Fatema Safri | Heapatology and Oncology | Best Researcher Award

Published on by Physics and Quantum Physics

Best Researcher Award

Fatema Safri
Affiliation Westmead Institute for Medical Research
Country Australia
Scopus ID 58944753700
Documents 6
Citations 146
h-index 2
Subject Area Hepatology and Oncology
Event International Physics and Quantum Physics Awards

Fatema Safri is affiliated with the Westmead Institute for Medical Research, Australia, and has contributed to scholarly investigations within hepatology and oncology. Her research activities focus on understanding disease mechanisms, clinical outcomes, and evidence-based healthcare approaches. Through peer-reviewed publications and collaborative scientific efforts, her work contributes to ongoing developments in biomedical research and patient-centered healthcare studies.[1]

Abstract

This academic profile summarizes the scholarly contributions of Fatema Safri in the fields of hepatology and oncology. The profile highlights publication activity, citation metrics, research influence, and scientific contributions relevant to biomedical research. The overview is intended to provide an objective assessment of research achievements and academic impact based on publicly available scholarly indicators.[1]

Keywords

Hepatology, Oncology, Medical Research, Clinical Studies, Biomedical Science, Cancer Research, Liver Disease Research, Healthcare Innovation, Translational Medicine, Academic Publications.

Introduction

Research in hepatology and oncology contributes significantly to the understanding, diagnosis, treatment, and prevention of complex diseases. Scientific investigations in these disciplines support advancements in clinical practice and healthcare outcomes. Fatema Safri’s academic work forms part of this broader research landscape through studies that contribute to evidence-based medical knowledge and patient care strategies.[2]

Research Profile

The available bibliometric indicators reflect participation in peer-reviewed research and collaborative scientific studies. These metrics provide insight into publication visibility and scholarly engagement within the research community.[1]

Research Contributions

  • Participation in hepatology-related clinical and translational research.
  • Contributions to oncology studies involving disease progression and treatment outcomes.

Publications

The researcher has contributed to scholarly publications addressing topics associated with hepatology, oncology, and related biomedical disciplines. Published work supports ongoing scientific discussion and dissemination of research findings.[1][3]

  1. Peer-reviewed journal articles.
  2. Collaborative biomedical research publications.

Research Impact

Citation records indicate engagement with the research output by other scholars and healthcare researchers. The citation count and publication metrics suggest that the published work has contributed to scientific discussions within relevant biomedical fields.[1][2]

Award Suitability

Fatema Safri’s scholarly record demonstrates participation in scientific research, publication activity, and contribution to biomedical knowledge. These attributes align with common evaluation criteria used in academic recognition programs that acknowledge research productivity, scholarly engagement, and scientific contribution. Such accomplishments support consideration for recognition through the International Physics and Quantum Physics Awards framework.[1]

Conclusion

Fatema Safri’s academic profile reflects active engagement in hepatology and oncology research through publication, collaboration, and scientific investigation. Her contributions form part of the broader effort to advance biomedical knowledge and improve understanding of important healthcare challenges. The documented research activities and scholarly outputs illustrate ongoing participation in the scientific community.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Fatema Safri, Author ID 58944753700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58944753700
  2. R., Safri, F., Xu, Y., Zhou, Y., Bao, J.-F., George, J., & Qiao, L. (2026). CDKN2A alterations as possible molecular link between environmental pollutants and pathogenesis of liver cancer: Epidemiology, mechanisms, and insights. Hepatobiliary & Pancreatic Diseases International. Advance online publication.
    https://doi.org/10.1016/j.hbpd.2026.05.008
  3. Nguyen, R., Safri, F., Sharma, A., Howell, J., Roberts, S. K., Strasser, S. I., Zekry, A., Wigg, A., Adams, L. A.Clinical need and research investment for liver cancer in Australia. Asia-Pacific Journal of Clinical Oncology. Advance online publication.
    https://doi.org/10.1111/ajco.70055

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Seyed Hasan Musavi | Engineering | Innovative Research Award

Published on by Physics and Quantum Physics

Innovative Research Award

Seyed Hasan Musavi
Researcher Seyed Hasan Musavi
Affiliation University of Mazandaran
Country Iran
Scopus ID 57201488091
Documents 17
Citations 452
h-index 10
Subject Area Engineering
Event International Physics and Quantum Physics Awards

