Tarik El Moudden | AI | Best Researcher Award

Posted on by Best Paper Award

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 (DiplĂ´me d’Études SupĂ©rieures 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.

 

 

Pavan Kumar Joshi | Financial Technology | Industry Insightful Paper Award

Posted on by Best Paper Award

Mr. Pavan Kumar Joshi | Financial Technology | Industry Insightful Paper Award

Pavan Kumar Joshi at Fiserv Inc, United States

Summary:

Pavan Kumar Joshi is a seasoned technology executive with a deep passion for FinTech. With over 18 years of experience, he has played a pivotal role in building and scaling enterprise-level payment platforms at Fiserv. Based in the San Francisco Bay Area, Pavan continues to lead strategic initiatives that shape the future of payment solutions across multiple regions globally.

Professional Profile:

👩‍🎓Education:

Pavan Kumar Joshi completed his Master’s in Computer Applications from the University of Rajasthan in 2006, graduating with honors. Prior to his master’s, he earned a Bachelor of Science degree, majoring in Mathematics and Physics. During his academic years, he collaborated on numerous academic projects with his professors. Notably, he undertook an internship with the Rajasthan State Industrial Department and Investment Corporations Ltd (RIICO), where he contributed to developing a web application for tracking and submitting tax and revenue details by companies and factories to the state department.

🏢 Professional Experience:

Pavan is currently the Vice President of Engineering and an Expert Engineer at Fiserv, bringing over 18 years of experience in the technology sector. He has dedicated most of his professional career to FinTech, focusing on building enterprise-level payment platforms. At Fiserv, Pavan has been instrumental in developing an omnichannel payment platform for in-person payment acceptance, which has fully gone live and is now serving enterprise merchants with over $200 million in gross processing volume annually. He also leads the strategy and delivery of SoftPOS solutions on iPhone and Android devices across regions such as the US, Asia Pacific (Australia and Singapore), and LATAM (Brazil).

Prior to this, Pavan led the launch of a credit card customer portal utilized by over 100 financial institutions and more than 2 million credit cardholders in the USA. As a Director of Engineering, he spearheaded a team that reimagined the merchant onboarding system for small and medium businesses in the US market. This initiative, which was the company’s first cloud-native application deployed on AWS, enabled significant cost savings by sunsetting multiple legacy systems.

Before joining Fiserv, Pavan worked at Accenture, where he contributed to JP Morgan Chase’s Capital Markets division by helping to create a modern platform using Java, Spring, and reactive frontend technologies.

Author Metrics:

  • Years of Experience: 18+
  • Current Role: Vice President of Engineering & Expert Engineer at Fiserv
  • Key Projects: Omnichannel Payment Platform, SoftPOS Solutions, Credit Card Customer Portal, Merchant Onboarding System
  • Technological Expertise: FinTech, Cloud-native applications, Java, Spring, Payment Processing Systems
  • Global Impact: Projects in the USA, Asia Pacific, and LATAM regions.

Research Interests:

Pavan’s research interests lie in the FinTech space, with a focus on payment processing systems, cloud-native applications, and the integration of emerging technologies to enhance financial services. He is particularly interested in exploring new technologies that can drive innovation in the financial sector, improving both user experience and operational efficiency.

Top Noted Publication:

Title: Implementation of AES DUKPT in Software Point of Sale: Enhancing Security in Digital Payment Systems
Author: Pavan Kumar Joshi
Journal: International Journal of Science and Research (IJSR)
Volume/Issue: 13(8)
Pages: 46-48
Year: 2024
Summary: This paper discusses the integration of the Advanced Encryption Standard (AES) Derived Unique Key Per Transaction (DUKPT) in software-based Point of Sale (SoftPOS) systems. The study highlights the significance of AES DUKPT in enhancing the security of digital payment systems, emphasizing its role in safeguarding transaction data from cyber threats. The implementation of this encryption method ensures that each transaction uses a unique key, adding a critical layer of security and data integrity in payment processing environments.

Title: Encryption of Host-to-Host Payment Transactions Using Master Session Key Implementation for Multi-Merchant Acquirer Integration via a Single Payment Gateway Platform
Author: Pavan Kumar Joshi
Journal: Journal of Artificial Intelligence & Cloud Computing
Volume/Issue: 1(3)
Pages: 1-3
Year: 2022
Summary: This paper explores the encryption techniques employed for host-to-host payment transactions, particularly focusing on the implementation of a master session key. The study provides insights into how this encryption method facilitates the integration of multiple merchant acquirers through a single payment gateway platform. It addresses the challenges of secure communication between hosts and underscores the importance of encryption in protecting sensitive transaction data in a complex, multi-merchant environment.