Selman Kızılkaya | Health Management | Best Academic Researcher Award

Assoc. Prof. Dr. Selman Kızılkaya | Health Management | Best Academic Researcher Award

Head of the Department of Health Management | The University of Dicle University | Turkey

Assoc. Prof. Dr. Selman Kızılkaya is a researcher in health management whose work focuses on critical challenges influencing healthcare systems, professional well-being, and public trust. His research spans healthcare system distrust, violence against healthcare professionals, work engagement, burnout, epidemic-related anxiety, reproductive health, and behavioral determinants shaping health outcomes. He has contributed more than 20 publications in internationally indexed journals, including SCI and Scopus outlets such as Discover Psychology, Current Psychology, Health Expectations, Discover Social Science and Health, and Disaster Medicine & Public Health Preparedness. His Google Scholar metrics 78 citations, h-index of 5, and i10-index of 2 reflect the growing influence of his interdisciplinary scholarship. A significant aspect of his work lies in developing and validating psychometric scales that capture healthcare professionals’ experiences, patient provider communication dynamics, and public perceptions of health systems. His studies provide evidence-based insights that support policy development, improve workplace safety in healthcare settings, and reinforce trust-building strategies between patients and health institutions. He is also engaged in collaborative research across public health, behavioral science, and organizational psychology, contributing to knowledge that informs healthcare workforce policies and patient centered care. His ongoing research continues to shape understanding of health behavior and system-level determinants affecting healthcare quality and outcomes.

Profiles: ORCID | Google Scholar 

Featured Publications

Kızılkaya, S., & Şenel Tekin, P. The effect of COVID-19 on quality of life: A community-based study in Türkiye. Disaster Medicine and Public Health Preparedness.

Kizilkaya, S., Şeremet, G. G., & Ekİncİ, N. Fertility-related quality-of-life scale for women: Development and validation. Women’s Reproductive Health.

Kizilkaya, S., & Ekİncİ, N. The moderating effects of gender and age on the relationship between stress management training, work engagement, and epidemic anxiety in healthcare professionals. Discover Psychology.

Durgun, B., & Kızılkaya, S. Determinants of fertility rates in Türkiye: The role of women’s income, human capital, participation in civil society and life expectancy.

Kızılkaya, S., & Buğdali, B. he relationship between healthcare system distrust and intention to use violence against health professionals: The mediating role of health news perceptions.

Magdalena Sobieska | Rewards & Recognition | Research Excellence Award

Prof. Magdalena Sobieska | Rewards & Recognition | Research Excellence Award

Dept. of Rehabilitation and Physiotherapy | The University of  Poznań University of Medical Sciences | Poland

Prof. Magdalena Sobieska is a distinguished researcher whose scholarly contributions sit at the intersection of immunology, physiotherapy, and rehabilitation medicine. Her work is characterized by a sustained commitment to understanding the biological mechanisms underpinning inflammatory responses, acute phase reactions, and immune activation in both clinical and physiotherapeutic contexts. With 117 scientific documents, 1,868 citations, and an h-index of 20, she has established herself as an influential figure in multidisciplinary biomedical research. A major thematic focus of her research involves the clinical applicability of acute phase proteins, cytokines, and biochemical markers in diverse medical conditions. She has extensively investigated their diagnostic and prognostic value in rheumatic diseases, traumatic injuries, inflammatory disorders, and immune related pathologies. Her studies have contributed valuable insights into how inflammatory biomarkers respond to physical activity, stress, physiotherapy interventions, and complex disease states. Prof. Sobieska has also made important scientific advances in the fields of exercise immunology, rehabilitation sciences, and rheumatologic diagnostics, demonstrating how laboratory-based biomarker profiling can be integrated into personalized therapeutic strategies. Her early contributions to understanding immunological disturbances in mental health disorders and metabolic diseases have provided additional depth to her multidisciplinary approach. Her international collaborations broadened her expertise in eosinophil activation, cytokine regulation, and immune pathways that influence chronic inflammatory conditions.