The Innovative Research Award recognizes researchers whose scholarly contributions demonstrate originality, technical advancement, and measurable impact within their respective disciplines. Seyed Hasan Musavi, affiliated with the University of Mazandaran, has established a research portfolio focused on advanced manufacturing technologies, tribology, machining optimization, cryogenic processing, nanofluid applications, and sustainable engineering solutions. His work has contributed to the understanding of machining performance enhancement, environmentally responsible lubrication systems, and surface engineering technologies relevant to modern manufacturing industries.[1]

Abstract

This article evaluates the research achievements and innovation-oriented contributions of Seyed Hasan Musavi in the field of engineering and advanced manufacturing. His investigations have addressed challenges related to machining efficiency, tribological performance, cryogenic cooling, nanofluid-assisted lubrication, surface texturing, and sustainable production technologies. Through experimental and analytical studies, his research has provided insights into improving manufacturing performance while supporting environmentally conscious engineering practices.[2]

Keywords

Advanced Manufacturing, Tribology, Cryogenic Machining, Surface Engineering, Sustainable Lubrication, Nanofluids, Grinding Technology, Machining Performance, Engineering Research, Green Manufacturing.

Introduction

Engineering innovation increasingly depends on interdisciplinary approaches that combine materials science, manufacturing technologies, and environmental sustainability. Research efforts aimed at optimizing machining operations, reducing tool wear, and improving energy efficiency play a significant role in industrial competitiveness. Within this context, Seyed Hasan Musavi has contributed to studies involving cryogenic turning, advanced lubrication systems, and tribological surface design, helping expand knowledge in precision manufacturing and production engineering.[3]

Research Profile

Seyed Hasan Musavi’s research profile demonstrates expertise in manufacturing engineering, tribology, machining science, and sustainable industrial processes. His publication record includes studies published in internationally recognized journals focusing on cryogenic machining, surface texturing technologies, grinding process optimization, ionic liquid lubrication systems, and nanofluid-assisted manufacturing methods.[4]

  • Advanced manufacturing processes and machining optimization.
  • Tribological behavior of engineered surfaces.
  • Cryogenic cooling technologies in machining.

Research Contributions

A notable aspect of Musavi’s research has been the exploration of cryogenic cooling techniques for improving machining efficiency and extending tool life. His investigations into pre-cooling intensity and cryogenic turning have provided data-driven evaluations of manufacturing performance under low-temperature operating conditions.

Publications

  • Pre-cooling Intensity Effects on Cooling Efficiency in Cryogenic Turning.
  • Manufacturing of Durable Tribological Surface by Grinding Process.
  • Development of a New Cutting Tool by Changing the Surface Texture for Increasing the Machining Performance.

Research Impact

With more than four hundred citations and a measurable h-index, Musavi’s work has gained visibility within engineering and manufacturing research communities. His publications address practical industrial challenges while contributing to theoretical developments in tribology, machining science, and sustainable manufacturing technologies.[1]

Award Suitability

The Innovative Research Award recognizes originality, technical advancement, and scholarly influence. Seyed Hasan Musavi’s body of work demonstrates these characteristics through the development of novel machining strategies, advanced lubrication concepts, tribological surface engineering techniques, and sustainable manufacturing methodologies. His contributions align with the objectives of recognizing researchers whose innovations advance scientific understanding and industrial practice.

Conclusion

Seyed Hasan Musavi has established a research profile characterized by innovation in manufacturing engineering, tribology, and sustainable industrial technologies. His contributions to cryogenic machining, lubrication science, and surface engineering demonstrate a consistent commitment to addressing practical engineering challenges through rigorous scientific investigation. These accomplishments provide a strong foundation for recognition under the Innovative Research Award category.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Seyed Hasan Musavi, Author ID 57201488091. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57201488091
  2. Musavi, S.H., Ganji, D.D. (2026). A Comprehensive Review on Nanofluids Applications in the Machining Industry. Results in Engineering.
    https://doi.org/10.1016/j.rineng.2026.109220
  3. Musavi, S.H., Razfar, M., Ganji, D.D. (2024). New Application of Ionic Liquid as a Green-Efficient Lubricant. Results in Engineering.
    https://doi.org/10.1016/j.rineng.2024.101773
  4. Google Scholar. (2026). Seyed Hasan Musavi Publication Record.
    https://scholar.google.com/citations?user=eJLLGRMAAAAJ&hl=en

