Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

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Dr. Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

Joint Institute for Nuclear Research | Russia

Dr. Oleg Selyugin is a Russian empirical and theoretical physicist with a distinguished career in high-energy hadron scattering and the structure of hadrons. After completing his studies at the Physics Department of Moscow State University, he joined the Joint Institute for Nuclear Research (JINR), first as a probationer and researcher at the Laboratory of Nuclear Problems, and later at the Bogoliubov Theoretical Laboratory (BTL), where he now serves as a leading scientist. At BTL, he earned his Ph.D. with the thesis “High energy elastic hadron-hadron scattering in a wide momentum transfer region,” and later obtained his Doctor of Physics and Mathematics degree with the thesis “The structure of high-energy amplitude of the elastic hadron-hadron scattering in the diffraction region.” Dr Selyugin has been recognized with multiple International Prizes of JINR for his outstanding contributions to polaron physics, hadron physics, and high-energy physics. His primary research interests include the structure of hadrons (PDFs, GPDs, form-factors), phenomenology of high-energy physics (differential cross sections, spin phenomena), models of extra dimensions (d-brane gravity), and nonlinear effects. He has been actively involved in interpreting experimental results from the CERN LHC, particularly the TOTEM and ATLAS Collaborations. His theoretical work integrates electromagnetic and gravitational form-factors derived from novel t-dependent GPDs, as well as soft and cross-even pomeron contributions, within dispersion-relation-based frameworks. With over 180 scientific papers, Dr Selyugin has made a profound and lasting impact on the understanding of elastic hadron scattering at high energies. Although specific bibliometric indicators such as 17 h-index, 78 documents, and 815 citations vary across databases, his scientific influence is widely recognized within the international physics community. He continues his pioneering research at JINR in Dubna, Russia.

Profiles: Scopus | Orcid

Featured Publications

Selyugin, O. V. (2024). Unified description of elastic hadron scattering at low and high energies. Physics of Atomic Nuclei, 87(S2), S349–S362.

Kai Wang | Statistical Data Visualization | Best Researcher Award

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Assoc Prof. Dr. Kai Wang | Statistical Data Visualization | Best Researcher Award

Shandong First Medical University | China

Assoc Prof. Dr. Kai Wang is an Associate Professor at the State Key Laboratory of Advanced Drug Delivery and Release Systems, School of Pharmaceutical Sciences & Institute of Materia Medica, Shandong First Medical University, China, whose work bridges chemistry, biology, and medicine. His research focuses on the design of boronic acid–based spectroscopic probes for glucose sensing and their application in fluorescence detection and bioimaging, as well as glycobiology studies that explore the therapeutic and diagnostic potential of saccharides in drug development and disease treatment. Dr. Wang has developed several innovative fluorescent probes that achieve high sensitivity and selectivity in imaging cellular glucose in live cells and zebrafish, contributing to the understanding of cellular glucose homeostasis, ROS signaling, and the interplay between diabetes and depression. He collaborates with renowned researchers worldwide, including Tony D. James, Zhongnan Wu, Shaojie Zhang, and Meng Meng, and maintains active membership in the Chinese Chemical Society and the Chinese Society of Biophysics. he has 1 document, 1 citation, and an h-index of 1, reflecting the growing international recognition of his contributions. His goal is to provide novel molecular tools and strategies for disease diagnosis, innovative drug design, and translational medicine.

Profiles : Scopus | Orcid

Featured Publications

“Reversible Recognition-Based Boronic Acid Probes for Glucose Detection in Live Cells and Zebrafish”

“Biomimetic Analysis of Neurotransmitters for Disease Diagnosis through Light‐Driven Nanozyme Sensor Array and Machine Learning”

“Synthesis of Diboronic Acid-Based Fluorescent Probes for the Sensitive Detection of Glucose in Aqueous Media and Biological Matrices”

“A DNA nanoscaffold-based electrochemical assay for sensitive determination of O-GlcNAc transferase (OGT) activity and its application in cell-permeable OGT inhibitors screening”

“A glucose-rich heteropolysaccharide from Marsdenia tenacissima (Roxb.) Wight et Arn. and its zinc-modified complex enhance immunoregulation by regulating TLR4-Myd88-NF-κB pathway”

Xhavit Islami | Econometrics and Statistical Economics | Best Researcher Award

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Assist Prof. Dr. Xhavit Islami | Econometrics and Statistical Economics | Best Researcher Award

AAB College | Albania

Assist Prof. Dr. Xhavit Islami is a leading academic in Management and Strategic Management at the Faculty of Economics, AAB College, Republic of Kosovo. He earned his PhD in Organizational Sciences and Management from the University of “Ss. Cyril and Methodius” in North Macedonia and has since built a strong record of research and scholarly contributions. Professor Islami has completed 35 research projects and is currently engaged in five ongoing projects, demonstrating his active involvement in advancing knowledge in management, strategic decision-making, human resource management, and supply chain management. He has published 16 articles in high-impact, Scopus-indexed journals and authored two books, reflecting his commitment to rigorous scholarship. His research work has earned him a Scopus h-index of 4 with 122 citations, highlighting the influence of his publications within the international academic community. He has also participated in five consultancy and industry-sponsored projects, bridging the gap between theory and practice. Professor Islami has collaborated on significant initiatives, including the “EDU-LAB Horizon” Project (2025–2027), and serves on the Scientific Committee of AAB College. His studies focus on innovative strategies, organizational performance, and the integration of artificial intelligence in management practices, providing practical insights for businesses and policymakers. Through his research, he has contributed to the understanding of competitive advantage, sustainable growth, and organizational effectiveness. Professor Islami maintains active professional profiles on Scopus, ORCID, ResearchGate, SSRN, and Academia.edu, ensuring his work is accessible and widely recognized. His scholarly achievements, combined with his ongoing research and industry collaborations, position him as a prominent figure in management and strategic studies, making him a highly deserving candidate for the Best Researcher Award.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

“When and How Does Innovation Augment the Effect of HRM on SME Performance?”

“Artificial intelligence and value-based strategy: a literature review and future research directions”

“Lean manufacturing and firms’ financial performance: the role of strategic supplier partnership and information sharing”

“Does competitive strategy moderate the linkage between HRM practices and company performance”

“The Role of Internal Human Resource Orchestration on Firm Performance”