Profiles:  Scopus | ORCID

Featured Publications

Pawlak-Andryszczyk, Ż., Andryszczyk, M., & Sobieska, M. Movements induced by optic flow in relation to HINE.

Bieniaszewska, A., Sobieska, M., & Gajewska, E. ,Functional and structural analysis of SITTER patients with spinal muscular atrophy.

Gajewska, E., Surowińska, J., Chałupka, A., Moczko, J., Michalak, M., & Sobieska, The qualitative motor assessment at three months allows a better prognosis than the traction test.

Christina Tassi | Mental Health Programs | Research Excellence Award

Dr. Christina Tassi | Mental Health Programs | Research Excellence Award

Postdoctoral Researcher | The University of  Ioannina | Greece

Dr. Christina Tassi is a scholar in counseling psychology whose work bridges group counseling theory, person centered facilitative conditions, and positive psychology interventions. Her research emphasizes the psychosocial development and emotional well-being of children and adolescents, with a particular focus on those facing psychological economic hardship. Through her publications and collaborative research, she has contributed valuable insights into how group processes, therapeutic factors, and supportive interpersonal climates can enhance participants’ resilience, adjustment, and overall mental health. Across 7 peer reviewed publications, Dr. Tassi’s research demonstrates methodological rigor and applied relevance, yielding a measurable scholarly impact reflected in 68 citations and an h-index of 4. Her studies explore a range of topics, including process outcome relationships in positive psychological interventions, person centered attitudes among facilitators, and the mechanisms through which group programs foster emotional growth in school-age populations. She has also examined the effectiveness of online positive psychology interventions implemented during the  pandemic, contributing early evidence on the feasibility and therapeutic value of digital group-based mental health support. Dr. Tassi has co authored a book on positive psychology and contributed chapters focusing on poverty’s psychological effects on children, strengths-based counseling, and psychoeducational interventions for youth with diverse needs. Her interdisciplinary collaborations reflect a commitment to advancing evidence-based practices in educational and therapeutic contexts.

Profile:  Scopus 

Featured Publication

Tassi, C., & Brouzos, A. Therapeutic factors in a group positive psychological intervention  for primary school students facing parental psychological economic hardship. International Journal of Applied Positive Psychology.

Zewen Zhuo | Rewards & Recognition | Excellence in Research Award

Mr. Zewen Zhuo | Rewards & Recognition | Excellence in Research Award

Engineer | The University of  Shandong Gangyuan Pipeline Logistics Co., Ltd | China

Mr. Zewen Zhuo is a researcher specializing in the rheology, microstructural behavior, and flow assurance mechanisms of waxy crude oil systems. His scholarly work focuses on understanding how wax crystallization, gel formation, and structural failure processes influence the stability and transport efficiency of crude oil in pipeline environments. Through the integration of rheology, in situ microscopy, and advanced experimental observation methods, his contributions address key scientific challenges associated with long distance crude oil transportation. With 3 published research documents, 48 citations, and a current h-index of 2, his work demonstrates measurable academic influence within the petroleum engineering and flow assurance communities. His studies provide detailed insights into the nonlinear and dynamic behavior of waxy crude oil under thermal and mechanical disturbances, offering data and models that support improved operational reliability in the oil and gas industry. One of his major contributions includes the investigation of the structural failure process of gelled waxy crude oil emulsions, using synchronous rheological and microscopic techniques to reveal how gel networks deform and break under external stress. Another publication examines shear thinning behavior and microstructural evolution in waxy crude oil, providing a clearer understanding of how shear fields disrupt wax crystal aggregates and modify flow characteristics. His additional work explores the destruction mechanisms of gel structures in emulsion systems, contributing to more accurate predictions of restart performance, wax deposition risk, and flow resistance. Across these studies, Mr. Zhuo’s research advances fundamental knowledge of wax oil interactions, microstructural dynamics, and rheological response under complex operating conditions. His contributions support the development of more efficient, safer, and scientifically grounded strategies for crude oil storage, transportation, and flow assurance technology.

