Duaa Mehiar | Artificial Intelligence | Best Researcher Award

Published on by Civil Engineering

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.

AZIZI ABDULLAH | Computer Vision | Best Paper Award

Published on by Civil Engineering

Assoc. Prof. Dr AZIZI ABDULLAH | Computer Vision | Best Paper Award

Researcher, Universiti Kebangsaan Malaysia, Malaysia

Azizi Abdullah is an esteemed academic and researcher, currently serving as an Associate Professor at Universiti Kebangsaan Malaysia. He holds a Ph.D. in Computer Vision from Utrecht University, The Netherlands. With over two decades of experience in the fields of machine learning, computer vision, and robotics, Dr. Abdullah is recognized for his contributions to medical applications, particularly breast cancer classification and object recognition. He has authored several influential research papers and is an expert in Simultaneous Localization and Mapping (SLAM). Dr. Abdullah is passionate about advancing AI and deep learning techniques, with a focus on applications in autonomous vehicles and medical image analysis.

PROFESSIONAL PROFILE

Google Scholar

Orcid

STRENGTHS FOR THE AWARD

  1. Strong Academic Foundation: Azizi Abdullah holds a Ph.D. in Computer Vision from Utrecht University, The Netherlands, along with a Master’s in Software Engineering and a Bachelor’s in Computer Science. This strong academic background provides a solid foundation for his research endeavors.
  2. Proven Research Impact: Abdullah’s publications reflect significant contributions in computer vision, machine learning, and robotics, with a focus on real-world applications in areas such as medical diagnostics (e.g., breast cancer classification) and autonomous systems (e.g., autonomous vehicle systems and SLAM). The high citation count for his work highlights the widespread impact of his research in the academic community.
  3. Diverse Research Interests: His research spans several cutting-edge areas, including deep learning, AI, object recognition, and autonomous mobile robotics. This multidisciplinary approach is critical for advancing knowledge in these fields.
  4. Leadership and Experience: Having held academic positions from Lecturer to Associate Professor at Universiti Kebangsaan Malaysia, Abdullah has demonstrated leadership in both research and teaching, further underlining his ability to shape the future of the field.

AREAS FOR IMPROVEMENT

  1. Expansion of Collaborative Research: While Abdullah has published extensively, fostering collaborations with more international researchers could further broaden the scope and impact of his work.
  2. Interdisciplinary Applications: Although Abdullah’s research touches on multiple domains, additional focus on interdisciplinary applications, particularly in industries outside academia (e.g., healthcare, manufacturing), could maximize the practical application of his work.

EDUCATION

Dr. Azizi Abdullah earned his Ph.D. in Computer Vision from Utrecht University in 2010. He completed his Master of Software Engineering (MSE) at Universiti Malaya in 1999 and his Bachelor of Science in Computer Science from Universiti Kebangsaan Malaysia in 1996. His academic journey reflects his deep commitment to expanding his expertise in software engineering, artificial intelligence, and computer vision, which are central to his groundbreaking work in machine learning and robotics. His diverse academic background has laid the foundation for his successful career in both research and teaching.

EXPERIENCE

Dr. Abdullah’s academic career spans over two decades, beginning as a Research Assistant at Universiti Kebangsaan Malaysia in 1997. He served as a Tutor and Lecturer before being promoted to Senior Lecturer in 2010. His expertise and leadership earned him the title of Associate Professor in 2015. Throughout his career, Dr. Abdullah has made significant contributions to teaching and research, guiding numerous students in software engineering, computer vision, and AI. He has also played an active role in various academic and research initiatives, further enhancing the global impact of his work.

AWARDS AND HONORS

Dr. Abdullah’s exceptional research contributions have earned him recognition in the fields of computer vision, machine learning, and AI. His work on improving neural network performance and breast cancer classification using deep learning has received widespread acclaim. His research on object categorization and autonomous vehicles has been influential in both academic and industrial sectors. In addition to his numerous citations, Dr. Abdullah’s expertise continues to be acknowledged with awards for his outstanding contributions to technological advancements and the scientific community.

