Hamada Zahera | Computer Science | Best Researcher Award

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Dr. Hamada Zahera | Computer Science | Best Researcher Award

Postdoctoral Researcher | Paderborn University | Germany

Hamada Zahera is a PhD candidate at Paderborn University in Germany, specializing in data science, semantic computing, machine learning, and natural language processing. His research primarily focuses on social media analysis for enhancing situational awareness during crises, as well as semantic web technologies and knowledge graph representations. With international experience at leading institutions, he has contributed to multiple projects in semantic computing, ontology generation, knowledge graph summarization, and deep learning applications for disaster management. His academic journey has taken him from undergraduate and master’s studies in computer science at Menoufia University, Egypt, to advanced doctoral research in Germany under the supervision of Prof. Axel Ngonga. Zahera has published extensively in high-impact venues, including ISWC, ESWC, K-CAP, and IEEE Access, and has been an active contributor to the academic community as a reviewer for top conferences. His work bridges machine learning, semantic web, and data-driven crisis intelligence.

Profile

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Education

Hamada Zahera is a PhD candidate at Paderborn University in Germany, specializing in data science, semantic computing, machine learning, and natural language processing. His research primarily focuses on social media analysis for enhancing situational awareness during crises, as well as semantic web technologies and knowledge graph representations. With international experience at leading institutions, he has contributed to multiple projects in semantic computing, ontology generation, knowledge graph summarization, and deep learning applications for disaster management. His academic journey has taken him from undergraduate and master’s studies in computer science at Menoufia University, Egypt, to advanced doctoral research in Germany under the supervision of Prof. Axel Ngonga. Zahera has published extensively in high-impact venues, including ISWC, ESWC, K-CAP, and IEEE Access, and has been an active contributor to the academic community as a reviewer for top conferences. His work bridges machine learning, semantic web, and data-driven crisis intelligence.

Professional Experience

Hamada Zahera obtained his Bachelor of Science in Computer Science from Menoufia University, Egypt, where he excelled academically and graduated at the top of his class with honors. During his undergraduate studies, he built strong foundations in mathematics, probability, data structures, distributed systems, and programming. He continued at Menoufia University for his Master of Science in Computer Science, conducting research on improving search engine results using quality-based methods under the supervision of Prof. Arabi Keshk. His master’s studies provided him with in-depth knowledge in machine learning, data mining, parallel computing, and high-performance systems. Building on this foundation, Zahera pursued doctoral studies at Paderborn University in Germany, joining the Data Science Group (DICE) under the supervision of Prof. Axel Ngonga. His PhD research centers on social media data analysis, situational awareness, and semantic web approaches. This academic journey reflects his consistent pursuit of excellence and strong interdisciplinary expertise.

Awards and Honors

Throughout his academic and professional career, Hamada Zahera has been recognized with several honors and awards that reflect his research excellence and innovative contributions. He was awarded a prestigious DAAD Scholarship to fully fund his doctoral studies at Paderborn University, highlighting his academic merit and potential. His team secured second place in the TREC Incident Stream challenge for categorizing disaster-related tweets into fine-grained types, showcasing his expertise in applying machine learning to crisis informatics. Earlier in his career, he was recognized with Ericsson’s Best Innovation Project Award for his graduation project, the Idrisian Navigation System, presented at IEEE EED. He also received the Graduation Distinction Award for ranking first in his undergraduate class in computer science at Menoufia University. Beyond awards, he has served as a reviewer for leading conferences such as NeurIPS, ICLR, ACL Rolling Review, and ESWC, demonstrating his role in advancing global research communities.

Research Focus

Hamada Zahera’s research focuses on the intersection of machine learning, natural language processing, and the semantic web, with a particular emphasis on knowledge graphs and crisis informatics. His doctoral research investigates methods for analyzing social media content to improve situational awareness during crises, enabling more effective event detection, prediction, and actionable information extraction. He has developed approaches for ontology generation from structured data, entity typing, and knowledge graph summarization, combining symbolic and neural methods to enhance semantic computing. His work integrates language models with graph-based techniques to advance keyphrase extraction, ontology alignment, and disaster tweet classification. A consistent theme in his research is leveraging heterogeneous data sources, including social media and environmental data, for real-world applications such as disaster response and crisis management. By bridging semantic technologies and deep learning, his research contributes to scalable, interpretable, and impactful solutions for data-driven decision-making and knowledge representation.

Publication

Title: ANTS: Abstractive Entity Summarization in Knowledge Graphs
Year: 2025

Title: UniQ-Gen: Unified Query Generation Across Multiple Knowledge Graphs
Year: 2025

Title: Enhancing Answers Verbalization Using Large Language Models
Year: 2024

Title: Generating SPARQL from Natural Language Using Chain-of-Thoughts Prompting
Year: 2024

Title: Universal Knowledge Graph Embeddings
Year: 2024

Conclusion

Hamada Zahera is highly suitable for a research award given his strong academic record, impactful contributions to semantic web and crisis informatics, international research exposure, and competitive achievements. With continued focus on interdisciplinary applications, greater industry collaboration, and leadership roles, his profile will become even stronger for prestigious global research honors.

Mudassir Shams | Mathematics | Best Researcher Award

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Assist. Prof. Dr. Mudassir Shams | Mathematics | Best Researcher Award

Assistant Professor | Balikesir University | Turkey

Assist. Prof. Dr. Mudassir Shams is a distinguished mathematician and academic whose career reflects excellence in teaching, research, and innovation in computational mathematics and numerical analysis. He currently serves as an Assistant Professor at Balikesir University, Turkey, and has held significant academic and research roles at Riphah International University, Pakistan, and the Free University of Bozen-Bolzano, Italy. His expertise lies in developing advanced numerical schemes for solving nonlinear equations, fractional systems, fuzzy models, and scientific computing problems. With a prolific record of more than sixty-eight research publications including peer-reviewed articles, book chapters, and an authored book, Dr. Shams has contributed to advancing modern applied mathematics in engineering, computational sciences, and physics-related applications. His academic journey demonstrates a commitment to interdisciplinary approaches, combining theory and applied problem-solving to address real-world challenges. As a mentor and researcher, he continues to push boundaries of mathematical innovation while actively engaging in international collaborations and scholarly contributions.

