Tarik El Moudden | AI | Best Researcher Award

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Mr. Tarik El Moudden | AI | Best Researcher Award

Tarik El Moudden at Ibn Tofail University, Kenitra, Morocco, Morocco

Summary:

Dr. Tarik El Moudden is a Moroccan-based data scientist and AI specialist, currently serving as a Senior Web Application Developer and Data Analyst at Zenithsoft and a lecturer at Ibn Tofail University. He has extensive experience in neural network frameworks, computer vision, and predictive analytics, leveraging tools such as Python, TensorFlow, and Keras. In addition to his research, he is dedicated to mentoring the next generation of AI professionals and data scientists. He combines a strong academic background with hands-on industry experience, working on complex problems in machine learning, AI integration, and big data analytics.

Professional Profile:

👩‍🎓Education:

Dr. Tarik El Moudden earned his Doctorate in Predictive Modeling using AI and Big Data Analysis from the Computer Science Research Laboratory at Ibn Tofail University, Kenitra, Morocco, in 2024. He holds a DESA (Diplôme d’Études Supérieures Approfondies) in Advanced Study in Telecommunication and Informatics from the same university, completed in 2008. Dr. El Moudden has also pursued a number of professional certifications, including specialized skills in Power BI, Artificial Intelligence (AI), Python, Data Science, Machine Learning, Deep Learning, and Big Data, powered by IBM Developer Skills Network (2024). He holds certifications from NASA’s Applied Remote Sensing Training (ARSET) program, covering large-scale machine learning applications for agriculture solutions and spectral indices for land and aquatic applications. Additionally, he is certified as a Professional Drone Pilot and in Project Management with AI.

🏢 Professional Experience:

Dr. El Moudden has been a Senior Web Application Developer and Senior Data Analyst and AI Models Integration Specialist at Zenithsoft, Rabat, Morocco, from 2020 to 2024. During his tenure, he developed expertise in neural networks, deep learning, and machine learning models for predictive analytics and data-driven solutions. At Ibn Tofail University, he has taught various modules across different levels, such as Power BI, Data Science, Applied Mathematics, Python Programming, and Machine Learning. He has been involved in teaching these subjects at the Master’s and Professional License levels in fields like Big Data, Artificial Intelligence (AI), Engineering, and Applied Mathematics from 2019 to 2024. His teaching portfolio extends to subjects like Numerical Methods with Python for Master’s students in Partial Differential Equations and Complex Geometry, as well as Applied Mathematics and Optimization for Engineering students.

Research Interests:

Dr. El Moudden’s research primarily focuses on AI integration in predictive modeling, machine learning applications for large-scale agriculture solutions, computer vision, neural networks (CNNs, RNNs, GANs), and data analysis. His work spans image classification, object detection, and image segmentation using Python, TensorFlow, Keras, and PyTorch. He is also passionate about exploring AI’s potential in various industry-specific applications, particularly Big Data, deep learning models, and cloud-based solutions through platforms like Microsoft Azure.

Author Metrics:

  • ORCID: 0000-0002-6963-6686
  • Published Articles: Dr. El Moudden has contributed to scientific publications and is a regular reviewer in the fields of AI, predictive analytics, and machine learning. His research focuses on enhancing AI’s impact on real-world applications, particularly in agriculture and big data. He continues to publish research papers in both local and international conferences.

Top Noted Publication:

Artificial intelligence for assessing the planets’ positions as a precursor to earthquake events

  • Authors: T.E. Moudden, M. Amnai, A. Choukri, Y. Fakhri, G. Noreddine
  • Journal: Journal of Geodynamics, 2024, Volume 162, Article 102057
  • This article explores the use of artificial intelligence to analyze planetary positions in relation to earthquake occurrences, contributing valuable insights into the role of celestial mechanics in earthquake prediction.

New unfreezing strategy of transfer learning in satellite imagery for mapping the diversity of slum areas: A case study in Kenitra city—Morocco

  • Authors: T.E. Moudden, M. Amnai, A. Choukri, Y. Fakhri, G. Noreddine
  • Journal: Scientific African, 2024, Volume 24, Article e02135
  • This open access research focuses on a novel transfer learning approach to analyze satellite imagery for detecting slum areas in Kenitra, Morocco. It highlights advancements in AI and satellite technology for urban mapping.

