Abasalt Bodaghi| Functional equations | Best Researcher Award

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Prof. Abasalt Bodaghi| Functional equations | Best Researcher Award

Islamic Azad University, Iran

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🎓 Early Academic Pursuits

Prof. Abasalt Bodaghi began his academic journey in Shiraz University, where he earned his Bachelor of Science in Mathematics (Education) in 1997. Driven by a deep interest in abstract mathematics, he pursued his M.Sc. in Pure Mathematics with a specialization in Non-commutative Geometry at Shahid Beheshti University in Tehran, graduating in 2000 under the mentorship of Dr. Vida Milani. His academic momentum culminated in a Ph.D. in Pure Mathematics (Analysis) from Islamic Azad University, Science and Research Branch, Tehran, in 2009 under the guidance of the renowned Prof. Alireza Medghalchi.

👨‍🏫 Professional Endeavors

Prof. Bodaghi’s teaching career spans over two decades. Starting as a Lecturer (2000–2009), he rose to Assistant Professor (2010–2015), then to Associate Professor (2015–2020), and ultimately achieved the prestigious rank of Professor in 2020. He also undertook a Postdoctoral Fellowship at Universiti Putra Malaysia (UPM) from 2010 to 2012, where he deepened his expertise in functional analysis and operator algebras. His administrative leadership is reflected in his roles as Editor-in-Chief of the journal "Mathematical Analysis and its Contemporary Applications" and as Editor of the "International Journal of Nonlinear Analysis and Applications".

🧠 Research Focus and Contributions

Prof. Bodaghi’s work significantly advances the theory of Banach algebras, module amenability, functional equations, and non-commutative geometry. His scholarly contributions cover areas such as module structures on iterated duals, (φ,ψ)-amenability, cubic multipliers, and fixed point approaches in algebraic stability problems. His publication record spans highly reputed journals like Banach Journal of Mathematical Analysis, Semigroup Forum, Archivum Mathematicum, Malaysian Journal of Mathematical Sciences, and more. His pioneering work on module derivations, double Jordan centralizers, and quantum spheres showcases his ability to interlink abstract theory with modern mathematical models.

🌍 Impact and Influence

Through a rich portfolio of 17+ high-impact publications, Prof. Bodaghi has made a lasting impression on the global mathematical community. He has collaborated with prominent mathematicians such as M. Amini, M. Eshaghi Gordji, and C. Park, contributing to both Iranian and international research initiatives. His work on the stability of functional equations via fixed point theorems is widely cited and appreciated for its methodological depth and analytical rigor.

📊 Academic Citations

Prof. Bodaghi’s scholarly articles have been cited broadly in both regional and international mathematical research. His contributions are indexed in notable databases such as Scopus, MathSciNet, and Google Scholar, reflecting the academic value and reach of his research output in fields such as algebraic topology, module theory, and abstract harmonic analysis.

💻 Technical and Mathematical Skills

Prof. Bodaghi has advanced capabilities in abstract mathematics, particularly in Banach space theory, topological algebras, functional equations, tensor products, and module contractibility. His technical acumen also includes LaTeX, Mathematica, Maple, and other symbolic computation tools that support high-level mathematical modeling and manuscript preparation.

📚 Teaching Experience

Over the past two decades, Prof. Bodaghi has taught numerous undergraduate and graduate courses in Pure Mathematics, especially in areas such as Functional Analysis, Linear Algebra, Abstract Algebra, and Real/Complex Analysis. His teaching philosophy integrates research exposure, problem-solving, and student-led discovery, creating a vibrant learning environment for aspiring mathematicians.

🏅 Legacy and Future Contributions

Prof. Abasalt Bodaghi’s legacy lies in his scholarly rigor, research integrity, and mentorship excellence. His editorial and academic leadership help shape the future of nonlinear analysis and operator theory in Iran and beyond. As he continues to explore new mathematical frontiers, especially in module derivation theory and quantum structures, his role in advancing mathematical understanding remains pivotal. He is also expected to play a larger role in shaping academic policies and fostering cross-border mathematical collaborations in the coming years.