Kamlesh Chandekar | Nanascience and Nanotechnology | Innovative Research Award

Published on by Physics and Quantum Physics

Innovative Research Award

Kamlesh Chandekar
Affiliation Rayat Shikshan Sansthas Karmaveer Bhaurao Patil College Vashi, Navi Mumbai
Country India
Scopus ID 49862955300
Documents 77
Citations 2453
h-index 34
Subject Area Nanoscience and Nanotechnology
Event International Physics and Quantum Physics Awards
ORCID 0000-0002-0712-2778

Kamlesh Chandekar is an Indian researcher whose scholarly work is primarily focused on nanoscience, nanotechnology, advanced functional materials, ferrite nanostructures, magnetic materials, and their applications in biomedical, electronic, and optoelectronic systems. His publication record, citation impact, funded research activities, and interdisciplinary collaborations demonstrate sustained contributions to contemporary materials science and applied physics research.[1]

Abstract

This article presents an overview of the academic achievements, research activities, publication output, and scientific influence of Kamlesh Chandekar. His research portfolio encompasses nanomaterials, ferrites, quantum-scale materials, magnetic nanoparticles, dielectric systems, and biomedical applications.he has contributed to the advancement of materials characterization and functional nanostructures for emerging technological applications.[2]

Keywords

  • Nanoscience
  • Nanotechnology
  • Ferrite Nanoparticles
  • Quantum Materials
  • Materials Physics
  • Biomedical Nanomaterials
  • Magnetic Materials
  • Advanced Functional Materials

Introduction

Research in nanoscience and nanotechnology has become increasingly important due to its potential applications across healthcare, electronics, energy, and environmental technologies. Kamlesh Chandekar’s academic work is situated within this interdisciplinary domain, focusing on the synthesis, characterization, and application of nanostructured materials. His studies frequently integrate structural, optical, dielectric, magnetic, and biological investigations to understand material behavior and performance under diverse conditions.[3]

Research Profile

The research profile of Kamlesh Chandekar reflects a strong emphasis on materials science, applied physics, nanotechnology, and interdisciplinary scientific investigations. He has authored or co-authored numerous scholarly articles indexed in major bibliographic databases and has participated in funded projects related to advanced functional materials and biomedical nanotechnology.[1]

Research Contributions

A significant portion of Chandekar’s research investigates ferrite-based nanostructures, quantum dots, doped oxide materials, and multifunctional nanocomposites. His work explores how modifications in composition, morphology, and synthesis methods influence physical and biological properties. These studies contribute to understanding magnetic behavior, electromagnetic shielding performance, optical characteristics, and anticancer applications of advanced nanomaterials.[4]

Publications

Selected recent publications demonstrate active engagement in advanced materials research and nanotechnology development.[4]

  1. Impact of PVA coated MFe2O4 nanocomposites on structural, magnetic, spectroscopic and anticancer properties. DOI: 10.1007/s00289-025-06269-2.
  2. Impact of Ag coated CoFe2O4, NiFe2O4 and ZnFe2O4 quantum dots for anticancer activity. DOI: 10.1016/j.matchemphys.2025.131963.
  3. Structural and electromagnetic shielding properties of Cr doped Ni–Zn ferrites. DOI: 10.1007/s10854-025-15939-w.

Research Impact

The citation metrics associated with Chandekar’s scholarly output indicate substantial visibility within the scientific community. His research contributes to ongoing developments in nanomaterials, magnetic systems, biomedical applications, and advanced functional materials. Citation performance, publication productivity, and collaborative research activities collectively suggest a measurable influence in the field of nanoscience and materials research.[1]

Award Suitability

Based on available bibliometric indicators, publication output, interdisciplinary collaborations, Kamlesh Chandekar demonstrates qualifications that align with evaluation criteria commonly considered for international scientific recognition programs. His work involving advanced nanomaterials, ferrite systems, quantum materials, and biomedical applications reflects scientific relevance to contemporary physics and materials research communities.[1]

