Sonia Abdennadher | Emerging Technologies | Research Excellence Award

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Dr. Sonia Abdennadher | Emerging Technologies | Research Excellence Award

The Higher Colleges of Technology | United Arab Emirates

Dr. Sonia Abdennadher, PhD, CMA, is an accomplished Associate Professor of Finance and Accounting at the Higher Colleges of Technology (HCT), Al Ain, United Arab Emirates, and a tenured Associate Professor at the University of Rouen, France. With over two decades of academic and professional experience across Europe and the Middle East, she has established a strong international reputation in corporate governance, auditing, financial reporting, fintech adoption, and ESG practices. Dr. Abdennadher earned her PhD in Business Administration from Paris-Saclay University, where her doctoral research pioneered the study of technology intermediation in corporate governance, with a particular focus on Internet voting in shareholders’ general meetings. Her academic background is further strengthened by dual master’s degrees in Networks Management and Economics and International Finance, Trading, and Capital Markets, complemented by a solid undergraduate foundation in finance. At HCT, Dr. Abdennadher plays a key leadership role, serving as Chair of Promotion Committees, member of the Higher Faculty Promotion Committee, Applied Research Coordinator, and System Course Team Leader in Sustainable Finance. She has taught a wide range of undergraduate and postgraduate courses in finance, accounting, auditing, corporate governance, sustainable finance, and investment analysis, and has extensive experience in executive education and capstone research supervision. Her research portfolio includes numerous high-impact publications in leading Q1 journals such as Journal of Business Ethics, Finance Research Letters, Corporate Governance, Corporate Social Responsibility and Environmental Management, and International Journal of Finance & Economics. Her work bridges theory and practice by examining blockchain, artificial intelligence, fintech, and ESG measurement within financial markets and governance systems, particularly in the UAE and MENA region. Dr. Abdennadher has successfully led and co-led multiple competitive research grants exceeding AED 600,000, and actively collaborates with regulators, stock exchanges, and Big Four audit firms. Through her scholarship, leadership, and policy-relevant research, she continues to contribute significantly to the modernization of corporate governance and sustainable finance globally.

 

Citation Metrics (Scopus)

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Citations
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Documents
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h-index
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Citations

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Featured Publications


The Effects of Blockchain Technology on the Accounting and Assurance Profession in the UAE: An Exploratory Study


– Journal of Financial Reporting and Accounting, Vol. 20(1), pp. 53–71, 2022

Corporate Social Responsibility Antecedents and Practices as a Path to Enhance Organizational Performance: Evidence from SMEs


– Corporate Social Responsibility and Environmental Management, Vol. 28(6), pp. 1647–1663, 2021

The Effectiveness of E-Corporate Governance: An Exploratory Study of Internet Voting at Shareholders’ Annual Meetings in France


– Corporate Governance: The International Journal of Business in Society, Vol. 20(4), 2020

Fengzhou Wang | Industry Collaboration | Best Researcher Award

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Mr. Fengzhou Wang | Industry Collaboration | Best Researcher Award

Mr. Fengzhou Wang | Zhe Jiang University | China

The nominee is an emerging researcher in the field of industrial engineering, currently engaged in advanced studies with a strong focus on traffic big data analytics, machine learning, and large-scale AI models. Their academic journey began with foundational training in system modeling and optimization algorithms, which laid the groundwork for their present research direction. Through this evolving academic path, the nominee has developed a growing interest in applying computational intelligence to transportation systems, contributing to the interdisciplinary space where engineering, data science, and artificial intelligence converge. Despite being at an early stage of their research career, the nominee has participated in scholarly work that includes publishing in reputable indexed journals. Their contribution to the article on segmented parabolic adjustment of the FAST reflector demonstrates proficiency in programming computation, data visualization, and scientific writing—skills essential for modern research environments. While the nominee has not yet undertaken formal research projects, consultancy assignments, patents, or editorial responsibilities, they remain committed to expanding their expertise and research footprint. The nominee possesses a strong sense of scientific curiosity and expresses an aspiration to contribute meaningfully to their field in the future. They acknowledge current limitations related to resources, knowledge, and experience but emphasize a forward-looking mindset rooted in creativity and innovative thinking. Their research interests reflect an alignment with emerging global priorities, particularly the integration of AI and big data for intelligent transportation systems. Through academic participation and continued skill development, the nominee aims to build a foundation for impactful research and real-world innovation. By engaging with the research community and enhancing technical competencies, they seek to evolve into a contributor capable of influencing advancements in transportation engineering, machine learning applications, and AI-driven solutions.

Profiles: Scopus | Orcid 

Featured Publications

Wang, F., Kang, Y., & Guo, F. (2024). Segmented parabolic adjustment of the FAST reflector utilizing spatial coordinate rotation transformation. Measurement Science and Technology, 35(10). https://doi.org/10.1088/1361-6501/ad5c93

Raffaele Marotta | Industry Collaboration | Young Innovator Award

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Dr. Raffaele Marotta | Industry Collaboration | Young Innovator Award

University of Naples Federico II | Baker Hughes | Italy

Dr. Raffaele Marotta is an accomplished researcher in vehicle dynamics, control systems, and AI-driven estimation, with proven academic and industrial impact. He earned his Ph.D. in Industrial Engineering (Mechatronics) with honors from the University of Naples Federico II, focusing on AI-enhanced vehicle dynamics. His career includes key roles at the Italian National Research Council (CNR), TU Ilmenau, Tenneco, ZF Group, and currently Baker Hughes, where he leads the development of advanced control algorithms for sustainable energy systems. He has contributed significantly to the European OWHEEL project, developing active chassis control and virtual sensing strategies. His research integrates Kalman filtering, neural networks, reinforcement learning, and digital twins into practical solutions for automotive and energy applications. He has published 22 documents, with 83 citations across 42 sources and an h-index of 6, reflecting strong scientific visibility and influence. His works, published in IEEE and SAE journals, include pioneering studies on wheel displacement estimation, traction force prediction, and vehicle mass estimation. International collaborations across Italy, Germany, Belgium, and Lithuania highlight his global network and impact. Recognized by Nova Talent’s top  global talent network, he also mentors young engineers in STEM leadership programs. With his blend of theoretical innovation, experimental validation, and industrial application, Dr. Marotta stands out as a promising candidate for global research excellence awards.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

“Multi-output physically analyzed neural network for the prediction of tire–road interaction forces”

“Deep learning for the estimation of the longitudinal slip ratio”

“Estimation of the tire-road interaction forces by using Pacejka’s formulas with combined slips and camber angles”

“Active control of camber and toe angles to improve vehicle ride comfort”

“Improvement of traction force estimation in cornering through neural network”

“Camber angle estimation based on physical modelling and artificial intelligence”

“Electric vehicle corner architecture: driving comfort evaluation using objective metrics”

“A PID-Based Active Control of Camber Angles for Vehicle Ride Comfort Improvement”

“A strain-based estimation of tire-road forces through a supervised learning approach”

“On the prediction of the sideslip angle using dynamic neural networks”

“Neural Network-Based Virtual Measurement of Road Vehicle Wheel Displacements”

“Enhancing Wheel Vertical Displacement Estimation in Road Vehicles Through Integration of Model-Based Estimator with Artificial Intelligence”

“On the measurement of unsprung mass displacement of road vehicles through a model-based virtual sensor”

“Model-Based Vehicle Mass Estimation for Enhanced Adaptive Cruise Control Performance”