Selected Publications

Title: Module Amenability of the Second Dual and Module Topological Center of Semigroup Algebras

  • Authors: M. Amini, A. Bodaghi, D. Ebrahimi Bagha

  • Journal: Semigroup Forum, Volume 80(2), pp. 302–312

  • Year: 2010

  • Title: Intuitionistic fuzzy stability of the generalized forms of cubic and quartic functional equations

  • Authors: A. Bodaghi

  • Journal: Journal of Intelligent & Fuzzy Systems, Volume 30(4), pp. 2309–2317

  • Year: 2016

  • Title: The Hermite-Hadamard inequality for r-convex functions

  • Authors: G. Zabandan, A. Bodaghi, A. Kılıçman

  • Journal: Journal of Inequalities and Applications, 2012, Article ID: 215, pp. 1–8

  • Year: 2012

  • Title: On the stability of quadratic double centralizers on Banach algebras

  • Authors: M. E. Gordji, A. Bodaghi

  • Journal: Journal of Computational Analysis and Applications, Volume 13(4)

  • Year: 2011Title: Two multi-cubic functional equations and some results on the stability in modular spaces

  • Authors: C. Park, A. Bodaghi

  • Journal: Journal of Inequalities and Applications, 2020(1), Article 6

  • Year: 2020

Yuxiao Gao | Big Data Science and Technology | Best Researcher Award

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Ms. Yuxiao Gao | Big Data Science and Technology | Best Researcher Award

Taiyuan University of Technology, China

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Early Academic Pursuits

Yuxiao Gao is currently an undergraduate student at Taiyuan University of Technology, majoring in Data Science and Big Data Technology. With a strong academic inclination toward cutting-edge technologies, Yuxiao has already made significant strides in the research community, especially in areas intersecting artificial intelligence and healthcare. His journey into research began with a deep interest in machine learning and its practical applications in the medical domain.

Professional Endeavors

Despite being an undergraduate, Yuxiao has demonstrated academic maturity by publishing a review article in an SCI-indexed journal focusing on deep learning-based medical image segmentation. He also showcased his work at a CCF-C level conference, presenting a novel segmentation framework, emphasizing his capability to contribute at recognized academic platforms. His technical skillset includes Python, Java, PyTorch, and proficiency in Linux environments, positioning him as a competent data science researcher.

Contributions and Research Focus

Yuxiao's research is characterized by interdisciplinary innovation. His notable contributions include developing a knowledge graph for Chinese health policy using Natural Language Processing (NLP)tools and assessing policies quantitatively via the Policy Modeling Consistency (PMC) index. This integration of NLP with healthcare and policy evaluation demonstrates his unique capability to apply data-driven approaches to real-world problems, reflecting both depth and relevance in his academic endeavors.

Collaborations and Academic Influence

Yuxiao has collaborated with faculty members involved in medical imaging and health policy analytics, enriching his interdisciplinary experience. His ability to merge computer vision, NLP, and graph databases to solve complex healthcare issues has made him a valuable contributor to collaborative research teams, even at the early stages of his career.

Academic Citations and Publications

Yuxiao has authored one SCI-indexed review paper and presented at a CCF-C conference, with future publications expected as his research matures. Although citation metrics are currently not applicable due to the early stage of his career, his work’s relevance and potential for impact are evident through the quality of publication and platforms.

Technical Skills

His core technical proficiencies span deep learning frameworks (PyTorch), programming languages (Python, Java), and Linux-based systems. Additionally, Yuxiao has hands-on experience in knowledge graph construction, policy analysis using PMC modeling, and implementing medical image segmentation frameworks, marking his expertise across both structured and unstructured data domains.

Recognition and Award Preference

Given his strong foundation in research, innovation, and interdisciplinary applications of data science, Yuxiao Gao is a deserving candidate for the Best Undergraduate Researcher Award. His achievements, despite being in the early stage of his academic career, reflect both academic rigor and real-world impact.

Legacy and Future Contributions

Looking ahead, Yuxiao aims to expand his work inintelligent healthcare systems and policy informatics, striving to build solutions that bridge the gap between machine learning technologies and societal needs. His passion for integrating science, policy, and innovation is poised to shape meaningful outcomes in both academia and applied research domains.

Selected Publications

  • Title: A Review on Deep Learning-Based Medical Image Segmentation

  • Authors: Yuxiao Gao, [Co-author Names if any]

  • Journal: [Journal Name, e.g., IEEE Transactions on Medical Imaging]

  • Year: [Year, e.g., 2024]

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  • Yuxiao Gao (sole author), or

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