Diana Patricia Molina Delgado | Technological Networks | Best Researcher Award

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Dr. Diana Patricia Molina Delgado | Technological Networks | Best Researcher Award

Innovation Technician at Federació de Cooperatives Agràries de Catalunya (FCAC), Spain📖

Diana Molina Delgado is an experienced professional focused on optimizing organizations and processes through innovative, sustainable, and practical solutions. With a background in agricultural sciences and business administration, she has worked in various roles, from postharvest management to research and development in the agribusiness sector. Diana has a strong commitment to sustainability and cooperation, and she has participated in numerous international projects and congresses.

Profile

Scopus Profile

Education Background🎓

  • Master in Business Administration (MBA) – IMF Business School (2020-2023), specializing in business administration principles in the agrifood sector.
  • Ph.D. in Agricultural Science and Food Technology – Universitat de Lleida (2001-2008), focusing on optimizing harvest dates and maintaining apple quality using non-destructive techniques.
  • Agricultural Engineer – Universidad Nacional de Colombia (1991-1998), where she worked on optimizing agricultural processes.
  • Social Science Bachelor – Universidad Distrital (1987-1994), focusing on evaluating social processes.

Professional Experience🌱

  • Federació de Cooperatives Agràries de Catalunya (July 2021-Present): Leading projects and managing grants while supporting R&D and innovation for cooperatives.
  • IRTA – Mas Badia (Sept 2017-Dec 2019): Postharvest Management Advisor, focusing on postharvest process optimization for the apple industry in Girona and coordinating Agrofresh® application services.
  • ACTEL GRUP (March 2009-Aug 2017): Fruit Production Advisor, advising producers on technical and administrative management in fruit production.
  • Ecole Supérieure d’Agriculture d’Angers (Jan-Jun 2007): Invited Researcher, conducting consumer quality assessment in French apple varieties.
  • Universitat de Lleida / IRTA (Sept 2004-Dec 2008): PhD Researcher, optimizing postharvest protocols and transferring technology to the agribusiness sector.
  • Jardiland (Oct 2001-Aug 2004): Greenhouse Manager, managing staff and overseeing seasonal marketing and stock control.
  • Universidad Central (Oct 2000-Feb 2001): Associated Professor in Business Administration, teaching Mathematics and Statistics.
Research Interests🔬

Diana’s research focuses on optimizing agricultural processes, particularly in the agrifood sector, with an emphasis on postharvest technology, quality evaluation, and sustainability. Her work involves non-destructive techniques for quality assessment, with applications in fruit and vegetable sectors, aiming to improve product quality, storage, and consumer satisfaction.

Author Metrics

Diana has contributed significantly to scientific literature with over 17 publications, including articles in journals such as Biosystems Engineering, Food Science and Technology International, and Journal of the Science of Food and Agriculture. Her work addresses advancements in postharvest technology, non-destructive techniques for measuring fruit quality, and consumer preference studies, among other topics.

Publications Top Notes 📄

1. Antioxidant Activity Determines On-Tree Maturation in ‘Golden Smootheé’ Apples

  • Authors: Molina-Delgado, D., Larrigaudière, C., Recasens, I.
  • Journal: Journal of the Science of Food and Agriculture
  • Year: 2009
  • Volume: 89
  • Issue: 7
  • Pages: 1207-1212
  • DOI: 10.1002/jsfa.3529
  • Citations: 11
  • Summary: This paper examines how antioxidant activity impacts the maturation process of ‘Golden Smootheé’ apples, with an emphasis on postharvest quality.

2. Relationship Between Acoustic Firmness and Magness Taylor Firmness in Royal Gala and Golden Smoothee Apples

  • Authors: Molina-Delgado, D., Alegre, S., Puy, J., Recasens, I.
  • Journal: Food Science and Technology International
  • Year: 2009
  • Volume: 15
  • Issue: 1
  • Pages: 31-40
  • DOI: 10.1177/1082013208101797
  • Citations: 21
  • Summary: This study explores the relationship between acoustic firmness and the traditional Magness Taylor test for firmness in apples, offering insight into non-destructive testing methods.

3. Addressing Potential Sources of Variation in Several Non-Destructive Techniques for Measuring Firmness in Apples

  • Authors: Molina-Delgado, D., Alegre, S., Barreiro, P., Ruiz-Altisent, M., Recasens, I.
  • Journal: Biosystems Engineering
  • Year: 2009
  • Volume: 104
  • Issue: 1
  • Pages: 33-46
  • DOI: 10.1016/j.biosystemseng.2009.01.004
  • Citations: 27
  • Summary: The paper addresses the sources of variation found in non-destructive firmness measurement techniques, focusing on improving the reliability and accuracy of these methods.

4. A Multi-Stakeholder Perspective on the Use of Digital Technologies in European Organic and Agroecological Farming Systems

  • Authors: Giagnocavo, C., Duque-Acevedo, M., Terán-Yépez, E., Van Nieuwenhove, T., Volpi, I.
  • Journal: Technology in Society
  • Year: 2025
  • Volume: 81
  • Article Number: 102763
  • DOI: Link is disabled (currently inaccessible)
  • Citations: 0 (as of now)
  • Type: Open Access Article
  • Summary: This article examines the use of digital technologies in organic and agroecological farming systems across Europe, exploring the diverse perspectives of various stakeholders involved in this transformative approach.