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Education

Assist. Prof. Dr. Mudassir Shams has pursued an extensive academic path with multiple degrees across mathematics, economics, and education. He completed a Postdoctoral Fellowship in Mathematics with specialization in Numerical Analysis at the Free University of Bozen-Bolzano, where he conducted advanced research on high-performance numerical solvers for engineering and thermonuclear applications. He earned a PhD in Mathematics from Riphah International University, Pakistan, with a perfect CGPA, focusing on computational mathematics and iterative methods for nonlinear equations. Prior to this, he completed an MPhil in Mathematics with distinction and a Gold Medal in Numerical Analysis from the same institution. He further holds master’s degrees in Mathematics, Economics, and Science Education, along with a Bachelor of Science in Mathematics and Physics. Additionally, he obtained a Bachelor of Education and a Postgraduate Diploma in advanced mathematics. His education demonstrates a multidisciplinary blend of mathematical rigor, computational theory, and applied problem-solving across diverse domains.

Professional Experience

Assist. Prof. Dr. Mudassir Shams has built a strong academic and research career through international teaching and research appointments. He currently serves as an Assistant Professor in the Department of Mathematics at Balikesir University, Turkey, where he teaches advanced courses in mathematics and supervises research projects. Previously, he worked as Assistant Professor and Senior Lecturer at Riphah International University, Islamabad, where he contributed extensively to curriculum design, research mentoring, and administrative responsibilities such as examination supervision and program coordination. He also served as a Postdoctoral Research Assistant at the Faculty of Engineering, Free University of Bozen-Bolzano, Italy, contributing to high-level projects in computational mathematics and numerical solvers for engineering applications. His experience spans more than a decade of teaching, research supervision, and scholarly publishing. He has participated in international projects, delivered workshops, and engaged in collaborative studies with scholars worldwide, reflecting his ability to combine academic leadership with innovative mathematical research.

Awards and Honors

Assist. Prof. Dr. Mudassir Shams has received numerous awards and distinctions recognizing his academic and research excellence. He was honored with a prestigious Gold Medal in his MPhil in Mathematics for achieving outstanding performance in Numerical Analysis. His consistent academic excellence is further reflected in his perfect CGPA scores during advanced studies. He has been recognized internationally for his research contributions with publications in highly ranked journals, earning him visibility within the global scientific community. His invited book chapters published by renowned publishers such as Elsevier and Springer demonstrate his recognition as an authority in computational mathematics. His postdoctoral research at the Free University of Bozen-Bolzano was awarded under supervision of esteemed scholars, further highlighting his role as a researcher of global standing. Through his innovative research in numerical schemes and fractional systems, Dr. Shams has earned professional acclaim, citations, and acknowledgment as a leading contributor in the field of applied mathematics.

Research Focus 

Assist. Prof. Dr. Mudassir Shams’ research focuses on computational mathematics, numerical analysis, and the development of efficient algorithms for solving complex mathematical models arising in engineering and applied sciences. His work emphasizes the construction and analysis of numerical schemes for nonlinear equations, iterative methods, fuzzy differential equations, fractional differential equations, boundary value problems, and integral equations. He has advanced the study of fractional iterative methods and q-numerical schemes, providing theoretical insights and practical tools for engineering problem-solving. His research also extends to the dynamical analysis of iterative methods and real and complex dynamics of nonlinear systems, offering contributions to stability and convergence studies. With applications spanning physics, engineering, and computational sciences, his projects include semi-analytical techniques and numerical linear algebra methods to optimize scientific computing. His interdisciplinary research integrates mathematical rigor with practical applications, supporting innovation in high-performance computing and advanced engineering models, making significant contributions to global mathematical sciences.

Publications

Artificial Neural Network-Based Single-Step Method for Solving Biomedical Engineering Application
Year: 2025

On Hybrid Parallel Scheme for Biomedical Engineering Problems
Year: 2025

Chaos-Enhanced Fractional-Order Iterative Methods for the Stable and Efficient Solution of Nonlinear Engineering Problems
Year: 2025

Chaos in Inverse Parallel Schemes for Solving Nonlinear Engineering Models
Year: 2024

Triangular intuitionistic fuzzy linear system of equations with applications: an analytical approach
Year: 2024

Conclusion

Assist. Prof. Dr. Shams’s research contributions demonstrate a rare combination of mathematical depth and engineering applicability, positioning him as a strong candidate for recognition and awards in computational mathematics, applied numerical methods, and biomedical engineering applications. His innovative work not only advances mathematical theory but also provides computationally efficient solutions for complex engineering and biomedical problems, underscoring his potential for continued impact in the scientific community.

Susanne Neufang | Medical Data Science | Best Researcher Award

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Dr. Susanne Neufang | Medical Data Science | Best Researcher Award

Principal Investigator | Insitute of Biomedical Informatics, University of Cologne | Germany

Susanne Neufang is a data scientist and neuroscientist with extensive expertise in developmental cognitive neuroscience, neuroimaging, psychiatry, and medical data science, combining her background in psychology, brain development, and computational approaches to explore normal and pathological mechanisms of executive functions, attention, and psychiatric disorders, and more recently advancing into biomedical informatics and artificial intelligence with a strong focus on fairness, explainability, and deep learning for clinical applications, contributing to high-impact international collaborations such as PRONIA and ENIGMA and producing more than fifty publications, numerous grants, and recognition through prestigious awards, while also developing and leading interdisciplinary research groups bridging neuroscience and data science to translate neurobiological findings into innovative diagnostic and therapeutic tools, thereby positioning herself at the interface of neuroscience, medicine, and machine learning, with a research career that spans multiple universities and international institutions and continues to evolve within biomedical informatics and applied AI.