RESEARCH FOCUS

Dr. Abdullah’s research is primarily focused on the intersection of computer vision, machine learning, and robotics. His current work revolves around deep learning models, particularly their application in medical image analysis, such as breast cancer detection. He also explores object categorization and recognition using machine learning techniques. Another key area of his research is autonomous mobile robots, specifically Simultaneous Localization and Mapping (SLAM), which is integral to the development of autonomous systems. His interdisciplinary approach combines cutting-edge AI algorithms with practical applications in medical and robotics fields.

PUBLICATION TOP NOTES

  • Deep CNN model based on VGG16 for breast cancer classification 🏥
  • A linear model based on Kalman filter for improving neural network classification performance 🤖
  • Support vector machine approach to real-time inspection of biscuits on moving conveyor belt 🍪
  • Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading 🧬
  • Detection of leukemia in human blood sample based on microscopic images 🩸
  • Vision-based autonomous vehicle systems based on deep learning: A systematic literature review 🚗
  • Machine vision for crack inspection of biscuits featuring pyramid detection scheme 🍪
  • An ensemble of deep support vector machines for image categorization 🖼️
  • Spatial pyramids and two-layer stacking SVM classifiers for image categorization 🖼️
  • Fixed partitioning and salient points with MPEG-7 cluster correlograms for image categorization 🖼️

CONCLUSION

Azizi Abdullah is a highly deserving candidate for the “Best Researcher Award.” His strong academic qualifications, broad research interests, and impactful contributions to computer vision, AI, and robotics make him a standout figure in his field. While there is room to enhance the interdisciplinary reach and foster more international collaborations, his record of achievement in both theory and application positions him as an influential researcher poised to continue making significant advancements in his areas of expertise.

Sina Fard Moradinia | Machin Learning | Best Researcher Award

Published on by Civil Engineering

Assist. Prof. Dr Sina Fard Moradinia | Machine Learning | Best Researcher Award

Reviewer&Editor, Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

Dr. Sina Fard Moradinia is an Assistant Professor in the Department of Civil Engineering at Islamic Azad University, Tabriz Branch, Iran. He specializes in water resource management, hydrology, hydraulic engineering, computational fluid dynamics, and the application of machine learning in civil engineering. With a strong academic background and a focus on integrating advanced technologies, Dr. Fard Moradinia has contributed significantly to research in sustainable construction, water management, and infrastructure optimization. His work is recognized for its innovative approaches to environmental and structural challenges, particularly in dam construction, flood prediction, and water resource forecasting. He has authored several peer-reviewed papers and participated in numerous academic and professional conferences.

Profile

Google Scholar

Orcid

Scopus

Strengths for the Award

Dr. Sina Fard Moradinia is a highly accomplished researcher and educator in civil engineering, particularly in the areas of water resource management, hydrology, hydraulics, and computational fluid dynamics. His research contributions are diverse and impactful, addressing key challenges in dam construction, flood risk prediction, and sustainable water management. Dr. Fard Moradinia’s ability to integrate machine learning with traditional engineering models to solve complex problems stands out as a significant strength. His extensive body of work, evidenced by multiple publications in high-impact journals, reflects his proficiency in both theoretical and applied research, especially in projects that integrate Building Information Modeling (BIM), System Dynamics, and ANFIS models for project optimization.

Dr. Fard Moradinia has demonstrated leadership in his field through innovative research in human resource risk analysis in construction, water quality management, and the use of computational models to optimize construction project time and cost. His work on flood flow prediction and seepage analysis in earth dams is a testament to his ability to address real-world infrastructure challenges with advanced methodologies.

Areas for Improvements

While Dr. Fard Moradinia has a robust and impressive portfolio of research, there are a few areas where improvements or further development could enhance his profile for recognition.

  1. Broader Global Collaboration: Although his work is highly relevant within the local context of Iran, expanding his collaborative efforts with international researchers, especially in global water management issues or climate change adaptation strategies, could increase the global impact of his research.
  2. Interdisciplinary Approaches: There is an opportunity for Dr. Fard Moradinia to explore more interdisciplinary research areas, such as the integration of civil engineering with environmental science, data analytics, or sustainable urban planning. This could make his work even more relevant to the global discourse on climate change and urban sustainability.
  3. Public Engagement and Outreach: While his academic and research credentials are strong, increasing his presence in public and policy-making circles, particularly in the context of water crisis management and sustainable infrastructure, could make his work more impactful outside academia.

