Richard Romano | Economics | Best Paper Award

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Best Paper Award

Richard Romano
University of Florida
 Richard Romano
Award Category Best Paper Award
Institution University of Florida
Country United States
Scopus 7102604921
ORCID 0000-0003-4961-4559
Article Title Multimodal PCSC Sensors for Real-Time Temperature and Force Detection Using LRTNet
Event Best Paper Awards

The Best Paper Award recognizes outstanding scholarly contributions that demonstrate originality, scientific rigor, technological innovation, and significant impact within their respective fields. Richard Romano has been honored for the publication titled “Multimodal PCSC Sensors for Real-Time Temperature and Force Detection Using LRTNet”, a research work that advances intelligent sensing technologies through the integration of multimodal sensor systems and deep learning methodologies.

Abstract

The awarded publication introduces an advanced multimodal sensing framework capable of simultaneously detecting temperature and force in real time. By incorporating the Long-Range Transformer Network (LRTNet) architecture with Polymer Composite Strain Capacitive Sensors (PCSC), the study demonstrates enhanced sensing accuracy, intelligent data interpretation, and improved performance for next-generation smart monitoring applications. The research contributes to the growing intersection of sensor engineering and artificial intelligence.

Awarded Article

Title: Multimodal PCSC Sensors for Real-Time Temperature and Force Detection Using LRTNet

The publication explores a novel sensing platform that combines multimodal sensor technology with deep neural network-based analytics. Through the implementation of LRTNet, the system effectively processes complex sensor signals and improves the reliability of simultaneous temperature and force measurements. The work provides valuable insights for wearable electronics, healthcare monitoring systems, robotics, and intelligent industrial sensing applications.

Author Profile

Richard Romano is affiliated with the University of Florida, United States. His research interests encompass advanced sensor technologies, intelligent sensing systems, machine learning applications, and interdisciplinary engineering innovations. Through his scholarly contributions, he has participated in the development of next-generation sensing frameworks designed to address real-world monitoring and automation challenges.

Research Contributions

  • Development of multimodal PCSC sensor technology.
  • Integration of LRTNet deep learning architecture for sensor data interpretation.
  • Enhanced accuracy in simultaneous temperature and force sensing.
  • Contribution to intelligent wearable and industrial sensing platforms.
  • Advancement of AI-enabled real-time monitoring systems.

Innovation and Impact

The research demonstrates how machine learning can significantly improve sensor intelligence and operational reliability. By combining multimodal sensing capabilities with advanced neural network models, the study establishes a foundation for more adaptive and responsive sensing platforms. Potential applications include smart healthcare devices, robotic systems, human-machine interfaces, industrial automation, and predictive monitoring environments.

Award Recognition

The Best Paper Award acknowledges publications that exhibit exceptional scientific quality, originality, technical excellence, and societal relevance. The selection of this article reflects its contribution to advancing intelligent sensor systems and its potential to influence future developments in AI-driven sensing technologies. The award celebrates both the scholarly achievement of the author and the broader impact of the research on the scientific community.

Conclusion

The recognition of Richard Romano with the Best Paper Award highlights the significance of innovative research that bridges sensor engineering and artificial intelligence. The publication contributes meaningful advancements to real-time multimodal sensing and demonstrates the transformative potential of deep learning in modern sensor applications. Its scientific value and practical relevance make it a distinguished contribution to the field.

References

  1. Romano, R. et al. (2026). Multimodal PCSC Sensors for Real-Time Temperature and Force Detection Using LRTNet. Sensors, MDPI.
    https://www.mdpi.com/1424-8220/26/11/3506
  2. Elsevier. (n.d.). Scopus author details: Richard Romano Author ID 7102604921. Scopus.
    https://www.scopus.com/
  3. Best Paper Awards Committee. (n.d.). Award evaluation criteria and recognition framework.
    https://bestpaperawards.com/

Ahmed Habib | Economics | Editorial Board Member

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Prof. Dr. Ahmed Habib | Economics | Editorial Board Member 

Independent Researcher | Egypt

Ahmed Mohamed Habib is an accomplished researcher and academic specializing in accounting and finance, with a research portfolio spanning corporate governance, intellectual capital performance, corporate social responsibility (CSR), environmental, social, and governance (ESG) practices, working capital management (WCM), managerial ability, auditor report readability, corporate narrative reporting, corporate liquidity, cost of debt, corporate finance, earnings management, and corporate investment efficiency. His work emphasizes performance optimization, continuous improvement, business excellence, and frontier analysis through advanced methodologies such as Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI), knowledge management, and Decision Support Systems (DSS), integrating rigorous econometric analysis to generate practical insights for firms and financial institutions. Habib has contributed extensively to understanding how efficiency in working capital, corporate governance, and intellectual capital impacts firm performance and value, particularly during crises such as the COVID-19 pandemic and global economic disruptions like the Russia–Ukraine conflict. His publications analyze diverse contexts, including Romanian, Polish, US, Egyptian, and MENA-region firms, exploring the interplay between competitive strategies, ESG practices, financial distress mitigation, and organizational efficiency. Additionally, he investigates the effects of managerial ability and auditor report readability on corporate liquidity, cost of debt, and earnings management, applying DEA-MPI approaches to assess intellectual capital and working capital management efficiency. Habib’s research also extends to healthcare systems and sports organizations, evaluating operational and financial efficiency through innovative analytical frameworks. Based in the United Kingdom and Ukraine, he has maintained an independent research position in accounting and finance since 2006 at Zagazig, Sharqia, Egypt, contributing over 26 publications in high-impact journals and book chapters that bridge theoretical frameworks with empirical applications. His interdisciplinary work provides valuable insights into corporate strategy, sustainability, and efficiency, advancing knowledge in financial and organizational management, fostering business excellence, and informing policymakers, investors, and practitioners on optimizing firm performance under dynamic global conditions.