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Education

Susanne Neufang pursued undergraduate studies in psychology at the Technical University Berlin, enriched her academic foundation with an exchange at Universidad Complutense de Madrid, and completed graduate studies at the University of Bonn where she earned her M.A. in psychology with highest distinction, followed by doctoral training at Ruhr-University Bochum where she investigated gender-specific development of brain anatomy and attention functions and was awarded a Ph.D. with magna cum laude, she then advanced to habilitation at Julius-Maximilians-University Würzburg with a thesis on the normal and pathological development of executive functions across the lifespan, earning the title Privatdozentin, and later complemented her neuroscience expertise with advanced training in data science at Sorbonne Université in collaboration with Datascientest, where she acquired modern analytical and machine learning skills including deep learning, explainable AI, fairness in AI, and multimodal data analysis, building a unique interdisciplinary education profile combining psychology, neuroscience, medicine, and data science.

Professional Experience

Her professional career spans diverse roles including graduate and doctoral researcher at the Research Center Jülich and RWTH Aachen, international research training at the Sackler Institute New York, and postdoctoral appointments at Charité Berlin and Technical University Munich where she worked on developmental cognitive neuroscience and neuroimaging, before leading research groups at Würzburg and Düsseldorf focusing on developmental neuroimaging, biological mechanisms of psychiatric transitions, and neurodiagnostics, in which she combined advanced MRI and genetic data to study psychiatric disorders, while contributing to European research consortia and clinical trials, she later transitioned to the University of Cologne as a data scientist at the Institute for Biomedical Informatics, where she applies modern machine learning techniques to multimodal biomedical data, developing explainable, fair, and clinically robust AI models for psychiatry and cognitive neuroscience, thus integrating her long-standing expertise in brain research with cutting-edge data science and artificial intelligence applications for medical research.

Awards and Honors

Throughout her career Susanne Neufang has been recognized with multiple awards and scholarships reflecting both academic excellence and innovative research contributions, including a European mobility scholarship supporting her academic year in Madrid, a DAAD fellowship enabling her research at the Sackler Institute in New York, and a research fellowship from the Parmenides Foundation in Germany supporting her postdoctoral work, her scientific achievements were further honored with the August-Homburger Award for Young Scientists acknowledging her contributions to developmental neuroscience and psychiatry, in addition she secured multiple competitive national and international research grants from organizations such as the DFG, IZKF, and collaborative research centers, supporting high-impact projects on anxiety, depression, schizophrenia, genetics, and neuroimaging, her ability to attract funding and recognition underlines her standing as an innovative researcher at the crossroads of neuroscience and data science, with a strong track record of excellence and international scientific impact.

Research Focus 

Her research centers on understanding the neurobiological and computational mechanisms underlying normal and pathological brain development, executive functions, attention, and psychiatric disorders such as ADHD, anxiety, depression, schizophrenia, and borderline personality disorder, integrating multimodal data sources including MRI, clinical, genetic, and socio-epidemiological datasets, she applies advanced machine learning, deep learning, and explainable AI methods to identify biomarkers, develop predictive models, and design fair and interpretable diagnostic tools for precision psychiatry, with emphasis on gender fairness, bias reduction, and robust clinical translation, her focus spans from fundamental cognitive neuroscience to applied biomedical informatics, linking brain connectivity, genetics, and behavior with computational approaches, and contributing to large-scale collaborations like PRONIA and ENIGMA to achieve reproducible and generalizable findings, by bridging neuroscience and artificial intelligence her work aims to advance early detection, prognosis, and individualized treatment strategies for mental health disorders, fostering integration of neuroimaging, genomics, and clinical data into next-generation medical AI.

Publication

Title: EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning
Year: 2025

Title: Theta burst stimulation add on to dialectical behavioral therapy in borderline-personality-disorder: methods and design of a randomized, single-blind, placebo-controlled pilot trial
Year: 2024

Title: Serotonergic modulation of normal and abnormal brain dynamics: The genetic influence of the TPH2 G-703T genotype and DNA methylation on wavelet variance in children and adolescents with and without ADHD
Year: 2023

Title: Brain-Based Classification of Youth with Anxiety Disorders: an ENIGMA-ANXIETY Transdiagnostic Examination using Machine Learning
Year: 2022

Title: Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages
Year: 2022

Conclusion

Susanne Neufang is highly suitable for recognition in research awards. Her rare combination of neuroscience expertise and advanced AI skills positions her at the forefront of precision psychiatry and biomedical data science. With continued emphasis on translational application and academic visibility, she will likely make even greater contributions to the field. Her career trajectory, international collaborations, and innovative focus make her a strong and deserving candidate for prestigious research awards.

 

Elmira Mohandesan | Ancient DNA | Best Researcher Award

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Dr. Elmira Mohandesan | Ancient DNA | Best Researcher Award

Senior Scientist | University of Veterinary Medicine Vienna | Austria

Elmira Mohandesan is a Senior Scientist and Head of the Genetics Lab at the University of Veterinary Medicine Vienna, specializing in population genomics, phylogenetics, and animal domestication with a strong focus on ancient DNA research across diverse taxa including primates, carnivores, reptiles, and ungulates, she has established herself as an international expert leading pioneering projects that combine molecular biology, bioinformatics, archaeology, and evolutionary genetics to reveal long-term genetic changes, domestication processes, and human-animal interactions, as principal investigator she directs multiple research initiatives supported by the Austrian Science Fund and has contributed extensively to advancing understanding of equine palaeogenomics, camelid evolution, and human migration, in addition to her research she leads a genetics laboratory where she advises scientists, supervises doctoral candidates, teaches graduate courses, and fosters interdisciplinary collaborations across Europe, New Zealand, and beyond, her career reflects a consistent dedication to advancing scientific knowledge in evolutionary biology and ancient genomics.

Profile

Scopus

Education

Elmira Mohandesan holds a PhD in Molecular Evolution and Genetics from Massey University in New Zealand where she focused on evolutionary genomics and developed expertise in molecular biology and statistical genetics, prior to that she completed a Master of Science in Molecular Genetics at Tarbiat Modarres University in Tehran where she concentrated on genetic analysis and laboratory-based research on DNA and molecular markers, she began her academic path with a Bachelor of Science in Zoology from Shahid Beheshti University in Tehran where she built a foundation in animal biology, evolutionary theory, and population studies, across her academic training she gained extensive laboratory skills in molecular methods, developed strong analytical capacities in bioinformatics, and expanded her research scope to integrate evolutionary biology, conservation genetics, and ancient DNA, her education provided a multidisciplinary grounding that enabled her to move seamlessly into postdoctoral research and later into leadership roles in palaeogenomics and population genetics.