Education 

Dr. Sina Fard Moradinia holds a Ph.D. in Civil Engineering, focusing on hydrology and water resources management, from an esteemed institution in Iran. His academic journey includes both Bachelor’s and Master’s degrees in Civil Engineering, where he developed a solid foundation in fluid dynamics, hydrology, and structural engineering. Dr. Fard Moradinia has continually expanded his expertise through advanced research in the application of computational techniques, including machine learning algorithms for solving complex civil engineering problems. His educational background reflects a commitment to both theoretical and practical aspects of civil engineering, preparing him for an impactful academic career in the field.

Experience 

Dr. Sina Fard Moradinia has accumulated a wealth of experience in both academic and research settings. As an Assistant Professor at Islamic Azad University in Tabriz, he teaches and mentors students in civil engineering, with an emphasis on hydrology, water resource management, and advanced computational methods. In addition to his teaching role, he is actively involved in high-impact research projects, collaborating with professionals in the fields of water resources, infrastructure, and construction management. His research spans areas such as flood prediction, water quality management, construction project optimization, and the use of artificial intelligence for infrastructure analysis. Dr. Fard Moradinia has also applied his expertise in industry-focused projects, working with governmental and private organizations to enhance the design and management of civil infrastructure, particularly in dam construction, flood mitigation, and reservoir management.

Awards and Honors

Dr. Sina Fard Moradinia’s research has garnered recognition from various academic and professional institutions. His publications have received multiple citations, attesting to the impact of his work in civil engineering, hydrology, and water resource management. He has been honored with awards for his contributions to research and education, including recognition for excellence in the application of machine learning techniques to civil engineering problems. Dr. Fard Moradinia has been invited to speak at international conferences and serve on editorial boards for leading journals in his field. Additionally, his role as a reviewer for numerous scholarly publications further solidifies his standing as a respected figure in his domain. His collaborative efforts with industry partners have also resulted in several successful projects aimed at improving infrastructure sustainability and management in Iran.

Research Focus

Dr. Sina Fard Moradinia’s research focuses on applying advanced computational techniques to solve pressing issues in civil engineering, particularly in the areas of water resources management, hydrology, and hydraulic engineering. His work explores innovative solutions for flood prediction, aquifer management, and sustainable water usage, with a strong emphasis on integrating machine learning and artificial intelligence. Dr. Fard Moradinia also investigates the optimization of construction projects, particularly in the context of dam and reservoir management, where he applies Building Information Modeling (BIM) and system dynamics to improve project efficiency and reduce risks. Another key area of his research is the analysis of environmental factors influencing civil infrastructure, such as the impact of sludge discharge in wastewater systems. Through his work, he aims to advance both the scientific understanding of hydrological systems and the practical tools available for managing water resources and infrastructure projects.