Building an efficient convolution neural network from scratch: A case study on detecting and localizing slums

  • Authors: T.E. Moudden, M. Amnai
  • Journal: Scientific African, 2023, Volume 20, Article e01612
  • This article presents a case study on developing an effective convolutional neural network (CNN) from scratch, specifically designed for slum detection and localization.

Slum image detection and localization using transfer learning: a case study in Northern Morocco

  • Authors: T. El Moudden, R. Dahmani, M. Amnai, A.A. Fora
  • Journal: International Journal of Electrical and Computer Engineering, 2023, Volume 13(3), Pages 3299–3310
  • This article applies transfer learning techniques to detect and localize slums using satellite imagery, focusing on Northern Morocco as a case study.

Nutrient removal performance within the biological treatment of the Marrakech wastewater treatment plant and characterization of the aeration and non-aeration process

  • Authors: M. Tahri, T. El Moudden, B. Bachiri, M. El Amrani, A. Elmidaoui
  • Journal: Desalination and Water Treatment, 2022, Volume 257, Pages 117–130
  • This article investigates the efficiency of nutrient removal during the biological treatment processes at the Marrakech wastewater treatment plant, providing key insights into water treatment technologies.

Conclusion:

Dr. Tarik El Moudden is a deserving candidate for the Best Researcher Award due to his significant contributions to the field of AI, data science, and machine learning, with a strong focus on practical applications in agriculture, urban development, and disaster prediction. His academic achievements, coupled with his industry expertise, reflect a researcher who is poised to make transformative impacts in the AI landscape. With a bit more focus on expanding his international collaborations and enhancing the visibility of his work, Dr. El Moudden’s research can become even more influential in shaping AI’s future in solving complex, real-world problems.

 

 

Maksym Lupei | Predictive Analytics | Best Paper Award

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Dr. Maksym Lupei | Predictive Analytics | Best Paper Award

Doctorate at The Pennsylvania State University, United States

Summary:

Dr. Maksym Lupei is a dedicated researcher and academic with extensive expertise in machine learning and computational genomics. Holding a Ph.D. in Information Technologies and Machine Learning from Uzhhorod National University, he has contributed significantly to the fields of text mining and artificial intelligence. Currently a Postdoctoral Researcher at The Pennsylvania State University, Dr. Lupei is recognized for his innovative work in developing large language models and optimizing computational frameworks for biomedical data analysis. His career reflects a blend of academic excellence and practical industry experience, underpinned by a strong commitment to advancing technology and data science.

Professional Profile:

👩‍🎓Education:

Ph.D. in Information Technologies and Machine Learning (2021)

  • Institution: Uzhhorod National University
  • Dissertation: Determining the Eligibility of Candidates for a Vacancy Using Artificial Neural Networks

MSc in Applied Mathematics (2013)

  • Institution: Uzhhorod National University
  • Thesis: .NET Websites Optimization

BSc in Applied Mathematics (2012)

  • Institution: Uzhhorod National University
  • Thesis: Modern Methods of Prediction

🏢 Professional Experience:

Dr. Maksym Lupei is currently a Postdoctoral Researcher in Computer Science & Engineering at The Pennsylvania State University (since August 2023), where he leads projects involving large language models for biomedical data fact-checking, computational genomics, and metagenomics. His work includes developing open-source text mining services and optimizing GPU infrastructure. Previously, he served as a Senior Research Fellow at the V. M. Glushkov Institute of Cybernetics of the National Academy of Science of Ukraine, specializing in machine learning and text mining (January 2022 – August 2023). At Uzhhorod National University, Dr. Lupei was an Assistant Professor in the Department of Informative and Operating Systems (December 2019 – January 2023), teaching programming languages and machine learning courses.

Dr. Lupei’s industry experience includes roles as an Engineering Manager at TIBCO Jaspersoft (March 2014 – February 2021), where he led cross-functional teams and established Agile/Scrum processes, and as a Full Stack Developer at JustAnswer (March 2011 – February 2014) and Swan Software Solutions (August 2010 – March 2011).

Research Interests

Dr. Lupei’s research interests encompass machine learning, large language models, computational genomics, metagenomics, and explainable artificial intelligence. His work focuses on processing large information arrays using mathematical methods, particularly in text mining.