Professional Experience

Elmira Mohandesan is Principal Investigator at the University of Vienna where she leads research in evolutionary anthropology and palaeogenomics while also heading the Genetics Lab at the University of Veterinary Medicine Vienna, her previous appointments include postdoctoral research positions at the University of Vienna in molecular evolution and cognitive biology, and at the University of Veterinary Medicine in population genetics and wildlife ecology where she worked with leading experts in evolutionary genetics, she also gained research experience at the Max Planck Institute for Evolutionary Anthropology in Leipzig focusing on ancient DNA methodologies and comparative genomics, her teaching career began as a teaching assistant at Massey University where she taught evolutionary biology and genetics, across these roles she has consistently combined molecular techniques with evolutionary theory, successfully managed international collaborations, supervised doctoral students, and contributed to advancing genomic research on species domestication, ancient population structures, and conservation biology.

Awards and Honors

Elmira Mohandesan has been recognized with several prestigious awards and honors throughout her academic career including first prize in the Life Science Photo Contest “Pictures of the Life Sciences” at the University of Vienna for her striking image capturing feral horses in the wild, earlier she received the first prize in the Design and Journalistic Award at the University of Veterinary Medicine Vienna for outstanding science communication, during her doctoral studies she was awarded the Allan Wilson Institute Doctoral Scholarship at Massey University as well as a PhD Completion Scholarship from the Institute of Molecular Biosciences, she also received travel awards to participate in advanced statistical genetics training in Seattle and scholarships from the Max Planck Institute for research in evolutionary anthropology, her academic achievements began with ranking third in the Iranian national examination for the Master of Science in Genetics and graduating with honors for academic excellence in zoology.

Research Focus 

Elmira Mohandesan’s research focuses on population genomics, phylogenetics, and animal domestication with an emphasis on ancient DNA analysis to trace genetic changes over time and reconstruct evolutionary histories, she applies a multidisciplinary approach integrating molecular biology, archaeology, morphology, and computational genomics to explore how domestication, hybridization, and migration have shaped animal and human populations, her work spans diverse taxa including primates, carnivores, reptiles, and ungulates with significant contributions to the understanding of camelid evolution, tuatara divergence, cave bear genetics, and particularly equine palaeogenomics where she has revealed insights into Roman breeding practices and the origins of feral horse populations in New Zealand, she also investigates ancient human migrations in Central Europe, in her lab she develops genomic tools, evaluates methodologies for species identification, and guides collaborative projects, her research ultimately seeks to advance evolutionary theory while contributing practical knowledge for conservation, domestication studies, and interdisciplinary archaeological genetics.

Publication

Title: Late Iron Age and Roman equine breeding north of the Alps: Genetic insights and cultural implications
Year: 2025

Title: Unraveling Genome- and Immunome-wide Genetic Diversity in Jaguars (Panthera onca): Implications for Targeted Conservation
Year: 2024

Title: Predictive use of modern reference osteological collections for disentangling the shape of Eurasian equid cheek teeth and metapodials in archaeological material
Year: 2023

Title: Reconstruction of the Major Maternal and Paternal Lineages in the Feral New Zealand Kaimanawa Horses
Year: 2022

Title: Genomic signatures of domestication in Old World camels
Year: 2020

Conclusion

Elmira Mohandesan is highly suitable for a “Distinguished Researcher Award in Evolutionary Genomics and Ancient DNA Studies.” Her pioneering work, outstanding academic achievements, and commitment to interdisciplinary science make her an exceptional candidate whose contributions continue to shape the understanding of animal domestication, ancient human migrations, and evolutionary processes.

 

Jasmine Ahmed | Marketing | Young Researcher Award

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Dr. Jasmine Ahmed | Marketing | Young Researcher Award

Lecturer in Marketing | Lancaster University | United Kingdom

Jasmine Mohsen is a Lecturer in Marketing Analytics at SP Jain School of Management, UK, and a Research Project Supervisor at Glasgow Caledonian University, with prior experience as a Postdoctoral Researcher at the University of Namur and Research Fellow at Brunel University London. She earned her PhD in Marketing from Leeds University Business School, where her doctoral thesis examined how perceived luxury shields brands from cancellation movements. Her research and teaching expertise span consumer psychology, branding, sustainability, and marketing communication, with publications in reputable journals such as the Journal of Research in Interactive Marketing and Technological Forecasting & Social Change. Beyond academia, she has contributed to UK-funded projects on food waste reduction, sustainability, and digital health adoption, collaborating with interdisciplinary teams to generate policy and industry-relevant insights. She also plays an active role as a reviewer for leading journals and conferences, reinforcing her academic citizenship and commitment to advancing knowledge in marketing.

Profile

Scopus

Education

Jasmine Mohsen completed her PhD in Marketing at Leeds University Business School with a fully funded scholarship, focusing on consumer behaviour, branding, and cancellation movements under the supervision of an experienced academic panel. Prior to her doctoral studies, she obtained an MSc in Business Administration with a concentration in Marketing from Cairo University, a rigorous programme that combined taught modules in research methodology, marketing theory, and business statistics with a substantial thesis exploring the antecedents and consequences of adolescent materialism in Egypt. She previously graduated with distinction in a Bachelor of Commerce with Honours in Business Administration from Cairo University, consistently ranking at the top of her class with comprehensive training in management, marketing, and business policy. She also pursued a Foundation Certificate in Accounting and Finance at the American University in Cairo, building strong competencies in financial and managerial accounting, corporate finance, and related analytical skills.