Publication Top Notes

  • “Toward Nearly Zero Energy Building Designs: A Comparative Study of Various Techniques” 🌱🏢
  • “Time and Cost Management of Dam Construction Projects Based on BIM” 💼🏞️
  • “The Role of BIM in Reducing the Number of Project Dispute Resolution Sessions” ⚙️💬
  • “Wavelet-ANN Hybrid Model Evaluation in Seepage Prediction in Nonhomogeneous Earth Dams” 🌊🧠
  • “Optimization of Quantitative and Qualitative Indicators of Construction Projects” ⚙️📊
  • “An Approach for Flood Flow Prediction Using New Hybrids of ANFIS” 🌧️🔮
  • “Forecasting the Level of Aquifers in the Ajab Shir Plain with Different Management Scenarios” 💧🔍
  • “Development of an ANFIS Model for Human Resource Risk Analysis in Construction” 🏗️🧑‍💼
  • “Using Umbrella Arch Method in Design of Tunnel Lining” 🏞️⚒️
  • “Evaluation of Water Diversion Tunnel Lining Using Numerical Model” 🔢🌍
  • “Analysis and Investigation of Hydrological Drought Indicators in Mahenshan” 🌵💧
  • “A Novel Approach to Flood Risk Zonation: Integrating Deep Learning Models with APG” 💻🌊
  • “The Prediction of Precipitation Changes in the Aji-Chay Watershed Using CMIP6 Models” 🌧️📈
  • “Applying Project Knowledge Management to Enhance Time and Cost Efficiency in Water Reservoir Projects” 🕒💡
  • “Developing a System Dynamics Model to Study Human Resource Motivation and Time Productivity” 🕹️💼
  • “Investigating Strategies for Implementing Knowledge Management in Dam Construction Projects” 🏗️📚
  • “Simulation of Delay Factors in Dam Construction Projects with System Dynamics” ⏳🏞️
  • “Mathematical Equations for Grouting Pressure and Intensity in Joint Rocks” 🏔️🛠️
  • “Investigation of Excavation Behavior in Soil Nailing for Construction” 🏗️🌍
  • “Study of the Effects of Sludge Discharge from Water Treatment Plants” ♻️💧

Conclusion

Dr. Sina Fard Moradinia’s exceptional contributions to civil engineering, particularly in water resource management, hydrology, and construction project optimization, make him a strong candidate for the Best Researcher Award. His work, combining cutting-edge computational techniques and practical engineering solutions, addresses some of the most pressing challenges in sustainable development and infrastructure resilience. His innovative approaches in dam construction, flood prediction, and water quality management not only benefit academia but also have significant implications for real-world applications. With his continued focus on advancing research methodologies and expanding his influence both nationally and internationally, Dr. Fard Moradinia has the potential to be a leading figure in shaping the future of civil engineering and environmental management.

Bin Yang – AI for Everything – Best Researcher Award

Published on by Civil Engineering

Bin Yang - AI for Everything - Best Researcher Award

Chongqing University of Posts and Telecommunications - China

AUTHOR PROFILE

SCOPUS

ORCID

🧑‍🏫 ACADEMIC BACKGROUND AND RESEARCH PASSION

Dr. Bin Yang, also known as Sean Bin Yang, is an Assistant Professor at Chongqing University of Posts and Telecommunications. With a deep passion for leveraging big data and artificial intelligence (AI) to address urban challenges, he has been making significant contributions to the field. He is also a member of the Chongqing Key Laboratory of Image Cognition, working closely with Prof. Xinbo Gao.

🎓 EDUCATION AND GLOBAL COLLABORATIONS

Dr. Yang obtained his Ph.D. in Computer Science from Aalborg University in 2022, under the guidance of Prof. Bin Yang and Associate Prof. Jilin Hu. During his doctoral studies, he collaborated with renowned researchers at the Center for Data-Intensive Systems (Daisy) and the Machine Learning Group. He also spent time at the Mila-Quebec AI Institute in Canada, working with Associate Prof. Jian Tang.

📚 PROLIFIC PUBLICATION RECORD

Dr. Yang has authored more than 20 peer-reviewed publications in prestigious international journals and conferences, including KDD, ICML, and TKDE. His work, such as the development of lightweight path representation models, has gathered over 452 citations, with an h-index of 13. His innovative research in data mining, machine learning, and AI continues to push the boundaries of knowledge in these fields.

💡 INNOVATIVE PATENTS AND TECHNOLOGY APPLICATIONS

Dr. Yang's commitment to practical applications of his research is demonstrated by his filing of over 10 patents in China. These patents reflect his dedication to advancing technology through innovation, particularly in the fields of AI-driven solutions for urban and transportation challenges.

🎓 SUPERVISION AND MENTORSHIP

As a dedicated mentor, Dr. Yang has supervised numerous student research projects, including those on construction waste management through AI techniques. His guidance has led to the publication of impactful research articles, helping his students make meaningful contributions to the field of artificial intelligence and urban problem-solving.

🔬 RESEARCH IN AI AND URBAN CHALLENGES

Dr. Yang's research focuses on using AI to tackle complex urban issues, such as waste management, transportation optimization, and infrastructure development. His work in path representation learning, unsupervised learning, and predictive autoscaling has significantly contributed to the advancement of smart city technologies.

