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.

 

 

Balaji Srinivasan | Machine Learning Method | Best Researcher Award

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Mr. Balaji Srinivasan | Machine Learning Method | Best Researcher Award

Balaji Srinivasan at Engineers India Limited, India

Summary:

Balaji Srinivasan is a seasoned analyst with over 16 years of experience in the refinery and petrochemical industries. Specializing in asset lifecycle management and local stress analysis, he has played a pivotal role in ensuring the safety and reliability of complex systems. His expertise in finite element analysis and advanced technology development has earned him recognition in the field.

Professional Profile:

👩‍🎓Education:

Balaji Srinivasan holds a solid educational foundation in engineering, specializing in fields pertinent to the refinery and petrochemical industries. His education laid the groundwork for a successful career in managing complex projects and conducting advanced technology development activities.

🏢 Professional Experience:

With over 16 years of experience, Balaji Srinivasan has made significant contributions to the refinery and petrochemical sectors. He has been with Engineers India Limited in New Delhi since September 2007, where he specializes in local stress analysis. His expertise extends to conducting advanced technology development activities, including transient thermal and creep-fatigue interaction studies.

Balaji has executed finite element, fatigue, creep, and creep-fatigue analyses for pressure vessels and piping components, including high-pressure and high-temperature reactors, coke drums, dryers, and agitator vessels. He has led complex equipment troubleshooting exercises, ensuring safe and reliable plant operations through numerical simulations to identify root causes of fault sequences and performing fitness-for-service assessments on critical components.

Balaji’s knowledge of FEA software like ABAQUS and ANSYS has been instrumental in solving unconventional, complex, and multidisciplinary problems arising from pre- and post-commissioning activities. His interactive management approach has enhanced output, maximized quality, and increased employee satisfaction.

Research Interests:

Balaji’s research interests lie in asset lifecycle management, design basis assessment, local stress analysis, and advanced technology development for the refinery and petrochemical industries. He is particularly focused on enhancing the reliability and safety of critical infrastructure through innovative analysis and simulation techniques.

Author Metric:

Balaji Srinivasan has contributed to several industry-related publications and research projects. His work is well-regarded in the field of stress analysis and lifecycle management, with a focus on enhancing system reliability and safety. His publications have garnered citations, reflecting the impact of his research on the industry.

Top Noted Publication:

1. Strain engineering and one-dimensional organization of metal–insulator domains in single-crystal vanadium dioxide beams

  • Authors: J. Cao, E. Ertekin, V. Srinivasan, W. Fan, S. Huang, H. Zheng, J.W.L. Yim, et al.
  • Journal: Nature Nanotechnology
  • Volume: 4
  • Issue: 11
  • Pages: 732-737
  • Year: 2009
  • DOI: 10.1038/nnano.2009.266
  • Citations: 676

2. Mechanism of thermal reversal of the (fulvalene) tetracarbonyldiruthenium photoisomerization: toward molecular solar–thermal energy storage

  • Authors: Y. Kanai, V. Srinivasan, S.K. Meier, K.P.C. Vollhardt, J.C. Grossman
  • Journal: Angewandte Chemie International Edition
  • Volume: 49
  • Issue: 47
  • Pages: 8926-8929
  • Year: 2010
  • DOI: 10.1002/anie.201003643
  • Citations: 136

3. Proton momentum distribution in water: an open path integral molecular dynamics study

  • Authors: J.A. Morrone, V. Srinivasan, D. Sebastiani, R. Car
  • Journal: The Journal of Chemical Physics
  • Volume: 126
  • Issue: 23
  • Pages: 234504
  • Year: 2007
  • DOI: 10.1063/1.2746330
  • Citations: 90

4. Interplay between intrinsic defects, doping, and free carrier concentration in SrTiO₃ thin films

  • Authors: E. Ertekin, V. Srinivasan, J. Ravichandran, P.B. Rossen, W. Siemons, et al.
  • Journal: Physical Review B—Condensed Matter and Materials Physics
  • Volume: 85
  • Issue: 19
  • Article: 195460
  • Year: 2012
  • DOI: 10.1103/PhysRevB.85.195460
  • Citations: 56

5. Exploring the potential of fulvalene dimetals as platforms for molecular solar thermal energy storage: computations, syntheses, structures, kinetics, and catalysis

  • Authors: K. Börjesson, D. Ćoso, V. Gray, J.C. Grossman, J. Guan, C.B. Harris, et al.
  • Journal: Chemistry–A European Journal
  • Volume: 20
  • Issue: 47
  • Pages: 15587-15604
  • Year: 2014
  • DOI: 10.1002/chem.201402857
  • Citations: 44

Anurag Upadhyay | Machine Learning Award | Best Researcher Award

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Mr. Anurag Upadhyay, Machine Learning Award, Best Researcher Award

Anurag Upadhyay at DGI GREATER NOIDA, India

Summary:

Mr. Anurag Upadhyay is a dedicated academician and experienced educator with over 15 years of teaching experience in the field of computer science and technology. He holds a Master’s degree (M.Tech) in Computer Science from IFTM University, Moradabad, and a Bachelor’s degree (B.Tech) in Computer Science from MIT Moradabad (UPTU).