Professional Experience

Jasmine Mohsen has extensive academic and research experience across leading institutions. She is currently a Lecturer in Marketing Analytics at SP Jain School of Management and a Research Project Supervisor at Glasgow Caledonian University, supporting MSc students and serving on ethics committees. Previously, she worked as a Postdoctoral Researcher at the University of Namur, leading qualitative projects on moral misalignment and workplace inclusion, and as a Research Fellow at Brunel University London on sustainability and digital health initiatives. At Leeds University Business School, she held roles as Research Assistant, Associate Faculty, and Data Analysis Tutor, contributing to high-impact projects on consumer behaviour, food waste, and sustainability. Her early career includes academic teaching at Cairo University, the American University in Cairo, and collaborative teaching with Georgia State University. She has consistently integrated her research expertise with teaching, supervising dissertations, developing curricula, and delivering both undergraduate and postgraduate modules in marketing and business.

Awards and Honors

Jasmine Mohsen has received multiple awards and recognitions for her academic achievements and research impact. She was nominated for the Sustainability Award by Leeds University Business School in recognition of her contributions to sustainability-focused research, particularly through publications addressing consumer behaviour and pro-environmental messaging. She received research funding to complete the Advanced Quantitative Methods module at the University of Oxford, strengthening her methodological expertise. Her academic excellence has been recognised with a Certificate of Appreciation for graduating with first-class honours as the top student in her department at Cairo University, along with awards for outstanding performance and contribution as a teaching assistant. She also earned the Carbon Literacy Certificate from a UK-based programme focused on climate awareness and sustainable practices, underscoring her commitment to sustainability. Earlier in her career, she was honoured for consistent academic excellence and commitment to education, receiving recognition from both faculty and departmental leadership.

Research Focus 

Jasmine Mohsen’s research focuses on consumer psychology and behaviour, exploring how individuals respond to branding, marketing communication, and evolving marketplace norms. She investigates themes such as brand resilience, cancellation movements, persuasive messaging, and consumer resistance, with a strong interest in understanding the psychological drivers behind shopping reduction campaigns and sustainability behaviours. Her work also contributes to food waste reduction, the circular economy, and pro-environmental consumer choices, drawing on both qualitative and quantitative approaches. She has collaborated on several UK-funded projects addressing food waste, citizen science engagement, and digital health platform adoption, generating practical insights for policymakers and industry stakeholders. In addition to her completed work, she has developed working papers targeting high-ranking journals, addressing topics such as symbolic self-branding, gendered work narratives, and consumer attitudes toward national startups. Her interdisciplinary and policy-relevant approach ensures that her research advances theory while offering actionable implications for marketing practice and sustainability transitions.

Publication

Title: Impact of E-Waste Regulations on Firms’ R&D and Marketing Expenditures: Insights for a Circular Economy
Year: 2025

Title: Enhancing resilience to negative information in consumer–brand interaction: the mediating role of brand knowledge and involvement
Year: 2021

Title: Shop smarter, not harder: How gentle messaging can help the planet more than tough talk
Year: 2025

Title: From Swipe Fatigue to Shared Tables: The Psychology Behind Dining with Strangers
Year: 2025

Title: How citizen science can benefit research in tackling societal problems
Year: 2023

Title: Why We Buy, Why We Waste: Fixing Tech’s Sustainability Problem
Year: 2025

Title: A story of perseverance: How a failed study led me to a breakthrough in sustainable shopping research
Year: 2025

Conclusion

Jasmine Mohsen’s research trajectory is marked by intellectual curiosity, societal relevance, and academic excellence. Her strengths in addressing contemporary issues such as cancel culture, consumer resilience, and sustainability make her an emerging scholar with strong potential for long-term impact. With further consolidation of her international publication profile and leadership in large-scale funded projects, she is exceptionally well-positioned to be recognized with a prestigious research award.

 

Jasmine Mohsen | Business | Women Researcher Award

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Dr. Jasmine Mohsen | Business | Women Researcher Award

Assistant Professor and Research Project Supervisor | SP Jain School of Management and GCU | United Kingdom

Dr. Jasmine Mohsen is a Lecturer in Marketing Analytics at SP Jain School of Management, UK, and Research Project Supervisor at Glasgow Caledonian University. She earned her PhD in Marketing from Leeds University Business School and previously held academic positions at Brunel University London, University of Namur in Belgium, and Cairo University. Her academic career combines teaching, research, and consultancy, with a strong focus on consumer psychology, brand resilience, persuasive messaging, and sustainability in marketing. She has contributed to projects funded by UK research councils on digital health adoption, food waste management, and net zero initiatives. Her work has been published in leading academic journals and shared through invited blogs, media outlets, and industry collaborations. She actively serves as a reviewer for high-impact journals and conferences and integrates research insights into teaching, supervision, and curriculum development, shaping the next generation of marketing professionals.

Profile

Orcid

Education

Jasmine completed her PhD in Marketing at Leeds University Business School, where her doctoral thesis examined how perceived luxury helps brands withstand cancellation movements. She also earned an MSc in Business Administration (Marketing) from Cairo University, focusing her research on adolescents’ materialism and its consequences. Her undergraduate studies in Business Administration at Cairo University resulted in graduating with top honours, providing her with strong foundations in management, marketing, finance, and organizational behaviour. She further expanded her academic profile with a foundation certificate in accounting and finance from the American University in Cairo, achieving high distinction. She completed advanced training in research design, data analysis, and quantitative methods, including specialized coursework at Oxford University. Her educational journey reflects a strong balance of theory, research methodology, and applied business knowledge, equipping her with the expertise to lead impactful research and deliver innovative teaching in marketing and consumer behaviour.

Professional Experience

Jasmine has developed an international academic career across the UK, Belgium, and Egypt, combining teaching, research, and consultancy. She currently lectures in marketing analytics at SP Jain School of Management and supervises postgraduate dissertations at Glasgow Caledonian University. She has previously been a postdoctoral researcher at the University of Namur, focusing on moral misalignment in institutions and workplace inclusion, and a research fellow at Brunel University London, contributing to projects on digital health platforms and sustainability transitions. At Leeds University Business School, she worked extensively on projects related to food waste reduction, citizen science, and consumer sustainability behaviours while also serving as a tutor and associate faculty member. She has held assistant lecturer roles at Cairo University and taught in joint international programs with Georgia State University, delivering courses in marketing, finance, and management. Her career demonstrates a consistent integration of academic rigour, practical application, and student-focused teaching.