🏅 CONFERENCE AND JOURNAL INVOLVEMENT

Dr. Yang is an active member of the research community, serving as a Program Committee member for top conferences like ICML, KDD, and IJCAI. His expertise is frequently sought as a reviewer for leading journals such as IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Intelligent Transportation Systems, highlighting his influence in the AI and big data research domains.

NOTABLE PUBLICATION

Title:Extended-state-observer-based double-loop integral sliding-mode control of electronic throttle valve
Authors: Y. Li, B. Yang, T. Zheng, Y. Li, M. Cui, S. Peeta
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2015

Title: Unsupervised path representation learning with curriculum negative sampling
Authors: S.B. Yang, C. Guo, J. Hu, J. Tang, B. Yang
Journal: arXiv preprint arXiv:2106.09373

Title: Context-aware path ranking in road networks
Authors: S.B. Yang, C. Guo, B. Yang
Journal: IEEE Transactions on Knowledge and Data Engineering
Year: 2020

Title: Luenberger-sliding mode observer based fuzzy double loop integral sliding mode controller for electronic throttle valve
Authors: B. Yang, M. Liu, H. Kim, X. Cui
Journal: Journal of Process Control
Year: 2018

Title: An extended continuum model incorporating the electronic throttle dynamics for traffic flow
Authors: Y. Li, H. Yang, B. Yang, T. Zheng, C. Zhang
Journal: Nonlinear Dynamics
Year: 2018

Senbagavalli – Artificial Intelligence – Best Researcher Award

Published on by Civil Engineering

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

Published on by Civil Engineering

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

Ali Haider Khan – AI – Best Researcher Award

Published on by Civil Engineering

Ali Haider Khan - AI - Best Researcher Award

Ziauddin University - Pakistan

AUTHOR PROFILE

SCOPUS

EXPERIENCE

Ali Haider Khan is a seasoned biomedical engineer with extensive experience across various hospitals and enterprises in Pakistan. His tenure at Bahawal Victoria Hospital involved working with clinical laboratory equipment, ensuring their optimal functionality. At Al-Qadir Enterprises, his role in Radiology, Ultrasound, and Operating Theaters showcased his commitment to enhancing patient care. His earlier internships at Doctor’s Hospital and Ziauddin Hospital provided him with a solid foundation in biomedical engineering, covering aspects from service and safety to supply chain management.

UNIVERSITY PROJECTS

Ali's academic projects demonstrate his innovative spirit and technical expertise. His pioneering work on the real-time recognition of Pakistani Sign Language through a web application highlights his proficiency in using CNN and LSTM models. Additionally, his research on the trans-vascular transport efficiency of nanoparticles in tumor microenvironments via Computational Fluid Dynamics (CFD) shows his adeptness in using Ansys software. His project on anxiety detection and massage-based control through pulse oximetry exemplifies his ability to combine technology and healthcare for therapeutic solutions.

SKILLS & INTERESTS

Ali is well-versed in frontend development, Python, Microsoft Azure, and various other technical tools like Visual Studio and Jupyter Notebook. His creative skills extend to Photoshop and Canva, and he is an effective communicator. Outside of his professional interests, Ali enjoys playing cricket and table tennis and has a keen interest in researching economic issues.

ACHIEVEMENTS

Ali's accomplishments are a testament to his dedication and continuous learning. He completed a crash course on Python by Google and participated in the 7th All Pakistan DUHS-DICE Health Innovation Exhibition. His proficiency in the German language was honed at the Goethe Institute, Karachi. He also attended the IEEE Asia Pacific Comsoc Summer School on Autonomous Systems and completed courses on web development and artificial intelligence from prestigious institutions like the University of Michigan and Accenture.

MEMBERSHIPS

Ali is an active member of several esteemed organizations, including the Harvard Business School Club of Pakistan, the Institute of Electrical and Electronics Engineers (IEEE), and the Society for Peace and Harmony. These memberships reflect his commitment to professional development and community engagement.

