Associate Professor | Zhejiang University of Technology |China

Yinglong Li demonstrates strong academic and research excellence, supported by a solid portfolio of publications, patents, and externally funded projects. His 22 SCI/Scopus-indexed journal papers, more than 140 Web of Science citations, and a steadily increasing h-index reflect both productivity and growing scholarly influence. His contributions are further validated through documented outputs such as two published textbooks (ISBN: 9787302557425, 9787115415400), ten patents, and verified academic profiles including Google Scholar and institutional webpages. Strengths include his ability to integrate privacy protection, deep learning, and computer vision into practical AI solutions, as evidenced by consultancy projects with industry partners in marine systems and smart security. His research has consistently translated into deployable, high-impact technologies, demonstrating maturity in innovation and applied problem-solving. Areas for improvement include expanding international collaborations, enhancing cross-disciplinary engagement with emerging domains such as trustworthy AI governance, and increasing participation in editorial boards or leadership roles in prestigious conferences, which would further elevate his global visibility. Moving forward, his research has strong potential to contribute significantly to privacy-preserving intelligent systems, multimodal vision architectures, and secure data ecosystems for smart cities. With a well-documented research track record, growing citation metrics, and scalable research themes aligned with global technological needs, he is positioned for continued advancement and wider impact in the AI research community.

Citation Metrics (Google Scholar)

240180

120

Citations
234

h-index
8

i10-index
6

Citations
h-index
i10-index

Dr. Agnieszka Niemczynowicz - Machine Learning - Best Researcher Award

Cracow University of technology - Poland

AUTHOR PROFILE

ORCID

EARLY ACADEMIC PURSUITS 🎓

Agnieszka Niemczynowicz began her academic journey in the field of solid-state physics, earning her Ph.D. from the Faculty of Physics and Applied Informatics at the University of Łódź, Poland, in 2014. Her early research laid a strong foundation in the fundamental aspects of physics, equipping her with a deep understanding of physical systems and analytical techniques.

PROFESSIONAL ENDEAVORS 🏢

Upon completing her doctorate, Agnieszka transitioned into academia, taking up the role of Associate Professor at the Cracow University of Technology. She has since been instrumental in bridging the gap between physics and computational sciences, expanding her research horizons to include computational and mathematical methods for analyzing complex data sets across various disciplines.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Agnieszka’s research is at the forefront of computational analysis, focusing on multivariate statistics, chemometrics, and deep learning. She has developed advanced statistical and machine Machine Learning learning models that have found applications in diverse fields such as engineering, biology, medicine, and management. Her work is characterized by its interdisciplinary approach, integrating complex data analysis methods into practical applications.

ACCREDITATIONS AND RECOGNITION 🏅

A prolific researcher, Agnieszka has authored around 50 publications in international journals, contributing significantly to her field. Her excellence in research was recognized with the Machine Learning prestigious Doak Award in 2022, highlighting her impactful contributions to the scientific community and her role as a thought leader in computational analysis.

IMPACT AND INFLUENCE 🌍

Agnieszka’s work has had a significant impact on how complex analytical data is interpreted and utilized across various sectors. Her models have improved the accuracy of data-driven Machine Learning decisions in numerous applications, thereby enhancing the efficiency and effectiveness of processes in engineering, biology, medicine, and more.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Currently leading international research grants, Agnieszka investigates the mathematical foundations of hypercomplex neural networks and their applications. Her ongoing work promises to further unravel the complexities of data analysis, pushing the boundaries of what machine learning and computational methods can achieve. Her legacy lies in her pioneering efforts to integrate advanced mathematical models into practical solutions, ensuring that her influence will be felt across multiple disciplines for years to come.

NOTABLE PUBLICATIONS

Title: A critical analysis of the theoretical framework of the Extreme Learning Machine
Authors: Irina Perfilieva, Nicolás Madrid, Manuel Ojeda-Aciego, Piotr Artiemjew, Agnieszka Niemczynowicz
Journal: Neurocomputing
Title: Use of physicochemical, FTIR and chemometric analysis for quality assessment of selected monofloral honeys
Authors: Monika Kędzierska-Matysek, Anna Teter, Mariusz Florek, Arkadiusz Matwijczuk, Agnieszka Niemczynowicz, Alicja Matwijczuk, Grzegorz Czernel, Piotr Skałecki, Bożena Gładyszewska
Journal: Journal of Apicultural Research
Title: Conclusions
Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
Journal: (Book chapter, not a journal)
Title: Current research methods in mathematical and computer modelling of motivation management
Authors: Agnieszka Niemczynowicz, Radosław Antoni Kycia
Journal: (Book chapter, not a journal)
Title: Introduction
Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
Journal: (Book chapter, not a journal)