Throughout his career, Mr. Upadhyay has served in various teaching positions at esteemed institutions such as IFTM University Moradabad, KITPS Moradabad, and RIMT Bareilly, among others. Currently, he is an Assistant Professor at Dronacharya Group of Institutions, Greater Noida, where he continues to impart his knowledge and expertise to aspiring students.

Professional Profile:

Google Scholar Profile

👩‍🎓Education & Qualification:

Professional Experience:  

Mr. Anurag Upadhyay has over 15 years of experience in the field of teaching. He has held various positions in different educational institutions, including lecturer positions at Govt Girls Polytechnic Bareilly, FIET Bareilly, and CET IFTM Moradabad. He served as an Assistant Professor at IFTM University Moradabad, KITPS Moradabad, RIMT Bareilly, IIMT Greater Noida, and Dronacharya Group of Institutions Greater Noida. Throughout his career, Mr. Upadhyay has taught a wide range of subjects, including Machine Learning, Cloud Computing, Operating System, Information Technology, Computer Organization, Distributed System, Data Mining & Data Warehousing, Computer Concepts & Programming in ‘C,’ Soft Computing, Design of Algorithm, Software Engineering, and Compiler. He is an active member of professional organizations such as CSTA, ACM, and IAENG. Additionally, Mr. Upadhyay has undergone training and short-term courses in various areas related to computer science and technology.

Research Interest:

Machine Learning: Exploring algorithms and techniques to enable computers to learn from and make predictions or decisions based on data.

Cloud Computing: Investigating cloud-based services, architectures, and technologies for efficient data storage, processing, and management.

Operating Systems: Studying the design, implementation, and optimization of operating systems to enhance system performance and resource utilization.

Information Technology: Researching advancements in IT infrastructure, applications, and management practices to support organizational objectives and improve efficiency.

Data Mining & Data Warehousing: Analyzing large datasets to discover patterns, trends, and insights that can drive informed decision-making in various domains.

Computer Organization: Investigating the architecture and design of computer systems, including hardware components and their interactions, to optimize performance and functionality.

Software Engineering: Exploring methodologies, tools, and best practices for the systematic development, maintenance, and evolution of software systems.

Compiler Design: Studying the theory and implementation of compilers, which translate high-level programming languages into machine-readable code for execution on hardware platforms.

Publication Top Noted:

Title: Empirical Comparison by data mining Classification algorithms (C 4.5 & C 5.0) for thyroid cancer data set

  • Authors: A. Upadhayay, S. Shukla, S. Kumar
  • Journal: International Journal of Computer Science & Communication Networks
  • Volume: 3
  • Issue: 1
  • Page: 64
  • Year: 2013
  • Citation Count: 36

Title: A fresh loom for multilevel feedback queue scheduling algorithm

  • Authors: R.K. Yadav, A. Upadhayay
  • Journal: International Journal of Advances in Engineering Sciences
  • Volume: 2
  • Issue: 3
  • Pages: 21-23
  • Year: 2012
  • Citation Count: 19

Title: Animal husbandry practices in Pithoragarh district of Uttarakhand state

  • Authors: S. Shukla, D.P. Tiwari, A. Kumar, B.C. Mondal, A.K. Upadhayay
  • Journal: Indian Journal of Animal Sciences
  • Volume: 77
  • Issue: 11
  • Page: 1201
  • Year: 2007
  • Citation Count: 12

Title: Evaluation of fish curry from farmed and wild caught Indian major carps of Tarai Region, Uttarakhand

  • Authors: M. Gupta, A.K. Upadhayay, N.N. Pandey, P. Kumar
  • Publisher: Society of Fisheries Technologists (India) Cochin
  • Year: 2013
  • Citation Count: 2

Title: Cryptography and Network Security

  • Author: Anurag Upadhyay
  • Publisher: Lambert Publishing House
  • Volume: 1
  • ISBN: 978-620-2-02336-8
  • Year: 2017

 

 

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%)