Profile: ORCID

Featured Publications

  1. Habib, A. M., Nuta, A. C., Neslihanoglu, S., Dalwai, T., & Rangu, C. M. (2025). Analyzing the market performance of Romanian firms: Do the COVID-19 crisis and classification type matter? International Journal of Emerging Markets. https://doi.org/10.1108/IJOEM-05-2023-0842

  2. Zimon, G., Habib, A. M., & Haluza, D. (2024). Does the quality management system affect working capital management efficiency? Evidence from Polish firms. Cogent Business & Management, 11(1), 1–21. https://doi.org/10.1080/23311975.2023.2292787

  3. Habib, A. M., & Mourad, N. (2024). Analyzing the efficiency of intellectual capital: A new approach based on DEA-MPI technology. Benchmarking: An International Journal, 31(9), 1–25. https://doi.org/10.1108/BIJ-06-2022-0384

  4. Habib, A. M., Yang, G., & Cui, Y. (2024). Do competitive strategies affect working capital management efficiency? Business Process Management Journal, 30(6), 1–28. https://doi.org/10.1108/BPMJ-12-2023-0953

  5. Habib, A. M., & Dalwai, T. (2024). Does the efficiency of a firm’s intellectual capital and working capital management affect its performance? Journal of the Knowledge Economy, 15(3), 1–24. https://doi.org/10.1007/s13132-023-01138-7

Ahmed Mohamed Habib’s research advances the understanding of corporate efficiency, governance, and sustainability, providing actionable insights that help firms optimize performance, mitigate financial risk, and enhance ESG outcomes. His work bridges theory and practice, driving innovation in finance, management, and organizational decision-making globally.

Francisco Venegas-Martínez | Economics | Best Researcher Award

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Dr. Francisco Venegas-Martínez | Economics | Best Researcher Award

Full Professor | Instituto Politécnico Nacional | Mexico

Professor Francisco Venegas-Martínez is an exceptionally distinguished researcher whose career spans decades of groundbreaking contributions in economics, finance, and environmental studies. Holding dual PhDs in Mathematics and Economics from Washington State University and a post-doctoral tenure at the University of Oxford, he currently serves as a Profesor-Investigador at the Instituto Politécnico Nacional (IPN) in Mexico, where he has profoundly influenced both research and higher education. His research interests encompass environmental science, greenhouse gas emissions, renewable and non-renewable resources, economic and financial theory, and energy regulation, reflecting a rare interdisciplinary mastery. Professor Venegas-Martínez has an outstanding publication record with approximately 300 peer-reviewed articles in high-impact national and international journals, over 27 authored books including the widely cited “Riesgos Financieros y Económicos,” and more than 100 book chapters published by renowned houses such as Routledge and Springer. His work has garnered roughly 4,600 citations and recognition in major bibliometric rankings including EconLit, RePEc, and CONACYT metrics, making him one of the most prolific and influential Mexican researchers in economics and finance. His research has been cited by leading global economists including Stanley Fischer, Arnold Zellner, and Frank Fabozzi, highlighting the international significance of his work. Professor Venegas-Martínez has received numerous prestigious awards, such as the Finance Diamond Award from Fundación IMEF (2023), the Lázaro Cárdenas Distinction from IPN (2012), and the National Prize in Economic Research “Maestro Jesús Silva Herzog” (2002), reflecting both national and international recognition of his scientific excellence. Beyond publications, he has contributed to over 40 editorial boards, delivered more than 300 keynote lectures worldwide, and mentored generations of students and researchers. His deep and sustained impact on economic, financial, and environmental scholarship, combined with his leadership in scientific communities, makes him eminently suitable for recognition as a Best Researcher Award recipient.

Profiles: Google Scholar | Scopus | ORCID | LinkedIn | ResearchGate

Featured Publications

  1. Fonseca-Zendejas, A. S., Borrego-Salcido, C., & Venegas-Martínez, F. (2025). An estimated DSGE model under the New Keynesian framework for Mexico. Computational Economics.

  2. Jiménez-Preciado, A. L., Martínez-García, M. Á., Trejo-García, J. C., & Venegas-Martínez, F. (2025). Short- and long-term assessments of ESG risk in Mexican mortgage institutions: Combining expert surveys, radar plot visualization, and cluster analysis. Sustainability.

  3. Jiménez-Preciado, A. L., Álvarez-García, J., Cruz-Aké, S., & Venegas-Martínez, F. (2024). The power of words from the 2024 United States presidential debates: A natural language processing approach. Information.

  4. Venegas-Martínez, F., & Jiménez-Preciado, A. L. (2024). Clustering a sample of major and emerging economies in function of their economic policy uncertainty: K-means, agglomerative hierarchical clustering and density-based spatial clustering with noise. EconoQuantum.

  5. Jiménez-Preciado, A. L., Cruz-Aké, S., & Venegas-Martínez, F. (2024). Identification of patterns in CO2 emissions among 208 countries: K-means clustering combined with PCA and non-linear t-SNE visualization. Mathematics.