Featured Publication

Zhao, J., Zhuo, Z., Dong, H., & Wang, Z. Structural failure process of gelled waxy crude oil emulsion based on rheological-in-situ microscopic synchronous measurement.

Junfeng Zhao | Learning & Development | Research Excellence Award

Prof. Junfeng Zhao | Learning & Development | Research Excellence Award

Professor | The University of Henan University | China

Prof. Junfeng Zhao is an influential researcher in psychology whose scholarship integrates educational, developmental, health, and social psychology to address learning, adaptation, and mental health among children and adolescents. Across 98 publications, with 1,349 citations and an h-index of 26, his body of work combines rigorous empirical methods, longitudinal designs, and interdisciplinary approaches to investigate resilience, peer attachment, self-esteem, and school adaptation. He emphasizes applied outcomes measurement development, intervention design, and translation to educational practice while advancing theoretical understanding of developmental processes. A major strand of his research focuses on children affected by social disadvantages such as left-behind children, and those with sensory impairments examining risk and protective factors that shape psychological outcomes. Through multi-year tracking studies and psychometric scale evaluation, he has produced validated instruments and intervention-informed findings that clarify how family dynamics, peer relationships, and school contexts contribute to mental health trajectories. This work informs community based strategies and educational policies aimed at improving psychosocial supports for vulnerable groups. In educational psychology, his studies illuminate learning motivation, cognitive styles, learning strategies, and classroom processes, offering practical implications for curriculum design and teacher training. His research addresses early identification models for learning difficulties, the neural correlates of cognitive control and the psychological underpinnings of teacher professional identity and its influence on student well being. The portfolio demonstrates a productive mix of quantitative, qualitative, and neurophysiological methods. Methodologically, Zhao emphasizes mixed methods, longitudinal analyses, culturally sensitive measurement, and robust psychometrics strengthening the reliability and applicability of findings across contexts. His publications consistently bridge theory and practice, targeting educators, clinicians, and policymakers. The cumulative impact of his research lies in deepening understanding of how developmental mechanisms interact with social environments and in providing evidence-based frameworks for interventions that promote resilience and healthy development in children and adolescents. Overall, his work offers actionable frameworks for policy and practice.

Featured Publications

Huang, G., Qian, C., Newman-Norlund, R. D., Zhao, J., & Li, X.  Perceived stigma mediates the relationship between regional gray matter volume and aggressive behavior in children affected by parental.

Ji, L., Yu, Y., Wan, J., Zhang, Y., Zhao, J., & Chen, C. Relationship between cumulative peer risk and sense of security among adolescents: A moderated mediation model. BMC Psychology.

Wan, J., Ji, L., Wang, Z., Zhao, J., & Li, X.  Social exclusion and mental health of youths affected by parental HIV/AIDS in China: Based on a serial mediating model.

Chen, C., Wu, Q., Zhao, J., Zhao, G., Li, X., Du, H., & Chi, P. Enacted stigma influences bereavement coping among children orphaned by parental. A longitudinal study with network analysis.

Wu, J., Li, Q., Chi, P., Zhao, J., & Zhao, J. Mindfulness and well-being among socioeconomically disadvantaged college students: Roles of resilience and perceived discrimination.