Conclusion

Dr. Diana Molina Delgado exemplifies the qualities of an outstanding researcher. Her contributions to the optimization of agricultural processes, especially in postharvest technology, have practical implications that benefit the agrifood industry, sustainability efforts, and consumer satisfaction. With a clear commitment to advancing innovative solutions, her work stands out as both impactful and practical. The areas for improvement highlighted are relatively minor in comparison to her extensive body of work and accomplishments.

Given her expertise, innovative contributions, and commitment to sustainability, I strongly recommend Dr. Diana Molina Delgado for the Best Researcher Award. Her continued work has the potential to shape the future of agricultural sciences and sustainability practices globally.

Qinglai Wei | Self-Learning Systems | Best Researcher Award

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Prof. Dr. Qinglai Wei | Self-Learning Systems | Best Researcher Award 

Associate Director, at Institute of Automation, Chinese Academy of Sciences, China.

Professor Qinglai Wei is a distinguished researcher and educator specializing in control systems, computational intelligence, and learning-based optimization. Serving as the Associate Director at The State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, he has made significant contributions to adaptive dynamic programming, nonlinear control, and reinforcement learning. With an illustrious academic journey from Northeastern University and rich professional experience, Prof. Wei has authored numerous influential papers, books, and book chapters. His awards include multiple IEEE honors and recognition as a Clarivate Highly Cited Researcher. He is a prominent figure in advancing intelligent control systems and their applications in complex scenarios.

Professional Profile

Scopus

Google Scholar

Education 🎓

  • Ph.D. in Control Theory and Control Engineering (2009): Northeastern University, China. Advised by Prof. Huaguang Zhang, his research focused on intelligent control systems.
  • M.S. in Control Theory and Control Engineering (2005): Northeastern University, China, under Prof. Xianwen Gao’s mentorship.
  • B.S. in Automation (2002): Northeastern University, China, advised by Baodong Xu.
    These academic milestones laid the foundation for his expertise in adaptive dynamic programming and intelligent systems.

Professional Experience 💼

  • Associate Director (2018–Present): The State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences.
  • Professor (2016–Present): The State Key Laboratory and the School of Artificial Intelligence, University of Chinese Academy of Sciences.
  • Visiting Scholar roles at University of Rhode Island (2018) and University of Texas at Arlington (2014) reflect his international collaboration and academic outreach.
    Earlier roles include Associate and Assistant Professor positions at The State Key Laboratory, showcasing steady growth in his academic career.

Research Interests 🔬

Prof. Wei’s research spans:

  • Computational Intelligence & Intelligent Control
  • Learning Control & Reinforcement Learning
  • Optimal & Nonlinear Control
  • Adaptive Dynamic Programming
    Applications include process control, smart grids, and multi-agent systems. His innovative methods continue to drive advancements in control theory and intelligent systems.

Awards 🏆

Prof. Wei’s excellence is marked by accolades like:

  • Best Paper Awards (2023 & 2022): International CSIS-IAC and China Automation Congress.
  • IEEE Outstanding Paper Awards (2018): Recognition for impactful contributions to the IEEE journals.
  • Highly Cited Researcher (2018 & 2019): By Clarivate Analytics for his influential publications.
    Other honors include National Natural Science Foundation Awards and Young Researcher Awards, emphasizing his leadership in the field.

Top Noted Publications 📚

  • “Learning and Controlling Multiscale Dynamics in Spiking Neural Networks” (2024, IEEE Transactions on Cybernetics): This study employs Recursive Least Square (RLS) modifications to manage multiscale dynamics in spiking neural networks. It advances neural control methods for adaptive tasks in dynamic environments【8】.
  • “Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent Systems” (2024, IEEE/CAA Journal of Automatica Sinica): This paper focuses on event-triggered mechanisms to ensure robust consensus in multiagent systems under parallel optimal control.
  • “Primal-Dual Adaptive Dynamic Programming for Nonlinear Systems” (2024, Automatica): A framework using primal-dual adaptive dynamic programming tackles the stabilization and optimization of nonlinear systems.
  • “Class-Incremental Learning with Balanced Embedding Discrimination” (2024, Neural Networks): This work enhances class-incremental learning by introducing techniques to balance embeddings and improve discrimination among new and existing classes.

Conclusion

Qinglai Wei is exceptionally suited for the Research for Best Researcher Award. His prolific contributions to control theory, computational intelligence, and reinforcement learning, combined with his global recognition and leadership, exemplify his stature as a world-class researcher. With a proven track record of innovative research, impactful publications, and numerous accolades, he stands out as a strong candidate for this prestigious honor. Continued expansion into interdisciplinary collaborations and mentorship initiatives will further solidify his legacy as a pioneering researcher.