Awards and Honors

Jasmine has been recognised with multiple awards and honours that highlight her excellence in research, teaching, and academic impact. She was nominated for a sustainability research award in recognition of her contributions to consumer behaviour and environmental studies, particularly through publications and outreach in media platforms. She secured institutional funding to pursue advanced quantitative training at Oxford, strengthening her methodological expertise. She also earned a carbon literacy certification, reflecting her dedication to sustainable practices in both research and teaching. Earlier in her career, she received recognition from Cairo University for her outstanding teaching efforts and her consistent academic excellence. She graduated with top honours, earning a first-place distinction in her cohort, and received several certificates of appreciation for her academic achievements. These awards and honours illustrate a consistent record of dedication, innovation, and leadership in marketing research and education, reinforcing her standing as a rising scholar and impactful educator.

Research Focus 

Jasmine’s research is situated at the intersection of consumer psychology, branding, and sustainability. She investigates how consumers respond to branding and marketing communication under evolving social and cultural norms, with particular emphasis on brand resilience, cancellation movements, persuasive messaging, and psychological drivers of consumption reduction. Another core strand of her work explores sustainability in consumer markets, including food waste reduction, circular economy transitions, and the role of marketing in promoting pro-environmental behaviour. She adopts both qualitative and quantitative approaches, ranging from interviews and thematic analysis to experimental design and advanced statistical modelling. Her publications have appeared in respected journals, and she has several ongoing working papers targeting high-ranking academic outlets. Beyond academic publishing, she engages with wider audiences through blogs, media contributions, and consultancy collaborations. Her research is designed to advance theory, inform practice, and influence policy, bridging the gap between academic insights and real-world impact.

Publication

Title: Shop smarter, not harder. How gentle messaging can help the planet more than tough talk
Year: 2025

Title: Don’t Tell Me What To Do: How Different Messaging Strategies In Shopping Reduction Campaigns Trigger Psychological Reactance Among Consumers
Year: 2025

Title: Don’t Cancel Me: Investigating How Perceived Luxury Safeguards Brands from Cancellation Movements
Year: 2025

Title: How citizen science can benefit research in tackling societal problems
Year: 2023

Title: A Qualitative Comparative Analysis of The Antecedents of Adolescents Materialism
Year: 2022

Title: The Diffusion of “Cancel Culture” After the Post-lockdown Period
Year: 2022

Conclusion

Jasmine Mohsen’s contributions highlight her as a promising and innovative researcher whose work is both academically rigorous and socially relevant. Her ability to connect marketing theory with pressing real-world issues makes her a strong candidate for a Best Researcher award. With continued focus on top-tier publications, methodological robustness, and global collaboration, she has the potential to emerge as a leading figure in marketing and consumer research.

Faisal Alshami | Federated Learning | Best Researcher Award

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Mr. Faisal Alshami | Federated Learning | Best Researcher Award

PhD | Dalian University to Technology | China

Faisal Alshami is a scholar in Software Engineering with a strong focus on distributed systems, federated learning, and edge computing. He brings extensive experience in full-stack development, software architecture, and mission-critical systems integration, combining academic research with professional expertise. His work spans blockchain, graph neural networks, and natural language processing, aiming to design resilient, scalable, and intelligent software solutions for aerospace, automation, and advanced computing applications. With a background that bridges multiple cultures and academic systems, he has developed a versatile research outlook and problem-solving approach. His profile reflects a balance of deep technical knowledge, collaborative teamwork, and innovative thinking, enabling him to address complex technological challenges. Recognized through research publications and professional training, Faisal continues to advance intelligent software design and secure distributed systems. His biography reflects a commitment to leveraging computer science for global technological progress and interdisciplinary innovation across academia and industry.

Profile

 Google scholar

Education

Faisal Alshami has built a comprehensive academic foundation in Software Engineering, progressing through undergraduate, graduate, and doctoral studies across multiple institutions and international contexts. His early education emphasized network technology and computer security, where he explored system design and secure communication protocols, laying the groundwork for a strong technical base. At the graduate level, he advanced into software engineering with a thesis on intelligent recommendation systems, applying deep learning methods such as convolutional neural networks, bidirectional models, and word embeddings. His doctoral research expands this expertise to federated learning, distributed systems, edge computing, blockchain integration, graph-based machine learning, and natural language processing. Alongside formal education, he has strengthened his skills through specialized certifications in deep learning, computer networking, software development, and multiple languages, ensuring adaptability across research and industry environments. His academic path demonstrates a consistent focus on scalable, secure, and intelligent systems development supported by both theoretical and applied learning.

Professional Experience

Faisal Alshami has accumulated professional and research experience across software engineering, system architecture, networking, and communication technologies. He has worked on mission-critical systems as a full-stack developer and DevOps lead, where he focused on real-time performance, scalability, automation, and secure system integration. His role as a systems engineer allowed him to design and deploy reliable network solutions, implement advanced routing and switching protocols, and conduct rigorous performance testing. In communication services, he specialized in VoIP systems and application programming interfaces, contributing to optimization and debugging of large-scale infrastructures. His industry-linked training enriched his expertise in software frameworks, enterprise application development, and collaborative project execution, where he applied principles of Java-based platforms, modern web development, and mobile solutions. His combined academic and industry background reflects versatility in both theoretical exploration and practical system implementation, highlighting a career path centered on building secure, scalable, and intelligent solutions that address real-world challenges.

Awards and Honors

Faisal Alshami has earned recognition through certifications, training, and publications that reflect his academic and professional accomplishments. He completed advanced certification in neural networks and deep learning, enhancing his ability to apply artificial intelligence in research and applied domains. His language achievements demonstrate cross-cultural adaptability and communication strength, while professional networking certifications highlight his technical proficiency in system design and management. He has been recognized through participation in academic projects, industry collaborations, and training programs that strengthened his expertise in software frameworks and enterprise solutions. His research contributions have been published in highly regarded journals and conferences, underscoring the impact of his work in distributed systems, federated learning, and intelligent computing. The combination of scholarly recognition, professional certifications, and successful project outcomes positions him as a researcher and engineer who consistently seeks excellence, innovation, and international collaboration in advancing the field of software and systems engineering.