Top Noted Publication:

 

 

Bolaji Oladipo | Mechanical Engineering

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Mr. Bolaji Oladipo: Leading Researcher in Mechanical Engineering

Summary:

Bolaji Oladipo is a dedicated and accomplished mechanical engineer currently pursuing a Ph.D. in Mechanical Engineering at the University of Rhode Island, USA, where he maintains an impressive GPA of 3.74/4.00. His academic journey includes a Master of Science in Mechanical Engineering from Rowan University, New Jersey, USA, and a Bachelor of Science in Mechanical Engineering from the University of Ibadan, Nigeria.

Bolaji has made significant contributions to the field of mechanical engineering, particularly in areas such as auxetic metamaterials, corrosion assessment, and material interface adhesion. His expertise extends to machine learning, finite element analysis, and materials modeling, as evidenced by his presentations at various conferences and workshops. He has showcased research findings through poster presentations on topics like auxetic TPU metamaterials and efficient strengthening of concrete cylinders.

Professional Profile:

🎓 Education:

  • Pursuing a Ph.D. in Mechanical Engineering at the University of Rhode Island, USA (2022 – Present) with a GPA of 3.74/4.00.
  • Master of Science in Mechanical Engineering from Rowan University, New Jersey, USA (2018 – 2020) with a GPA of 3.76/4.00.
  • Bachelor of Science in Mechanical Engineering from the University of Ibadan, Nigeria (2008 – 2014) with a GPA of 3.30/4.00.

📊 Conference Presentations: He have consistently demonstrated my expertise in machine learning, finite element analysis, and materials modeling through engaging presentations at diverse conferences and workshops. These platforms have provided me with opportunities to share and discuss cutting-edge research findings, contributing to the broader academic and professional discourse.

📝 Poster Presentations: He have effectively communicated my research insights through visually compelling posters, covering subjects like auxetic TPU metamaterials and the efficient strengthening of concrete cylinders. These presentations, showcased at various conferences and forums, have facilitated discussions and knowledge exchange within the academic and professional communities.

🔍 Journal Review: He contribute to the academic community by serving as a meticulous reviewer for the Journal of Materials in Civil Engineering, a prestigious publication under the American Society of Civil Engineers. This role involves evaluating and providing valuable insights into scientific research articles.

🏆 Awards and Honors: He take pride in receiving accolades for my research contributions, securing 1st place in the Sixth Rhode Island Transportation and Engineering Poster Competition. Additionally, He achieved 2nd place in the 2022 TIDC Student Poster Fan Favorite Contest, showcasing the recognition of my work within the academic realm.

🌐 Professional Memberships: As a dedicated professional, He hold esteemed memberships in reputable organizations such as the American Society of Civil Engineers and the Nigerian Society of Engineers. These affiliations reflect my commitment to staying connected with the broader engineering community and staying abreast of the latest advancements in the field.

👨‍💼 Work Experience: In the capacity of Founder and CEO of Custod Engineering Services Limited, He lead a dynamic team, providing comprehensive training in CAD/CAM software and delivering top-notch engineering consultancy services.

💼 Research Associate: Currently serving as a Graduate Research Associate at the Multiscale And Multiphysics Mechanics Laboratory, University of Rhode Island, He engage in diverse numerical simulations and experiments related to concrete cylinders. My responsibilities also include interpreting data and contributing to research articles.

👨‍🏫 Teaching Experience: With a background as a Graduate Teaching Assistant and Graduate Teaching Fellow, He actively contribute to the education sector. My roles have involved teaching labs and lectures, grading assignments, and fostering an enriching learning environment.

🌐 Global Experience: He have showcased my research findings on a global platform by presenting virtually at international conferences. This experience reflects my commitment to a broader perspective in academia and research.

🏆 Judging Experience: He was honored to be invited as a judge at the 2023 Virginia Junior Academy of Science (VJAS) Research Symposium, where He assessed and scored research papers, particularly in the engineering category.