PUBLICATIONS

Ali has contributed significantly to the field of biomedical engineering and computer science through his publications. His work on the recognition and classification of the Urdu sign language dataset was published in PeerJ Computer Science. He also co-authored papers on deep learning approaches to Pakistani Sign Language recognition and the simulation of transvascular transport of nanoparticles in tumor microenvironments, published in top journals like Scientific Reports and Engineering Applications of Artificial Intelligence.

FUTURE DIRECTIONS

Looking ahead, Ali aims to further his research in biomedical engineering, focusing on innovative solutions that bridge technology and healthcare. His future projects will continue to explore advanced applications of artificial intelligence and computational methods to improve patient care and medical outcomes.

NOTABLE PUBLICATION

Simulation of Transvascular Transport of Nanoparticles in Tumor Microenvironments for Drug Delivery Applications

Authors: Shabbir, F., Mujeeb, A.A., Jawed, S.F., Khan, A.H., Shakeel, C.S.
Year: 2024
Journal: Scientific Reports
Volume: 14

A Neural-Network Based Web Application on Real-Time Recognition of Pakistani Sign Language

Authors: Mujeeb, A.A., Khan, A.H., Khalid, S., Mirza, M.S., Khan, S.J.
Year: 2024
Journal: Engineering Applications of Artificial Intelligence

A Computer Vision-Based System for Recognition and Classification of Urdu Sign Language Dataset

Authors: Zahid, H., Rashid, M., Syed, S.A., Mujeeb, A.A., Khan, A.H.
Year: 2022
Journal: PeerJ Computer Science

Fangyu Wu – Artificial Intelligence – Best Researcher Award

Published on by Civil Engineering

Fangyu Wu - Artificial Intelligence - Best Researcher Award

AUTHOR PROFILE

SCOPUS

ACADEMIC AND PROFESSIONAL BACKGROUND

Fangyu Wu is a distinguished researcher and academic in the field of computer science, specializing in deep learning, multi-modal learning, and intelligent data analysis. He is currently an Associate Professor at Xi’an Jiaotong-Liverpool University (XJTLU) in China, where he supervises PhD and Master's students focusing on innovative research topics such as multi-modal learning and deep learning for computer vision. His previous role included co-supervising PhD students at Zhejiang University, contributing to advancements in facial recognition and image-text retrieval.

HONORS AND AWARDS

Dr. Wu's achievements have been recognized through several prestigious awards. He was named a Suzhou Youth Innovation Leading Talent in 2023 and won first prize at the 7th China Innovation Challenge for his project on intelligent tracking systems using infrared thermal imaging. Additionally, he received the Lotfi Zadeh Best Paper Award at ICMLC&ICWAPR 2017 and has been honored with the Outstanding Graduates award from Xi’an Jiaotong-Liverpool University and National Encouragement Scholarships from China.

RESEARCH PROJECTS

Fangyu Wu leads several high-impact research projects. These include “Intelligent Multimodal Data Analysis for Digital Twin Cities” under the Gusu Innovation and Entrepreneurship Leading Talents Programme, and “Relational Modeling and Reasoning for Reliable Cross-Modal Retrieval” funded by the Zhejiang Natural Science Foundation. His projects also cover advanced topics such as distributed AI platforms for Metaverse scenarios and optimization software for injection molding processes.

PUBLICATIONS

Dr. Wu has an extensive list of publications in top-tier conferences and journals. Notable works include papers on fine-grained image-text matching, relation-aware prototype networks, and pose-robust face recognition. His research has been featured at prestigious conferences such as CVPR, ECCV, and ICPR, showcasing his contributions to advancements in deep learning and computer vision.

CONFERENCE ORGANIZATION

In addition to his research, Fangyu Wu plays a vital role in organizing academic conferences. He served as the Publication Chair for the IEEE 17th International Conference on Computer Science & Education (ICCSE 2022) and as General Co-Chair for the 5th International Symposium on Emerging Technologies for Education (SETE 2020). His involvement ensures the smooth execution of these events and contributes to the dissemination of cutting-edge research.