Research Focus 

Faisal Alshami’s research is centered on distributed computing, federated learning, and edge intelligence, with emphasis on building secure, scalable, and resource-efficient systems. His work addresses the challenges of communication efficiency, convergence acceleration, and reliability in decentralized learning environments. He integrates blockchain for secure multi-agent collaboration, graph neural networks for enhanced decision-making, and natural language processing for intelligent human–machine interaction. His research extends to mission-critical applications such as aerospace and space exploration, where intelligent payload software and secure satellite communication are key challenges. He also investigates simulation and testing frameworks for embedded and real-time systems, ensuring resilience and dependability under constrained environments. His broader interests include combining artificial intelligence with blockchain to strengthen data privacy and system robustness. Through his research, he aims to bridge academic innovation with industrial application, producing frameworks and algorithms that advance next-generation computing systems while contributing to global technological development and interdisciplinary collaboration.

Publication

  1. Title: Errors-Guided Reasoning: Enhanced Framework for Mathematical Reasoning and Multi-Incorrect Feedback in LLM
    Year: 2025

  2. Title: SCDFL: A Spectral Clustering-Based Framework for Accelerating Convergence in Decentralized Federated Learning
    Year: 2025

  3. Title: Enhancing Communication Efficiency in Decentralized Federated Learning via Pruning
    Year: 2024

  4. Title: A Detailed Analysis of Benchmark Datasets for Network Intrusion Detection System
    Year: 2021

  5. Title: Intrusion Detection Model for Imbalanced Dataset using SMOTE and Random Forest Algorithm
    Year: 2021

Conclusion

In conclusion, Dr. Faisal Alshami exemplifies the qualities of a forward-looking researcher whose work bridges academic theory and applied innovation. His combination of strong research output, technical expertise, and interdisciplinary vision makes him an excellent candidate for the Best Researcher Award. With continued global collaboration and expanded leadership in research initiatives, he has the potential to emerge as a leading figure in the advancement of distributed computing and intelligent software systems.

Han-Ning Dai | Atomic | Best Researcher Award

Published on by Popular Scientist

Prof. Dr. Han-Ning Dai | Atomic | Best Researcher Award 

Researcher | University of Science and Technology of China | China

Prof. Dr. Han-Ning Dai is a leading physicist specializing in quantum physics, quantum information, and atomic, molecular, and optical (AMO) physics. He serves as a professor at major quantum research institutions and has extensive experience in both theoretical and experimental physics. His research focuses on quantum simulation, quantum metrology, ultracold atoms, optical lattice clocks, and ultrastable laser systems. He has published in high-impact journals including Nature Physics, Physical Review Letters, Science, and Optica, and has led multiple large-scale national and international research projects. Recognized for his innovative contributions, he has received several prestigious awards and research fellowships. His work bridges fundamental quantum science with practical technology applications, contributing significantly to advancements in precision measurement and quantum information processing. Through his leadership and collaborations, he continues to influence the global quantum research community and shape the future of next-generation quantum technologies.

Profile

Orcid

Education

Prof. Dr. Han-Ning Dai earned his Bachelor of Science and Doctor of Philosophy degrees in Physics from a top national science and technology university. His academic training combined theoretical studies in quantum mechanics and atomic physics with experimental expertise in ultracold atoms, optical lattices, and laser systems. His doctoral research focused on quantum information processing with cold atoms, advancing techniques for quantum simulation and precision measurement. His studies included rigorous training in experimental design, laser frequency stabilization, vacuum systems, and quantum state manipulation. He gained substantial experience in developing and integrating advanced quantum optics tools, enabling high-precision control of atomic systems for fundamental physics research. His academic background provided a solid platform for international collaborations and postdoctoral research in leading quantum physics laboratories abroad, positioning him to lead cutting-edge research projects in quantum science and contribute to the development of next-generation quantum technologies.

Professional Experience

Prof. Dr. Han-Ning Dai has held key academic and research positions at leading institutions in the field of quantum science. His early postdoctoral work at an internationally recognized physics institute in Europe involved advanced experiments in ultracold atomic systems and quantum many-body physics. He subsequently returned to his home country to assume professorial positions at top research universities and national laboratories, where he leads experimental quantum optics and ultracold atom research groups. His responsibilities include directing large-scale research projects, supervising graduate and doctoral students, publishing in leading peer-reviewed journals, and fostering international collaborations. He has been actively involved in national strategic programs in quantum technology, contributing to the development of optical lattice clocks, ultrastable lasers, and quantum simulation platforms. His career demonstrates a strong balance between cutting-edge laboratory experimentation, high-level academic teaching, and leadership in both national and global scientific communities focused on advancing quantum technology.

Awards and Recognition

Prof. Dr. Han-Ning Dai has been recognized with multiple awards for his contributions to quantum physics and technology. His achievements include national and regional talent awards that acknowledge both research excellence and leadership in scientific innovation. He has also received competitive fellowships supporting high-impact research in quantum information science and experimental quantum optics. In addition to formal honors, he has been entrusted with leadership roles in major research projects funded by national science foundations, ministries, and municipal innovation programs. These awards and appointments highlight his outstanding capabilities in developing advanced quantum experiments, building interdisciplinary research teams, and contributing to the strategic advancement of quantum technologies. His consistent recognition by scientific and governmental organizations underscores his status as a leading figure in experimental quantum science and his ability to translate fundamental discoveries into impactful technological advancements.