Publication Top Noted:

Title: Corrosion assessment of some buried metal pipes using neural network algorithm

  • Authors: B.A. Oladipo, O.O. Ajide, C.G. Monyei
  • Journal: International Journal of Engineering and Manufacturing (IJEM)
  • Volume: 7
  • Issue: 6
  • Pages: 27-42
  • Year: 2017

Title: Integrating Experiments, Finite Element Analysis, and Interpretable Machine Learning to Evaluate the Auxetic Response of 3D Printed Re-entrant Metamaterials

  • Authors: B. Oladipo, H. Matos, N.M.A. Krishnan, S. Das
  • Journal: Journal of Materials Research and Technology
  • Volume: 2
  • Year: 2023

Title: Evaluating the adhesion response of acrylonitrile-butadiene-styrene (ABS)/thermoplastic polyurethane (TPU) fused interface using multiscale simulation and experiments

  • Authors: J.T. Villada, G.A. Lyngdoh, R. Paswan, B. Oladipo, S. Das
  • Journal: Materials & Design
  • Volume: 232
  • Pages: 112155
  • Year: 2023

Research Focus:

Auxetic Metamaterials: Bolaji has delved into the study of auxetic materials, exploring their unique mechanical properties and potential applications. These materials exhibit negative Poisson’s ratios, making them valuable for specific engineering applications due to their ability to expand laterally when stretched.

Corrosion Assessment: Bolaji has conducted research on the corrosion assessment of buried metal pipes, employing neural network algorithms to analyze and predict corrosion behavior. This work contributes to the understanding of corrosion processes and aids in the development of effective mitigation strategies.

Material Interface Adhesion: His research extends to evaluating the adhesion response of material interfaces, specifically focusing on acrylonitrile-butadiene-styrene (ABS)/thermoplastic polyurethane (TPU) fused interfaces. This work involves multiscale simulation and experiments to enhance our understanding of material interactions.

Finite Element Analysis (FEA): Bolaji has expertise in finite element analysis, utilizing tools like ANSYS Multiphysics to simulate and analyze complex mechanical systems. His work involves applying FEA techniques to study the mechanical behavior of structures, such as concrete cylinders.

Machine Learning Applications: With a keen interest in machine learning, Bolaji integrates this technology into materials science and engineering. His research involves the use of interpretable machine learning to evaluate the auxetic response of 3D printed re-entrant metamaterials, showcasing an interdisciplinary approach.

Global Infrastructure and Transportation: Bolaji’s research extends to the domain of transportation infrastructure durability. He has presented findings at conferences on topics related to the efficient strengthening of concrete cylinders, contributing to the development of resilient and sustainable infrastructure.

 

 

Zakria Qadir | Computer Engineering

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Dr. Zakria Qadir: Leading Researcher in Computer Engineering

🎉 Congratulations Dr. Zakria Qadir on Winning the Most Reader’s Article Award! 🏆 Your dedication to research, mentorship, and collaboration with international teams is truly commendable. This award is a testament to your outstanding work and the impact it has on the broader community.

Professional Profile:

🔬 Research Focus: Enthusiastic PostDoc Research Associate at UNSW Artificial Intelligence Institute, dedicated to pushing boundaries in DIGITECH. Research spans Artificial Intelligence, Machine Learning, Wireless Communication, IoT, and Cybersecurity. Highly cited Young STEM Researcher.

🎓 Education:

  • Ph.D. in Electrical and Computer Engineering (Western Sydney University).
    • Research: Smart UAVs for disaster relief, AI, ML, IoT applications.
  • Master’s in Sustainable Environment and Energy System (METU).
    • Thesis: Neural Network-Based Prediction Algorithms for Hybrid PV-Wind System.
  • Bachelor of Science in Electronic Engineering (UET Taxila).
    • Gold Medal Award for securing First Position.

🏆 Achievements:

  • Google Scholar: Citations 1000+, H-Index 17, Total Papers 40, Cumulative Impact Factor >100+.
  • Keynote Speaker at Core A conferences.
  • Fully Funded ARC Research Discovery Scholarship for Ph.D.
  • Various scholarships and awards for academic excellence.

