Jean-Philippe Valois | Computer Science | Young Scientist Award

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Mr. Jean-Philippe Valois | Computer Science | Young Scientist Award

Universite de Lille | France

Jean-Philippe Valois is a Ph.D. candidate in Computer Science and Applications at the MADIS Graduate School in Lille, with a long-term academic objective of becoming a Lecturer (Maître de Conférences) in Computer Science, specializing in scientific computing, optimization, and high-performance computing. He holds a Master’s degree in Scientific Computing and a Bachelor’s degree in Mathematics, and has a strong background in numerical methods for ordinary and partial differential equations, numerical analysis, linear algebra, modeling, fluid mechanics, optimization, algorithm design, and operations research. His technical expertise includes parallel metaheuristics, genetic algorithms, machine learning, quantum computing, and hybrid parallel programming (MPI+X), with proficiency in C, C++, MATLAB, and Python, as well as OpenMP, MPI, CUDA, and large-scale computing infrastructures such as Grid’5000 and MesoNET. His doctoral research focuses on “Massively Parallel Exact Optimization for Qubit Allocation in Quantum Systems,” addressing scalable algorithms for emerging quantum architectures. He completed a research internship at Inria within the RAPSODI team, working on 3D population dynamics modeling and the numerical solution of partial differential equations using finite difference and finite volume methods, alongside seasonal professional experience in an agricultural cooperative. He has authored one scientific document, received one citation, and currently reports an h-index of 1 and an i10-index of 0, reflecting the early but promising stage of his research career in computational science and high-performance computing.

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Featured Publications

Efficient and Scalable Branch-and-Bound Algorithm for Exact Qubit Allocation
– JP Valois, G Helbecque, N Melab, Future Generation Computer Systems, Article 108342, 2025

A Parallel Island Genetic Algorithm for Triangle-based Image Reconstruction
– JP Valois, T Firmin, N Melab, ACS/IEEE International Conference on Computer Systems and Applications, 2025

Eshref Trushin | Economics of Innovation and New Technology | Research Excellence Award

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Dr. Eshref Trushin | Economics of Innovation and New Technology | Research Excellence Award

Leicester Castle Business School | United Kingdom

Dr Eshref Trushin is a Senior Lecturer in Economics at Leicester Castle Business School, De Montfort University, Economics of Innovation and New Technology and an accomplished scholar with a distinguished international academic and professional profile. He holds a PhD from Queen Mary University of London, an MA from Duke University in the United States, and an MSc (Research) in Economics and Finance from the London School of Economics and Political Science. His co-authored research has been published in Research Policy, a Financial Times top fifty journal, and he has presented his work at major international academic forums including the Royal Economic Society, BAFA, ISPOR, and RADMA, earning three Best Paper Awards. Over his academic career, Dr Trushin has taught eighteen courses across six British universities and is a Fellow of the UK Higher Education Academy. He has received seven competitive research grants from leading bodies such as the British Academy, ESRC, and the Royal Economic Society. His citation impact includes an h-index of nine, over four hundred citations, and more than thirty indexed documents on Google Scholar. Formerly Chief Economist at BearingPoint Consulting, he led economic reform research influencing national regulations, consulted for World Bank Development Economics on WTO accession and FDI barriers, authored a book on East Asian economic development, and now leads interdisciplinary research on ESG, sustainable development, CO₂ emissions, and the economic and policy impacts of artificial intelligence.

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Featured Publications

R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis

M. Ugur, E. Trushin, E. Solomon – Research Policy, Vol. 45(10), pp. 2069–2086, 2016 · Citations: 172
Inverted-U relationship between R&D intensity and survival: Evidence on scale and complementarity effects in UK data

M. Ugur, E. Trushin, E. Solomon – Research Policy, Vol. 45(7), pp. 1474–1492, 2016 · Citations: 102
Basic Problems of Market Transition in Central Asia

E. Trushin – Central Asia and the New Global Economy: Critical Problems, Critical Choices, 2019 · Citations: 18
Uzbekistan: problems of development and reform in the agrarian sector

E. Trushin – Central Asia, pp. 259–291, 2017 · Citations: 16
A firm-level dataset for analyzing entry, exit, employment and R&D expenditures in the UK: 1997–2012

M. Ugur, E. Trushin, E. Solomon – Data in Brief, Vol. 8, pp. 153–157

Gharieb El-Sayyad | Immunology and Microbiology | Best Researcher Award

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Assoc. Prof. Dr. Gharieb El-Sayyad | Immunology and Microbiology | Best Researcher Award

Imam Mohammed Ibn Saud Islamic University Deanship of Scientific Research | Saudi Arabia