Conclusion

Kamlesh Chandekar has established a scholarly profile characterized by sustained research productivity, interdisciplinary scientific engagement, and contributions to nanoscience and nanotechnology. His publication record, citation performance, funded projects, and investigations into advanced functional materials demonstrate an active role in advancing contemporary materials and applied physics research.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Kamlesh Chandekar, Author ID 49862955300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=49862955300
  2. ORCID. (2026). Kamlesh V. Chandekar Research Activities and Scholarly Record.
    https://orcid.org/0000-0002-0712-2778
  3. Chandekar, K. V., Shkir, M., Khan, A., & Alfaify, S. (2022). Novel magnetic materials preparation, characterizations and their applications. In Fundamentals and Industrial Applications of Magnetic Nanoparticles (pp. 67–109). Woodhead Publishing.
    https://doi.org/10.1016/B978-0-12-822819-7.00015-6
  4. Chandekar, K.V., et al. (2026). Impact of Ag coated CoFe2O4, NiFe2O4, and ZnFe2O4 quantum dots synthesized by co-precipitation route for anticancer activity against MDA-MB 231 and MCF-7 breast cancer cell lines.DOI:
    https://doi.org/10.1016/j.matchemphys.2025.131963

Panagiota-Kyriaki Revelou | Food science and machine learning | Best Researcher Award

Published on by Physics and Quantum Physics

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Best Researcher Award

Panagiota-Kyriaki Revelou
Affiliation University of West Attica
Country Greece
Scopus ID 55340850400
Documents 31
Citations 540
h-index 13
Subject Area Food Science and Machine Learning
Event International Physics and Quantum Physics Awards
ORCID 0000-0003-3329-9398

Panagiota-Kyriaki Revelou is a Greek researcher specializing in food science, food technology, analytical chemistry, food safety, phytochemistry, and the application of machine learning methodologies in food-related systems. Her academic and professional activities include research, teaching, laboratory analysis, and interdisciplinary investigations that connect food quality, sustainability, consumer behavior, and emerging technological approaches.[1] [2]

Abstract

This article presents an academic overview of Panagiota-Kyriaki Revelou, a researcher affiliated with the University of West Attica whose work spans food science, food technology, phytochemical analysis, food safety systems, sustainability, consumer studies, and machine learning applications in food monitoring. Her scholarly output includes peer-reviewed journal publications addressing analytical methodologies, food waste reduction, food quality assessment, bioactive compounds, and digital innovations in food safety management.[1][3]

Keywords

Food Science, Food Technology, Machine Learning, Food Safety, HACCP, Analytical Chemistry, Consumer Behavior, Food Waste, Phytochemistry, Sustainable Food Systems, Bioactive Compounds, Research Excellence.

Introduction

The integration of advanced analytical techniques and data-driven methodologies has transformed modern food science. Researchers increasingly combine traditional laboratory investigations with computational approaches to improve food quality, safety, traceability, and sustainability. Within this context, Panagiota-Kyriaki Revelou has contributed to research activities that examine food composition, phytochemical properties, consumer perceptions, and machine learning applications in food systems.[4]

Research Profile

Revelou earned a PhD in Organic Chemistry within the field of Food Science and Human Nutrition from the Agricultural University of Athens. Her academic career includes postdoctoral research appointments and teaching activities at the University of West Attica, particularly within the Department of Food Science and Technology. Earlier professional experience included laboratory analytical work, contributing to her expertise in food testing and quality assessment.[1]

  • Food Science and Technology research
  • Analytical and Organic Chemistry applications
  • Food Safety and HACCP monitoring systems

Research Contributions

Her research portfolio demonstrates interdisciplinary engagement across food chemistry, nutritional science, sustainability studies, and emerging computational technologies. Published investigations have addressed household food waste behaviors, machine learning applications for food safety monitoring, consumer awareness of cultured meat technologies, and analytical determination of biologically active compounds in food matrices.[3][4]

  • Investigation of food waste reduction strategies and educational interventions.
  • Application of machine learning tools for HACCP and food safety monitoring.
  • Characterization of phytochemical constituents and bioactive compounds.

Publications

Selected publications associated with Panagiota-Kyriaki Revelou include peer-reviewed journal articles that demonstrate research activity in food science, sustainability, analytical chemistry, and machine learning applications.[3]

  1. Investigating Household Food Waste Behaviors: A Social Practice Theory-Based Survey Combined with an Educational Intervention (2026).
  2. Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods (2025).
  3. Determination of Phenethyl Isothiocyanate, Erucin, Iberverin, and Erucin Nitrile Concentrations in Broccoli Tissues Using GC-MS (2024).

