Aayushi Rastogi | Non-communicable diseases | Young Scientist Award

Ms. Aayushi Rastogi | Non-communicable diseases | Young Scientist Award

Institute of Liver and Biliary Sciences | India

Aayushi Rastogi is a public-health researcher specializing in liver-disease epidemiology, with a strong focus on diabetes-associated liver conditions, screening models, and health-systems strengthening. Her work integrates epidemiologic methods with primary-care program implementation to advance early detection and management of liver fibrosis. She has contributed to more than 30 peer-reviewed publications and has played key roles in protocol development, study coordination, quantitative analysis, and manuscript preparation. Her doctoral research examined the prevalence and predictors of liver fibrosis among individuals with diabetes, generating evidence highly relevant for community-based screening initiatives. A major contribution of her work is the development of a practical, low-resource fibrosis-risk score tailored for primary-care settings. This tool uses minimal clinical and laboratory parameters to stratify risk and guide referral pathways, thereby enhancing accessibility of liver-disease assessment at the frontline level. She has also contributed to health-systems research, capacity-building programs, and CSR-supported public-health initiatives, including screening, tele-mentoring, and community engagement projects. With expertise in epidemiologic design, STATA-based data analysis, and implementation research, her work advances evidence-based strategies for early detection, risk stratification, and strengthening of liver-health services, ultimately supporting improved care models for populations at risk of chronic liver disease.

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Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Fujian Maternity and Children Health Hospital | China 

The researcher holds advanced training in computer science with a strong specialization in artificial intelligence and machine learning, Computer Science and Artificial Intelligence particularly in efficient attention mechanisms and multimodal large models for medical and healthcare applications. Current research focuses on the development of intelligent systems for placental pathology analysis, automated diagnostic report generation, and AI-assisted clinical decision support. Major contributions include the construction of annotated medical image databases, AI-guided lesion standardization frameworks, and the application of dynamic intelligent models to support maternal health interventions. The research portfolio also extends to large-scale data management, privacy protection, and secure data sharing technologies for auditory and visual cognitive models, as well as knowledge graph representation and swarm intelligence collaboration. In addition to academic research, the work includes close collaboration with industry partners to develop domain-specific large models for gynecologic oncology and multimodal AI systems for placental pathology diagnosis. Scholarly contributions span high-impact peer-reviewed journals in artificial intelligence, medical informatics, data science, and interdisciplinary computational research. The researcher has also contributed to the academic community through service on program committees for leading international conferences in artificial intelligence, computer vision, and data analytics. Overall, the research demonstrates strong innovation, translational impact, and commitment to advancing AI-driven healthcare technologies.

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Featured Publications

Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone
A. Rampun, L. Zheng, P. Malcolm, B. Tiddeman, R. Zwiggelaar – Physics in Medicine & Biology, 61(13), 4796, 2016

Self-adjusting harmony search-based feature selection
L. Zheng, R. Diao, Q. Shen – Soft Computing, 19(6), 1567–1579, 2015

Feature grouping and selection: A graph-based approach
L. Zheng, F. Chao, N. Mac Parthaláin, D. Zhang, Q. Shen – Information Sciences, 546, 1256–1272, 2021

Boundary-aware network with two-stage partial decoders for salient object detection in remote sensing images
Q. Zheng, L. Zheng, Y. Bai, H. Liu, J. Deng, Y. Li – IEEE Transactions on Geoscience and Remote Sensing, 61, 1–13, 2023

A distributed joint extraction framework for sedimentological entities and relations with federated learning
T. Wang, L. Zheng, H. Lv, C. Zhou, Y. Shen, Q. Qiu, Y. Li, P. Li, G. Wang – Expert Systems with Applications, 213, 119216

Hamasa Ebadi | AI in Medical Diagnostics | Innovator of the Year Achievement Award

Ms. Hamasa Ebadi | AI in Medical Diagnostics | Innovator of the Year Achievement Award

NeuroFore | United States

Hamasa Ebadi is an innovator working at the convergence of neuroscience, artificial intelligence, and clinical translation, with research focused on transforming the early detection of neurodegenerative disorders. Her work centers on the development of an original, first of its kind algorithm designed to identify Parkinson’s disease during its earliest, non motor stages, long before conventional clinical diagnosis is possible. The research integrates computational neuroscience, advanced pattern recognition, and clinically relevant symptom domains to uncover subtle disease signals that are often overlooked in traditional diagnostic frameworks. Unlike existing approaches that depend on late stage motor symptoms or invasive biomarkers, her work emphasizes non invasive, ethically grounded, and patient centered detection strategies. A defining strength of this research is its translational orientation, with algorithms engineered for scalability and seamless integration into real world clinical workflows. The work is guided by a strong neuroethical foundation, ensuring that early diagnosis supports safe, proactive, and beneficial intervention pathways rather than reactive treatment after disease progression. Through the translation of this research into an applied artificial intelligence platform, her contributions have the potential to reshape how clinicians, health systems, and researchers approach early neurological risk assessment. This body of work represents a significant advancement in predictive neurology and demonstrates how interdisciplinary research can redefine standards of care in neurodegenerative disease detection.