STUDENT SUPERVISION

Fangyu Wu is actively engaged in supervising students at both the PhD and Master’s levels. He currently supervises a PhD student at XJTLU focusing on multi-modal learning and has previously co-supervised a PhD student at Zhejiang University on deep learning for computer vision. His mentorship extends to six Master’s students at XJTLU and three at Zhejiang University, covering areas such as facial recognition and image-text retrieval.

COMPETITIONS AND RECOGNITION

Dr. Wu has achieved notable success in various competitions. His project on human motion recognition based on deep neural networks won third prize at the China First Smart Manufacturing and Big Data Innovation Competition. Additionally, his participation in competitions has been marked by significant awards, including the first prize in the China Innovation Challenge for his intelligent tracking system.

NOTABLE PUBLICATION

  • Fine-grained Image-text Matching by Cross-modal Hard Aligning Network
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2023
    • Conference: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
    • Pages: 19275–19284
  • Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification
    • Authors: Li, J., Chen, Q., Wang, W., Wu, F.
    • Year: 2023
    • Conference: IEEE International Conference on Smart Computing (SMARTCOMP)
    • Pages: 222–224
  • Kernel Triplet Loss for Image-Text Retrieval
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2022
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2093
  • FaceCaps for Facial Expression Recognition
    • Authors: Wu, F., Pang, C., Zhang, B.
    • Year: 2021
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2021

Nibras Abdullah – Artificial neural network – Best Researcher Award

Published on by Civil Engineering

Nibras Abdullah - Artificial neural network forecasting model - Best Researcher Award

Universiti Sains Malaysia - Malaysia

AUTHOR PROFILE

Scopus
ORCID

EARLY ACADEMIC PURSUITS:

Dr. Nibras Abdullah Ahmed Faqera's academic journey began in Yemen, where he laid the foundation for his career. His dedication and passion for computer sciences led him to pursue higher education and contribute significantly to the field.

PROFESSIONAL ENDEAVORS:

Dr. Faqera's professional journey reflects a progression through various academic roles, demonstrating his commitment to education and research. Starting as a Full-time Lecturer at Hodeida University in Yemen, he gradually advanced through roles such as Research Assistant, Assistant Professor (Teaching Fellow), and currently holds the position of Assistant Professor (Senior Lecturer) at Universiti Sains Malaysia.

CONTRIBUTIONS AND RESEARCH FOCUS:

Throughout his career, Dr. Faqera has made substantial contributions to academia. His experiences include conducting research with high potential for international impact, managing postgraduate and undergraduate programs, and teaching a diverse range of courses. Notably, his expertise spans areas such as Big Data Storage and Management, Internet Communication Protocols, Internet Security, and more.

IMPACT AND INFLUENCE:

Dr. Faqera's impact is evident in his roles as a Visiting Scholar, where he conducted research with the potential for international impact. His influence extends to postgraduate seminars, coordination of student activities, and the publication of research articles. As a Senior Lecturer at Universiti Sains Malaysia, he continues to shape the academic landscape.

ACADEMIC CITES:

Having worked as a Research Assistant for several years, Dr. Faqera has acquired extensive research skills and has contributed to numerous high-quality research articles. His collaboration with professional and expert supervisors has enhanced his expertise and positioned him as a valuable contributor to the academic community.

LEGACY AND FUTURE CONTRIBUTIONS:

Dr. Nibras Abdullah Ahmed Faqera's legacy is marked by his dedication to education, research, and the development of postgraduate and undergraduate programs. As he continues to progress in his career, his future contributions are anticipated to further enrich the field of computer sciences. His commitment to staying at the forefront of technological advancements and imparting knowledge positions him as a leader and mentor for future generations of computer scientists.

NOTABLE PUBLICATION

IoT-Based Waste Management System in Formal and Informal Public Areas in Mecca.  2022 (5)

A Technical Review of SQL Injection Tools and Methods: A Case Study of SQL Map.  2022 (4)

Integrated Approach to Achieve a Sustainable Organic Waste Management System in Saudi Arabia.  2022 (7)

Improving Waste Management System Efficiency and Mobility with Efficient Path MANET.  2021 (4)

Metaheuristic Based IDS Using Multi-objective Wrapper Feature Selection and Neural Network Classification.   2021 (7)