👨‍💻 Professional Experience:

  • Post-Doc Research Associate at UNSW, collaborating with the Department of Defence Australia.
  • Research: Drones-aided AI Algorithms for Battlefield Scenarios.
  • Research Assistant at UNSW, collaborating with Cisco, focusing on Intelligent Transportation Systems.
  • Sessional Lecturer at Victoria University, teaching Data Science, AI, Computer Science, Business Analysis, Networking.
  • Casual Lecturer at Western Sydney University (WSU) and Melbourne Institute of Technology (MIT).
  • Lecturer at National University of Technology, teaching IoT, AI, and Machine Learning.
  • Senior Research Scientist at Imam Abdulrahman Bin Faisal University.
  • Graduate Teaching Assistant at Middle East Technical University (METU).
  • Lab Engineer at National University of Science and Technology (NUST).

Publication Top Noted:

  • Towards 6G Internet of Things: Recent advances, use cases, and open challenges
  • A Hybrid Deep Learning Approach for Bottleneck Detection in IoT
  • A strong construction of S-box using Mandelbrot set an image encryption scheme
  • Resource optimization in UAV-assisted wireless networks—A comprehensive survey
  • Autonomous UAV Path-Planning Optimization Using Metaheuristic Approach for Predisaster Assessment

📚 Skills:

  • Programming Languages: MATLAB, Python, C++.
  • Metaheuristic Algorithms: PSO, ACO, DGBCO, GWO.
  • Machine Learning (AI): Deep learning, Feature Extraction, CNN, FRNN, YOLO.
  • Understanding of Arduino, Raspberry Pi, Proteus, Lucid Chart, VOSViewer, LaTeX.

🎓 Teaching Experience:

  • Lectured and supervised students at various universities.
  • Lesson planning, preparation, and research in diverse areas.

🏅 Honors and Awards:

  • Graduate Teaching Assistant Scholarship at METU.
  • Gold Medal Award for securing First Position in Bachelors.
  • Best Engineering Project Award at UET Taxila.

🏆 Funding and Recognition:

  • Awarded ARC Research Discovery Scholarship, Research Candidate Support Funding, Teaching Assistant Scholarships, Travel Grants, and Research Grants.
  • Recognition from Core A conferences and Australia’s Natural Hazard Research.

 

The paper “A Prototype of an Energy-Efficient MAGLEV Train: A Step Towards Cleaner Train Transport” focuses on the development and evaluation of a prototype Magnetic Levitation (MAGLEV) train with an emphasis on energy efficiency. Below are some key points and important content from the paper:

Abstract:

  • Focus: Development and assessment of an energy-efficient MAGLEV train prototype.
  • Goal: Contributing to cleaner and more sustainable train transportation.

Introduction:

  • Motivation: Addressing the need for environmentally friendly and energy-efficient transportation solutions.
  • Importance of MAGLEV: Highlighting the advantages of MAGLEV technology, such as reduced friction and energy consumption.

Key Features of the MAGLEV Prototype:

  • Energy Efficiency Measures: Description of features and technologies incorporated to enhance energy efficiency.
  • Magnetic Levitation System: Explanation of the MAGLEV technology used in the prototype.
  • Propulsion System: Details about the propulsion mechanism and its role in energy savings.

Performance Evaluation:

  • Energy Consumption Analysis: Quantitative assessment of energy consumption compared to traditional train systems.
  • Environmental Impact: Discussion on the potential reduction in carbon footprint and environmental benefits.

Results and Findings:

  • Energy Savings Percentage: Presentation of the achieved energy savings compared to conventional trains.
  • Operational Stability: Evaluation of the MAGLEV prototype’s stability during operations.

Conclusion:

  • Significance: Emphasizes the significance of developing energy-efficient transportation solutions.
  • Future Implications: Discusses the potential widespread adoption of MAGLEV technology for cleaner and sustainable train transport.

Impact and Citations:

  • Citation Count: Indicates the paper’s impact and recognition within the research community.
  • Reader’s Count: Reflects the broader readership and interest in the paper’s findings.

Innovation and Contribution:

  • Novelty: Highlights any novel approaches, technologies, or methodologies introduced in the MAGLEV prototype.
  • Contribution to the Field: Describes how the research contributes to advancements in cleaner and energy-efficient transportation.

This summary provides a glimpse into the essential content of the paper, focusing on its goals, methodology, findings, and impact on the field of transportation and energy efficiency.