Bingfei Gu | Rewards & Recognition | Research Excellence Award

Prof. Dr. Bingfei Gu | Rewards & Recognition | Research Excellence Award

Professor | The University of Zhejiang Sci-Tech University | China

Prof. Dr. Bingfei Gu is a prominent researcher in the interdisciplinary domain of digital apparel engineering, computational ergonomics, and intelligent garment technologies. With a scholarly record of 81 publications, 255 citations, and an h-index of 11, the author has built a strong research presence that spans human body modeling, fabric behavior simulation, and advanced garment design systems. Their work integrates computational methods, image processing, 3D point cloud analytics, and artificial intelligence to address long-standing challenges in apparel fit, pattern generation, body measurement accuracy, and digital clothing representation. A central focus of the author’s research is the development of precise and scalable human body measurement frameworks using hybrid scanning and imaging systems. This includes advanced classification of body shape, automated feature extraction, and individualized prototype generation for apparel design. Their studies on digital garment systems explore virtual fittings, numerical simulations of fabric drape, and biomechanics-based modeling of clothing body interaction, contributing to improved prediction of wearer comfort and performance. The author has produced influential work on garment technologies, including new algorithms for pattern adaptation, topologically consistent model reconstruction, and simulation-driven design optimization. Their research in garment virtual simulation extends into computational evaluations of ergonomics, ballistic protection mechanisms, and AI driven virtual try on methods leveraging generative diffusion models. Through collaboration with multidisciplinary teams, the author has contributed to notable advancements in industrial ergonomics, textile engineering, and digital fashion innovation. Their publications in high impact journals demonstrate a commitment to methodological rigor and practical relevance, supporting the broader transition toward intelligent apparel manufacturing, personalized garment engineering, and data-driven fashion technologies. The author’s contributions continue to shape emerging standards in digital human modeling and next-generation garment simulation.

Featured Publications

Hou, J., Lu, Y., Wang, M., Ouyang, W., Yang, Y., Zou, F., Gu, B., & Liu, Z.  A Markov Chain approach for video-based virtual try-on with denoising diffusion generative adversarial network. Knowledge Based Systems.

Jin, S., & Gu,, Production scheduling optimization of shirt component module based on standard man-hour prediction.

Sheng, X., Zhao, S., & Gu, B. Construction of shirt component module groups based on process similarity

Sun, Y., Niu, W., Chen, X., Chen, Q., Gu, B., & Liu, Y. Application of human finite element model in flexible protective products. Journal of Medical Biomechanics.

Feng, H., Sheng, X., Zhang, L., Liu, Y., & Gu, B. Color analysis of brocade from the 4th to 8th centuries driven by image based matching network modeling.

Jin, S., & Gu, B. Individualized generation of women’s prototype based on the classification of body shape.

Yifei Zhang | Learning & Development | Research Excellence Award

Dr. Yifei Zhang | Learning & Development | Research Excellence Award

Professor | The University of Hebei University | China

Dr. Yifei Zhang is a developing scholar whose research contributions span metallurgical physical chemistry, advanced materials processing, non-destructive testing, and intelligent material characterization. With a growing academic profile supported by 13 research documents, 235 citations, and an h-index of 7, the author has established a strong foundation in studying material behavior, performance evolution, and diagnostics using both experimental and data-driven approaches. Their work in alloy systems, particularly titanium alloys produced through selective laser melting and other additive manufacturing pathways, has yielded influential findings regarding microstructural evolution, oxide film dynamics, and electrochemical performance. These studies have improved the understanding of how processing conditions affect long-term material stability, reliability, and corrosion behavior an area of increasing importance for aerospace, biomedical, and high-performance engineering applications. The author’s contributions extend to investigating surface modification and coating technologies, including the impact of residual stress on the adhesion behavior of thin films such as TiN coatings. Their insights into interfacial mechanics and coating performance support the broader development of durable protective layers and engineered surfaces. In parallel, the author has advanced methodological innovation in the field of non-destructive evaluation. By integrating acoustic emission analysis, variational mode decomposition, continuous wavelet transforms, and convolutional neural networks, their work enhances the accuracy of damage mode identification in complex composite structures and stainless steels. These integrated diagnostic frameworks offer improved capabilities for monitoring structural health, predicting failure, and optimizing material maintenance strategies. Collectively, the author’s research demonstrates a commitment to bridging materials science, machine learning, and modern diagnostic technologies. Their publications contribute to both theoretical understanding and practical solutions for evaluating and enhancing material performance. With a steadily increasing citation profile and a diverse research portfolio, the author continues to influence key developments in materials characterization, surface engineering, and intelligent non-destructive testing.