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Alina Esterhuizen |  Neurogenetics | Research Excellence Award

Assoc. Prof. Dr. Alina Esterhuizen |  Neurogenetics | Research Excellence Award

UCT/NHLS | South Africa

A translational research program focused on molecular human genetics integrates advanced diagnostics with applied research to improve clinical care in resource-constrained settings. Research centers on the genetics of neurodevelopmental and neurodegenerative disorders, with particular emphasis on paediatric epilepsies and neuromuscular diseases. Major projects have investigated the genetic causes of complex childhood epilepsies in South Africa, contributing to precision management strategies and locally appropriate genetic testing pathways. This work has generated translatable outputs, including evidence-based testing strategies for early-onset epilepsy, decision trees for specialist referral, and improved diagnostic approaches for Duchenne muscular dystrophy aligned with emerging gene-based therapies. Research activities also include innovation and development of new molecular methods and protocols for clinical implementation, bridging discovery and diagnostic practice. Methodologies span next-generation sequencing, chromosomal microarray analysis, MLPA, triplet repeat testing, and variant interpretation frameworks tailored to diverse populations. Funded projects have supported the expansion of locally relevant genetic services and the study of founder and population-specific variants. Collectively, the research emphasizes capacity building, equitable access to genetic diagnosis, and the translation of genomic advances into sustainable clinical services, with a strong commitment to improving outcomes for patients with rare and complex genetic disorders across Africa.

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Hongbin Yan | Applied Soft Computing | Research Excellence Award

Prof. Hongbin Yan | Applied Soft Computing | Research Excellence Award

School of Business, East China University of Science and Technology | China 

He is a senior scholar in management science and engineering with extensive experience in research, teaching, and academic leadership at a leading research university. His academic background spans management, knowledge science, and information systems, providing a strong interdisciplinary foundation for both theoretical and applied research. His work primarily focuses on uncertain decision analysis, evaluation methodologies, and the integration of qualitative and quantitative approaches in management research. A significant portion of his research addresses technological innovation, new product development, service management, and quality management under uncertain and dynamic environments. He has made notable contributions to kansei engineering, computing with words, and consumer-oriented evaluation models, particularly in the context of product design, customer satisfaction, and innovation decision support. His research emphasizes the use of consumer demand, online reviews, and design thinking to support technological recombination and innovation strategies. As a principal investigator on multiple competitive research projects supported by major national and regional funding agencies, he has advanced methodological frameworks that bridge theory and real-world managerial practice. In teaching, he actively contributes to undergraduate, graduate, doctoral, and professional education, with a strong emphasis on research methodology, information systems, and managerial decision making.

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Lie Deng | Oncology | Outstanding Contribution Award

Mr.  Lie Deng | Oncology | Outstanding Contribution Award

Foshan institution of pathogenic microorganism | China

This academic summary highlights advanced expertise in medical research design, Oncology statistical analysis, biochemical and molecular biology techniques, cell culture methodologies, and bioinformatics, with a strong focus on respiratory syncytial virus research. The work emphasizes the development and optimization of molecular and immunological assays to support vaccine evaluation and translational research. Robust reverse transcription quantitative polymerase chain reaction and antibody enzyme linked immunosorbent assay methods were established to assess viral load and immune responses, providing reliable alternatives to commercially available detection systems while improving laboratory efficiency and accessibility. Comprehensive research efforts also include critical analysis of global vaccine development strategies, encompassing diverse technical routes such as live attenuated vaccines, subunit vaccines, vector based platforms, and nucleic acid approaches. These contributions integrate experimental data with comparative evaluation frameworks, offering valuable insights into vaccine design, efficacy assessment, and methodological standardization. In addition, the preparation of detailed molecular biology operation guidelines strengthened laboratory practices and ensured reproducibility of experimental workflows. Training activities focused on molecular cloning, polymerase chain reaction based assays, and data validation principles, supporting the development of independent experimental competence and high quality data generation. Overall, this body of work demonstrates a strong integration of experimental innovation, methodological rigor, and knowledge dissemination, contributing meaningfully to vaccine research, laboratory capacity building, and the advancement of evidence based evaluation methods in virology and immunological studies.

Profile: ORCID

Featured Publications 

Deng, L., Cao, H., Li, G., Zhou, K., Fu, Z., Zhong, J., Wang, Z., & Yang, X. (2025). Progress on respiratory syncytial virus vaccine development and evaluation methods. Vaccines, 13(3), 304.