Gharieb S. El-Sayyad is an Egyptian academic and researcher serving as an Associate Professor at Badr University in Cairo, affiliated with departments spanning microbiology, biotechnology, and nanotechnology. He works extensively in fields such as medical microbiology, nanomaterials, antimicrobial and anticancer applications of nanoparticles, and biotechnology, collaborating with multiple universities and research centers including the Egyptian Atomic Energy Authority and several Egyptian universities. According to his Google Scholar profile, he has a substantial academic impact with approximately 7940 citations and an h-index of around 48, reflecting significant influence across his research publications . His body of work includes hundreds of research documents on topics such as synthesis and characterization of nanocomposites, antimicrobial and anticancer activities of novel materials, and optimization of enzyme and nanoparticle processes, demonstrating multidisciplinary contributions to both fundamental science and applied technologies . El-Sayyad’s research outputs are published in a variety of international journals and often involve collaborative investigations into nanomaterials for biomedical and environmental applications. His scholarship reflects a strong record of citations and influence, underscoring his role as a productive and impactful researcher in his fields of expertise

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Featured Publications

Antimicrobial activity of metal-substituted cobalt ferrite nanoparticles synthesized by sol–gel technique
– AH Ashour, AI El-Batal, MIAA Maksoud, GS El-Sayyad, S Labib, Particuology, 40, 141–151

Therapeutic and diagnostic potential of nanomaterials for enhanced biomedical applications
– MA Elkodous, GS El-Sayyad, IY Abdelrahman, HS El Bastawisy, Colloids and Surfaces B: Biointerfaces, 180, 411–428

Antibacterial, antibiofilm, and photocatalytic activities of metals-substituted spinel cobalt ferrite nanoparticles
– MIAA Maksoud, GS El-Sayyad, AH Ashour, AI El-Batal, MA Elsayed, Microbial Pathogenesis, 127, 144–158

Response Surface Methodology Optimization of Mono-dispersed MgO Nanoparticles Fabricated by Ultrasonic-Assisted Sol–Gel Method
– CW Wong, YS Chan, J Jeevanandam, K Pal, M Bechelany, Journal of Cluster Science, 31, 367–389

Biomolecules-mediated synthesis of selenium nanoparticles using Aspergillus oryzae fermented Lupin extract and gamma radiation
– FM Mosallam, GS El-Sayyad, RM Fathy, AI El-Batal, Microbial Pathogenesis, 122, 108–116

Njemuwa Nwaji | Chemistry and Materials Science | Research Excellence Distinction Award

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Assist. Prof. Dr. Njemuwa Nwaji | Chemistry and Materials Science | Research Excellence Distinction Award

Institute of Fundamental Techmological Research, Polish Academy of Science | Poland

The research focuses on nanotechnology-driven solutions for energy storage, energy conversion, and advanced functional materials. Core expertise lies in the rational synthesis of novel nanostructured materials with tailored physicochemical properties for next-generation electronic and energy applications. Significant contributions have been made in the development of advanced nanomaterials for photo- and electrocatalysis, particularly targeting efficient hydrogen production through water splitting by optimizing catalyst composition, morphology, and interfacial charge-transfer processes. Another major research direction involves energy storage systems, with an emphasis on designing high-performance electrode materials for supercapacitors using diverse synthetic strategies to achieve enhanced capacitance, stability, and rate capability. In addition, research extends into biocompatible nanomaterials, including hydrogel- and fiber-based systems for biomedical applications such as controlled drug delivery and self-powered implantable devices. The work integrates materials chemistry, nanofabrication, and electrochemical characterization to address critical challenges in sustainable energy technologies. Collaborative and interdisciplinary research efforts have resulted in impactful publications and the supervision of graduate-level research projects in nanomaterials synthesis, catalysis, and energy-related applications, contributing to advancements in clean energy and functional nanomaterials research.

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Yvonne Brunetto | Organizational Justice | Research Excellence Award

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Prof. Dr. Yvonne Brunetto | Organizational Justice | Research Excellence Award

Southern Cross University | Australia

Yvonne Brunetto is a Professor of Management and Human Resource Management at Southern Cross University, where she works in the School of Business and Tourism. She earned her PhD in Management and has devoted her career to researching the individual and organisational determinants of employee performance, commitment, wellbeing and resilience across public and private sectors — including nurses, police officers, engineers and other professional workers in multiple countries. Her scholarship is extensive and impactful: she has published around 100 journal articles (with roughly 90 since 2011), and her work has been widely cited; according to a recent profile she has a Google Scholar h-index of 37. Her research spans emotional labour, psychological capital, leadership, supervisor–subordinate relationships, organisational commitment, workplace well-being, employee retention and safety across sectors such as healthcare, policing and public administration in countries including Australia, UK, Italy, USA, Malta and Brazil. ANZAM+2Cambridge University Press & Assessment+2 She has not only contributed to empirical research (for example, showing how supervisor–subordinate relationships and psychological capital influence police officers’ training satisfaction and commitment) but has also translated academic findings into practical interventions — delivering resilience leadership and emotional well-being/psychological-capital training to middle managers in health and government sectors, with measurable improvements in employee outcomes.

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Aayushi Rastogi | Non-communicable diseases | Young Scientist Award

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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

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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

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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

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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

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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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