Featured Publication

Zhang, Y., Yao, Y., Li, J., et al. Effect of residual stress on adhesion behaviour of TiN coating. Bulletin of Materials Science.

Xu Xinsheng | Strategic HR Management | Research Excellence Award

Prof. Xu Xinsheng | Strategic HR Management | Research Excellence Award

Professor | The University of Shandong University of Aeronautics | China

Prof. Xinsheng Xu is an accomplished scholar whose research sits at the intersection of supply chain management, inventory theory, risk analytics, and quantitative optimization. With 34 academic documents, over 300 citations, and an h-index of 10, his scholarly impact is reflected in both the depth and breadth of his contributions to operations research and management science. His work advances understanding of decision-making under uncertainty, particularly focusing on how risk attitudes such as loss aversion and risk aversion shape procurement and ordering behavior. A significant portion of his research extends classical models such as the newsvendor framework, exploring new dimensions that incorporate backlogging, shortage penalties, fill rate considerations, opportunity loss, and advanced risk measures including Conditional Value-at-Risk. These models offer improved decision-support tools for retailers, suppliers, and logistics managers facing increasingly volatile market environments. Beyond behavioral decision models, his research also encompasses multi sourcing procurement, dual sourcing under emergency conditions, supply option contracts, supplier default risks, and portfolio purchasing strategies. He has developed analytical methods for optimizing procurement in hybrid sourcing systems, considering mismatch costs, spot market dynamics, emergent replenishment strategies, and utility maximizing approaches for risk-sensitive buyers. In parallel, Xinsheng Xu has made influential contributions to optimization theory, including bilevel programming, tri level supply chain models, smoothing techniques for penalty functions, and algorithmic strategies for constrained optimization. These theoretical developments are applied in multi-stage supply chain design, cooperative risk-sharing, and interaction programming problems. His work appears in respected journals such as International Journal of Production Economics, International Journal of Production Research, Annals of Operations Research, Industrial Management & Data Systems, Computers & Industrial Engineering, Mathematics, Discrete Dynamics in Nature and Society, and Numerical Functional Analysis and Optimization.

Featured Publications

Xu, X., Sang, S., & Lee, C. K. M. The optimal ordering decision of a retailer with a spot buying. International Journal of Production Research.

Xu, X., & Lee, C. K. M. Portfolio procurement with an option contract and spot market. International Journal of General Systems.

Sang, S., Xu, X., & Lee, C. K. M. A purchaser’s optimal procurement strategy under emergencies. International Journal of General Systems. Published online.

Chao-Feng Shih | Leadership Development | Best Researcher Award

Assist. Prof. Dr. Chao-Feng Shih | Leadership Development | Best Researcher Award

Assist. Prof | The University of  Central Police University | Taiwan

Dr. Chao-Feng Shih is a scholar and engineer specializing in marine engineering, maritime safety, smart port technologies, and computational mechanics. His academic background and research trajectory focus on advancing hydrodynamics, nonlinear sloshing analysis, marine risk assessment, and intelligent port-based monitoring systems. He has developed strong expertise in integrating engineering theory with modern computational tools to address complex maritime challenges and enhance operational safety in port and offshore environments. His doctoral research applied a modified Lie-Group algorithm to nonlinear sloshing problems, contributing new numerical strategies for analyzing fluid structure interactions in confined and dynamic marine systems. Dr. Shih’s broader research in nonlinear hydrodynamics includes studies on sloshing suppression using baffle designs, meshless methods for heat transfer simulation, and explicit/implicit Lie-Group numerical schemes. His work has been published in reputable indexed journals, addressing topics such as underwater vehicle acoustics, two-dimensional tank sloshing behavior, and Trefftz-based multi-scale methods. Beyond theoretical contributions, Dr. Shih’s research intersects with applied maritime safety and smart harbor development. He has played key roles in projects involving 5G-enabled port monitoring, based inspection systems, and driven maritime applications. His recent works explore remote sensing for port operations, edge-computing frameworks for drone communications, and AI-enhanced solutions for underwater environmental monitoring. These efforts highlight his commitment to integrating emerging technologies with marine engineering to support safer, more efficient, and data-driven maritime operations. His academic publications also include studies on fire prevention in cargo vessels, unmanned underwater vehicle applications, and marine safety risk assessment. Future research directions involve developing AI assisted maritime training systems, simulation-based digital twin platforms, autonomous navigation technologies, and advanced predictive models for port-level risk management. Through this multidisciplinary research portfolio, Dr. Shih continues to contribute to innovation across marine engineering, intelligent maritime systems, and computational analysis.

