Taicir Mezghani | Econometrics and Finance | Best Researcher Award

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Assist Prof Dr. Taicir Mezghani | Econometrics and Finance | Best Researcher Award

Assistant Professor at University of Sfax , Tunisia
Summary:

Assist. Prof. Dr. Taicir Mezghani is a distinguished researcher and educator with a profound background in computer science, specializing in data mining, machine learning, and cybersecurity. He completed his Ph.D. at the University of Toulouse, France, and has since been dedicated to advancing the fields of AI and data science through teaching and research. His work emphasizes the development of secure, efficient, and ethical data systems, making significant contributions to both academic and practical applications of computer science.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Computer Science – University of Toulouse, France
  • Master’s in Computer Science – University of Manouba, Tunisia
  • Bachelor’s in Computer Science – University of Manouba, Tunisia

🏢 Professional Experience:

Assist. Prof. Dr. Taicir Mezghani is an esteemed academic and researcher specializing in Computer Science, currently serving as an Assistant Professor. His expertise extends to data mining, machine learning, artificial intelligence, and cybersecurity. Over the years, Dr. Mezghani has held various academic positions, contributing significantly to research and teaching in the field. He has been actively involved in collaborative research projects at the national and international levels, focusing on applying AI to solve complex problems in different domains.

Research Interests:

Dr. Mezghani’s research interests encompass data mining, machine learning, artificial intelligence, and cybersecurity. He is particularly focused on developing innovative algorithms and techniques to improve the efficiency and security of data systems. His work aims to address the challenges of big data and the ethical use of AI in modern applications.

Author Metrics:

Dr. Mezghani has authored numerous publications in peer-reviewed journals and conferences, with several citations reflecting his impact in the field. His research contributions are well-regarded, particularly in the areas of AI-driven data security and advanced machine learning algorithms. Dr. Mezghani’s work continues to influence the ongoing evolution of data science and cybersecurity practices.

Top Noted Publication:

  • Journal: International Journal of Emerging Markets
  • Year: 2023
  • DOI: 10.1108/IJOEM-06-2020-0619
  • EID: 2-s2.0-85121467821
  • ISSN: 1746-8817, 1746-8809
  • Source: Scopus – Elsevier

“Forecast the Role of GCC Financial Stress on Oil Market and GCC Financial Markets Using Convolutional Neural Networks”

  • Journal: Asia-Pacific Financial Markets
  • Year: 2023
  • DOI: 10.1007/s10690-022-09387-3
  • EID: 2-s2.0-85139767055
  • ISSN: 1573-6946, 1387-2834
  • Source: Scopus – Elsevier

“Forecasting Bitcoin returns using machine learning algorithms: impact of investor sentiment”

  • Journal: EuroMed Journal of Business
  • Year: 2023
  • DOI: 10.1108/EMJB-03-2023-0086
  • EID: 2-s2.0-85170833198
  • ISSN: 1758-888X, 1450-2194
  • Source: Scopus – Elsevier

“Forecasting the impact of financial stress on hedging between the oil market and GCC financial markets”

  • Journal: Managerial Finance
  • Year: 2023
  • DOI: 10.1108/MF-10-2022-0472
  • EID: 2-s2.0-85169306019
  • ISSN: 1758-7743, 0307-4358
  • Source: Scopus – Elsevier

“Influence of oil price fluctuations on the network connectedness between oil, GCC Islamic and conventional financial markets”

  • Journal: International Journal of Islamic and Middle Eastern Finance and Management
  • Year: 2023
  • DOI: 10.1108/IMEFM-09-2021-0392
  • EID: 2-s2.0-85149312705
  • ISSN: 1753-8408, 1753-8394
  • Source: Scopus – Elsevier

Conclusion:

Assist. Prof. Dr. Taicir Mezghani is an excellent candidate for the Best Researcher Award, given his extensive contributions to data science, AI, and their applications in finance and cybersecurity. His work is characterized by its interdisciplinary nature, academic rigor, and practical relevance, making him a prominent figure in his field. Dr. Mezghani’s focus on ethical AI and innovative data systems addresses both current challenges and future needs in the digital economy.

To further strengthen his profile, expanding his research focus, enhancing visibility through open access, and increasing industry collaborations would be beneficial. Overall, Dr. Mezghani’s dedication to advancing AI-driven solutions positions him as a highly deserving nominee for the Best Researcher Award.

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.