Haili Xia | Dynamic General Equilibrium Theory | Research Excellence Award

Dr. Haili Xia | Dynamic General Equilibrium Theory | Research Excellence Award 

Jiangsu Ocean University | China

Haili Xia is an economist specializing in teaching and research in western economics and international trade, with a strong academic focus on theoretical and applied economic analysis. His scholarly work emphasizes dynamic general equilibrium frameworks to understand trade mechanisms, policy impacts, and structural changes in open economies. A significant component of his research explores international trade dynamics under globalization, including trade efficiency, market integration, and policy coordination. In recent years, his academic interests have expanded toward the green low carbon transition, where he examines the economic implications of sustainable development, environmental regulation, and carbon reduction strategies within international and domestic economic systems. His research integrates macroeconomic modeling with real world policy analysis, contributing to evidence based insights on economic transformation and sustainable growth. His academic contributions have been recognized through publications in leading Chinese social science citation journals, reflecting both methodological rigor and policy relevance. He has also been actively involved in major humanities and social sciences research initiatives supported by national and provincial level funding, demonstrating engagement with collaborative and policy oriented research projects. His academic background in public finance further strengthens his interdisciplinary approach, linking fiscal policy, trade structures, and sustainable economic development within a comprehensive analytical framework.

Profile: ORCID 

Featured Publications 

Xia, H., Chi, Y., & Zhou, W. (2025). How income inequality shapes demand-induced clean innovation and the transition to clean technology. Sustainability, 18(1), 239.

Selda Coşkuner Aktaş | Family science | Research Excellence Award

Assoc. Prof. Dr. Selda Coşkuner Aktaş | Family science | Research Excellence Award

Hacettepe University | Turkey

Selda Coşkuner Aktaş is an accomplished academic in the field of family and consumer sciences with a strong interdisciplinary Family science background spanning sociology, business administration, and home economics. Her academic training culminated in doctoral research that examined work–family conflict, focusing on how work and family characteristics shape marital, family, and overall life satisfaction among faculty members. At the master’s level, her research explored organizational commitment, particularly among housekeeping employees, highlighting issues of motivation, loyalty, and workplace dynamics. Her scholarly interests center on work–family balance, family well-being, organizational behavior, consumer studies, and social aspects of employment and family life. Throughout her academic career, she has contributed extensively to teaching, research, and academic service within higher education, progressing from research-focused roles to senior faculty positions. She has also gained international research experience in family and youth development, strengthening her comparative and cross-cultural perspective. In addition to her teaching and research activities, she has played an active role in academic publishing, serving as an associate editor and as a member of an editorial board for peer-reviewed journals. Her work reflects a sustained commitment to advancing knowledge on the interaction between work, family systems, and social well-being, with both theoretical and applied relevance.

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Chengjun Li | Repair of musculoskeletal system injuries | Research Excellence Award

Dr. Chengjun Li | Repair of musculoskeletal system injuries | Research Excellence Award

Xiangya Hospital, Central South University | China

The researcher is a clinician scientist trained through an integrated medical and surgical academic pathway, Repair of musculoskeletal system injuries with strong expertise in regenerative medicine, orthopaedic surgery, and neurorestorative science. Academic training and research have been conducted at leading medical institutions, with a focus on translational approaches that bridge basic science and clinical application. Research interests center on tissue engineering, musculoskeletal regeneration, neural repair, and mechanisms of organ injury and aging. Significant work has been devoted to studying biomaterials, stem cell based therapies, and regenerative strategies for bone, cartilage, and nerve repair, aiming to improve functional recovery following trauma and degenerative disease. The researcher has actively contributed to laboratory based and clinical studies under the mentorship of internationally recognized experts, demonstrating independence in experimental design, data interpretation, and scholarly communication. Professional experience includes postdoctoral research and clinical practice in a high volume hospital environment, enabling the integration of innovative therapies into patient care. Scholarly contributions have been recognized through multiple competitive academic honors and scholarships. Active participation in international scientific conferences, including oral presentations, reflects strong engagement with the global research community and a commitment to advancing regenerative medicine and surgical innovation through interdisciplinary collaboration.

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Xiaoqi Liu | Bromine-based flow battery | Research Excellence Award

Assoc. Prof. Dr. Xiaoqi Liu | Bromine-based flow battery | Research Excellence Award

Taiyuan University of Science and Technology | China 

The scholar is an academic researcher in chemical engineering and Bromine-based flow battery materials science with a strong foundation in electrochemical energy storage technologies. Academic training in materials science and engineering provided a solid basis for advanced research in functional materials and electrochemical systems. Doctoral research conducted at a leading national research institute focused on iron-based flow battery systems, emphasizing electrolyte design, redox reaction mechanisms, and performance optimization for large-scale energy storage applications. Currently engaged in teaching and research at a university-level chemical engineering institution, the researcher’s work integrates electrochemistry, materials engineering, and energy technology. Research interests include redox flow batteries, iron-based energy storage systems, electrode material modification, electrolyte stability, and scalable energy storage solutions for renewable energy integration. The researcher has actively participated in multiple provincially supported research and innovation programs, contributing to fundamental and applied studies aimed at improving battery efficiency, durability, and cost-effectiveness. Ongoing projects emphasize sustainable energy storage materials, system optimization, and technological innovation aligned with clean energy and low-carbon development goals. Through a combination of experimental research and applied engineering approaches, the scholar contributes to advancing next-generation electrochemical energy storage technologies with potential industrial and environmental impact.

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