Featured Publications

Tan, C.-C., Shih, C.-F., Shen, J.-H., & Chen, Y.-W.  A time–space numerical procedure for solving the sideways heat conduction problem.

Chen, Y.-W., Pan, C.-C., Lin, Y.-H., Shih, C.-F., Shen, J.-H., & Chang, C.-M. Acoustic field radiation prediction and verification of underwater vehicles under a free surface. Journal of Marine Science and Engineering

Tolasa Tamasgen | HR Technology and Digital Transformation | Editorial Board Member

Assist. Prof. Dr. Tolasa Tamasgen | HR Technology and Digital Transformation | Editorial Board Member 

Course Instructor and Researcher | The University of Bonga University | Ethiopia

Dr. Tolasa Tamasgen Hirpha, is a dedicated scholar in Condensed Matter optical properties, nanostructures, and computational physics. His academic pathway includes a in Condensed Matter Physics, complemented by strong interdisciplinary grounding through master’s degrees in Physics and Project Management. His research interests bridge fundamental physics and applied materials science, with a particular emphasis on nanocomposites, thin films, electronic structure calculations, and field-enhancement phenomena. His scholarly work demonstrates strong competence in both theoretical modeling and materials characterization. Publications authored or co-authored address critical topics such as the optical and structural behavior of PbS thin films, local field enhancement mechanisms in spheroidal core-shell nanocomposites, nonlinear optical responses, and the impact of interfacial layers on enhancement factors in metal–dielectric systems. He has also contributed to computational investigations of bulk and monolayer using Density Functional Theory, reflecting his ability to apply modern simulation tools to explore electronic and optical properties. Additional interdisciplinary research includes fault-tolerant control systems for electrical machines, highlighting versatility beyond physics-focused domains. Proficient he integrates computational analysis with high-quality scientific documentation. His research strengths include data interpretation, modeling, simulation, and the dissemination of findings through peer-reviewed publications and scientific presentations. His academic foundation and research record demonstrate a continuous commitment to advancing materials science, physics-based modeling, and interdisciplinary scientific inquiry. He remains strongly interested in further integrating project management principles into scientific research methodologies to enhance applied outcomes and broaden the real-world impact of theoretical concepts.

Featured Publications

Hirpha, T. T., Gurmesa, G. S., Ali, B. M., & Aga, G. S. Investigation of the electronic and optical properties of bulk and monolayer AlxGa(1−x)N structure using density functional theory.

Chehhat, A., Chouchane, N., Si-Ameur, M., Rebai, B., Larguech, S., Hirpha, T. T., & Menni, Y. Investigation of compressible internal flow mechanisms and thermofluid interactions in centrifugal compressors through advanced hub-to-shroud computational fluid dynamics for diesel engine turbocharger performance.

Bellali, B., Makhloufi, S., Belbekri, T., Alkhafaji, M. A., Hirpha, T. T., Bousserhane, I. K., & Menni, Y. Active fault-tolerant control for asynchronous machines using EKF-based fault estimation and 3-H-bridge inverter mitigation of ITSCs.

Hirpha, T. T., Bergaga, G. D., Ali, B. M., & Gebre, S. S. Investigation of optical bistability in spheroidal core–shell nanocomposites with passive and active dielectric cores.

Hirpha, T. T., Bergaga, G. D., Ali, B. M., & Gebre, S. S.  Local field enhancement factor of spheroidal core–shell nanocomposites with passive and active dielectric cores.