Year: 2024
Journal: Smart Agricultural Technology, 7, 100405

Title: Classification and monitoring of urbanized areas using computer vision techniques | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional
Authors: E.C. Tetila, P.M. de Moraes, M. Constantino, M.M.D.M. Greco, H. Pistori
Year: 2023
Journal: Desenvolvimento e Meio Ambiente, 61, pp. 32–42

Title: An approach for applying natural language processing to image classification problems
Authors: G. Astolfi, D.A. Sant'Ana, J.V.D.A. Porto, E.T. Matsubara, H. Pistori
Year: 2022
Journal: Neurocomputing, 513, pp. 372–382

Title: Performance Analysis of YOLOv3 for Real-Time Detection of Pests in Soybeans
Authors: F.A.G. Silveira, E.C. Tetila, G. Astolfi, A.B. Costa, W.P. Amorim
Year: 2021
Conference: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13074 LNAI, pp. 265–279

Title: Associative classification model for forecasting stock market trends
Authors: E.C. Tetila, B.B. MacHado, J.F. Rorigues, M. Constantino, H. Pistori
Year: 2021
Journal: International Journal of Business Intelligence and Data Mining, 19(1), pp. 97–112