 

 

 

 

 

Nasser Metwally | Applied mathematics

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Prof Dr. Nasser Metwally: Leading Researcher in Applied mathematics

🎉 Congratulations Prof Dr. Nasser Metwally on Winning the Most Cited Article Award! 🏆 Your dedication to research, mentorship, and collaboration with international teams is truly commendable. This award is a testament to your outstanding work and the impact it has on the broader community.

Professional Profile:

📚 Education:

  • Ph.D. in Mathematics, “Entangled Qubit Pairs,” Muenchen University, Germany (2002).
  • M.Sc., “Mathematics,” “Atomic Hydrogen in Electromagnetic Field,” Faculty of Science, Assuit University, Egypt (1994).
  • B.Sc., Science, “Mathematics,” Aswan Faculty of Science, Assuit University, Egypt (1987).

🏢 Current Positions:

  • Professor, Math. Dept., Faculty of Science, Aswan, Egypt (2015-present).
  • Associate Professor, Department of Mathematics, College of Science, University of Bahrain (Since March 2021).

🔍 Previous Positions:

  • Demonstrator, Faculty of Science, Math. Dept., Aswan University (1987).
  • Assistant Lecturer, Faculty of Science, Aswan (1994).
  • Lecturer (Assistant Professor) at Math. Dept., Faculty of Science, Aswan (2002).
  • Associate Professor, Math. Dept., Faculty of Science, Aswan, Egypt (Nov. 2010).

📜 Accolades:

  • Mohamed Amin Lotfy Award in Mathematics (2011).
  • Among the top 2% scientists in the Stanford University’s List (2020 & 2021).
  • Best Research Award (2022).
  • Obada Prize in Mathematics (2023).

🌐 Activities:

  • Editor, Journal of Applied Mathematics & Sciences.
  • Consultant Member, Master program of quantum information, Faculty of Science, Rabat, Morocco (2010).
  • Researcher, Center for Artificial Intelligence and Robotics (CAIRO) (2009).

📖 Research Field: Quantum optics, including Teleportation, Purification, Entanglement, Cryptography, and Quantum Computing.

📚 Publications Top Noted:

  1. “The efficiency of fractional channels in the Heisenberg,” Chaos, Solitons and Fractals, Volume 172, 113581.
  2. “Multiparameter estimation for a two-qubit system coupled to independent reservoirs using quantum Fisher information,” Quantum Studies: Mathematics and Foundations (Accepted).
  3. “Dynamics of Quantum effects in a three-level system interacting with two-mode time-dependent fields including parametric down-conversion and damping,” Journal of Modern Optics.
  4. “Efficiency increasing of the bidirectional teleportation protocol via weak and reversal measurements,” Phys. Scr. 97 025102.
  5. “Local two-atom correlations induced by a two-mode cavity under nonlinear media: Quantum uncertainty and quantum Fisher information,” Results in Physics, Volume 31, 104975.

📚 Books Contribution:

  1. “Kinematics of qubit pairs,” in “Mathematics of quantum computation” by R. Brylinski, G. Chen.
  2. “Teleportation using a finite pairs of generalized Werner states” in “Aspects of optical since and quantum information” by M. Abdel-Aty.

🏆 Honors and Awards:

  • Award of Mohamed Amin Lotfy in Mathematics (2011).
  • Among the top 2% scientists in the Stanford University’s List (2020 & 2021).
  • Best Research Award (2022).
  • The Award of Obada Prize in Mathematics (2023).

 

 

 

Yogesh | Artificial Intelligence

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Dr. Yogesh: Leading Researcher in Artificial Intelligence

Congratulations to Dr. Yogesh on Winning the Best Researcher Award! Dr. Yogesh is a dedicated researcher known for his impactful contributions to the field of Artificial Intelligence. His commitment to research, mentorship, and collaboration with international teams has earned him this prestigious recognition.

Dr. Yogesh is a distinguished researcher in the field of Artificial Intelligence, recognized for his outstanding contributions and achievements. Currently serving as Assistant Professor-III in the Department of Computer Science and Engineering at Chitkara University, Punjab, he brings a wealth of experience and expertise to his role.

Professional Profile:

🎓 Educational Qualifications:

  • Ph.D.: Amity University Uttar Pradesh, Noida, 2021
  • M. Tech: Amity University Uttar Pradesh, Noida, 2013 (84.7%)
  • B. Tech: Magadh University, Patna, 2007 (76%)