Research Focus 

Prof. Dr. Han-Ning Dai’s research integrates quantum physics, quantum information science, and AMO physics with a focus on precision experimental systems. His work encompasses quantum simulation of many-body systems, advanced quantum metrology, and manipulation of ultracold atoms for both fundamental and applied studies. He is engaged in the development of optical lattice clocks with exceptional stability, ultrastable laser systems for high-precision measurement, and engineered quantum states for enhanced metrology and information processing. His research also explores synthetic quantum systems, topological phases, and emergent phenomena in quantum matter. By combining advanced laser stabilization, vacuum engineering, and coherent control techniques, his work pushes the limits of precision measurement and quantum control. His contributions support both fundamental scientific exploration and the creation of enabling technologies for future quantum communication, computation, and navigation systems, reinforcing his role in shaping the trajectory of global quantum science and technology.

Publication

1. Title : Staggered-immersion cooling of a quantum gas in optical lattices

     Year : 2019

2. Title : High-contrast transparency comb of the electromagnetically-induced-transparency memory

    Year : 2018

3. Title : Four-body ring-exchange interactions and anyonic statistics within a minimal toric-code Hamiltonian

    Year : 2017

4. Title : Quantum criticality and the Tomonaga-Luttinger liquid in one-dimensional Bose gases

    Year : 2017

5. Title : Spin-dependent optical superlattice

   Year : 2017

Conclusion

Dr. Han-Ning Dai stands out as a leading experimental quantum physicist whose work has significantly advanced ultracold atom research, precision optical clocks, and quantum simulation. His track record of innovation, coupled with high-profile publications and institutional leadership, makes him a compelling candidate for the Best Researcher Award. Continued efforts to expand global collaborations, strengthen translational research pathways, and raise his international visibility would further solidify his standing as one of the foremost researchers in his discipline.

Guiting Song | Oceanography | Best Researcher Award

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Prof. Guiting Song | Oceanography | Best Researcher Award

Professor at Sun Yat-Sen University, China

Guiting Song is a tenured professor and Ph.D. supervisor at Sun Yat-sen University, where he leads the Smart Marine Meteorology Team. He holds dual Ph.D. degrees in Meteorology (University of Hamburg, Germany) and Physical Oceanography (Institute of Oceanology, Chinese Academy of Sciences), as well as an MBA from the University of Birmingham, UK.

Profile:

Educational Background:

Dr. Song earned a PhD in Meteorology from the University of Hamburg, Germany, and another PhD in Physical Oceanography from the Institute of Oceanology, Chinese Academy of Sciences. He also holds a Master’s in Business Administration (MBA) from the University of Birmingham, UK, and a Bachelor’s degree in Meteorology from the Ocean University of China.

Professional Experience:

He is currently a Tenured Professor and Ph.D. Supervisor at Sun Yat-sen University, where he founded the Smart Marine Meteorology Team and developed precision marine weather forecasting, navigation, and renewable energy meteorology products. His career includes leadership roles in Beijing Xinzhi Technology Co., Ltd. and Envision Digital in Singapore, as well as research positions with the Meteorological Service of Singapore, Terra Weather, the University of Guanajuato in Mexico, and Nanyang Technological University. His expertise covers smart meteorology, power forecasting, marine navigation, climate change research, and coupled ocean–atmosphere modeling.

Awards and Recognition:

Dr. Song has received multiple national and international awards, including innovation and entrepreneurship honors, national-level talent recognition, overseas talent program awards, and product excellence accolades in smart meteorology.

Research and Projects:

He has led and contributed to numerous projects in smart marine weather navigation, renewable energy forecasting, climate change modeling, and hydropower prediction. His collaborations span global institutions such as NCAR, UK Met Office, IBM TWC, and the Hong Kong Observatory.

Publications and Patents:

Dr. Song is the author of a substantial body of scientific publications in high-impact journals covering meteorology, oceanography, renewable energy forecasting, and climate systems. He holds several international patents related to wind speed forecasting, WRF model optimization, and meteorological model enhancements.

Publication:

  • Validation of the medium-range and sub-seasonal forecast of solar irradiance and wind speed using ECMWF

Lacrimioara Grama | Social Robotics | Best Researcher Award

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Assoc. Prof. Dr. Lacrimioara Grama | Social Robotics | Best Researcher Award

Technical University of Cluj-Napoca, Romania

Lăcrimioara-Romana Grama is an Associate Professor at the Technical University of Cluj-Napoca, Faculty of Electronics, Telecommunications and Information Technology, within the Basis of Electronics Department. She holds a PhD in Electronic Engineering and Telecommunications, with expertise in digital signal processing, data modeling, and electronic systems.

Profile:

Educational Background:

She holds a PhD in Electronic Engineering and Telecommunications, awarded Magna Cum Laude. Additionally, she completed an MSc in Design Techniques for Complex Electronic Circuits and an Engineer Diploma in Communications. She has also obtained certifications in pedagogy and academic leadership from institutions such as Harvard Graduate School of Education, Babson College, and University POLITEHNICA of Bucharest.

Leadership and Administrative Roles:

Grama currently serves as Vice-Dean and President of the Faculty Scholarship Committee. She has coordinated master-level admissions, represented her faculty in various university-wide and European initiatives (including EUt+ and RO European Universities), and contributed to numerous accreditation processes for academic programs.

Scientific and Academic Contributions:

She has actively participated in organizing international conferences such as RTSP, SpeD, and SPAMEC, often as a technical chair. Her roles also include session chair and technical program committee member for major conferences like IEEE ICIIP, EUSIPCO, and VisionNet.

Community and Institutional Engagement:

Beyond teaching and research, she has shown a strong commitment to community-building within the academic ecosystem through student mentorship, promotion of study programs, coordination of Erasmus students, and sustained involvement in faculty governance.

Google Scholar Citation Metrics:

  • Total citations: 452

  • Citations since 2020: 251

  • h-index: 11

  • h-index since 2020: 9

  • i10-index: 15

  • i10-index since 2020: 8

Publication Top Notes:

Audio signal classification using linear predictive coding and random forests
2017
34

On the optimization of SVM kernel parameters for improving audio classification accuracy
2017
31

Supercapacitor modelling using experimental measurements
2009
25

Adding audio capabilities to TIAGo service robot
2018
23

A novel wearable foot and ankle monitoring system for the assessment of gait biomechanics
2020
22

Extending assisted audio capabilities of TIAGo service robot
2019
18