Research Impact

According to the supplied Scopus metrics, Revelou has authored 31 indexed documents, accumulated approximately 540 citations, and achieved an h-index of 13. These indicators suggest sustained scholarly engagement and measurable influence within food science and related interdisciplinary research domains.[2] Her work contributes to ongoing discussions regarding sustainable food systems, food safety technologies, consumer education, and analytical methodologies for food evaluation.[3][4]

Award Suitability

For the Best Researcher Award presented within the International Physics and Quantum Physics Awards framework, Panagiota-Kyriaki Revelou demonstrates characteristics commonly considered in academic recognition programs, including peer-reviewed publication activity, interdisciplinary research engagement,  Her research profile reflects sustained scholarly productivity and the advancement of knowledge in applied scientific disciplines.[1][2]

Conclusion

Panagiota-Kyriaki Revelou has established a research profile centered on food science, analytical chemistry, sustainability, and technology-enabled approaches to food safety and quality assessment. Her scholarly record, research collaborations, and interdisciplinary investigations illustrate continued contributions to academic research and applied scientific knowledge. Through publications, educational involvement, and methodological innovation, she remains engaged in areas that support the development of modern food systems and evidence-based decision-making.[1][4]

References

  1. ORCID. (n.d.). Panagiota-Kyriaki Revelou (ORCID: 0000-0003-3329-9398).
    https://orcid.org/0000-0003-3329-9398
  2. Elsevier. (n.d.). Scopus author details: Panagiota-Kyriaki Revelou, Author ID 55340850400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55340850400
  3. Revelou, P.-K., et al. (2025). Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods. Foods.
    DOI:https://doi.org/10.3390/foods14060922
  4. Revelou, P.-K., et al. (2026). Investigating Household Food Waste Behaviors: A Social Practice Theory-Based Survey Combined with an Educational Intervention. World.
    DOI:https://doi.org/10.3390/world7030042

Steven Rountree | Coherent-Phase Optical Time Domain Reflectometry for Monitoring High-Temperature Superconducting Magnet Systems | Innovative Research Award

Published on by Physics and Quantum Physics

Innovative Research Award

Steven Rountree
Affiliation Luna Innovations Incorporated
Country United States
Scopus ID 57212292067
Documents 3
Citations 3
h-index 1
Subject Area Coherent-Phase Optical Time Domain Reflectometry for Monitoring High-Temperature Superconducting Magnet Systems
Event International Physics and Quantum Physics Awards
ORCID 0000-0002-2151-3556

The Innovative Research Award recognizes researchers who demonstrate sustained scientific contributions through impactful publications, interdisciplinary collaboration, and technological innovation. Steven Rountree has contributed to research involving distributed fiber optic sensing, optical instrumentation, harsh-environment monitoring, superconducting magnet diagnostics, and advanced sensing technologies for nuclear and energy applications.[1][2]

Abstract

Steven Rountree’s published research primarily focuses on optical fiber sensing technologies for demanding operational environments including nuclear reactors, clean-energy systems, and high-performance superconducting magnet infrastructures. His work integrates coherent-phase optical time domain reflectometry, distributed sensing, machine learning, radiation-resistant optical fibers, and advanced photonic instrumentation to improve monitoring accuracy and operational reliability.[2][3]

Keywords

Distributed Fiber Optic Sensors, Optical Time Domain Reflectometry, High-Temperature Superconductors, Nuclear Instrumentation, Machine Learning, Fiber Optics, Smart Materials, Optical Engineering, Energy Monitoring, Photonics.

Introduction

Modern sensing systems increasingly rely on advanced optical technologies capable of operating in extreme environments where conventional electronic sensors encounter significant limitations. Steven Rountree’s research has contributed to this field through studies involving distributed optical sensing, harsh-environment fiber optics.His publications emphasize practical implementation while maintaining scientific rigor and engineering reliability.[2]

Research Profile

Steven Rountree is affiliated with Luna Innovations Incorporated in the United States. According to the supplied Scopus author profile, the researcher has three indexed documents, three citations, and an h-index of one. His scholarly work spans optical sensing technologies, distributed fiber optic monitoring, harsh-environment instrumentation, and applied photonics for scientific and industrial applications.[1]

Research Contributions

  • Development of distributed fiber optic sensing technologies for nuclear reactor environments.
  • Research on coherent optical sensing methods for high-temperature superconducting magnet monitoring.
  • Application of machine learning to improve temperature profile reconstruction in reactor cores.

Publications

  • High Spatial Resolution and Accurate Temperature Profile Measurements in a Nuclear Reactor Core Enabled by Machine Learning. IEEE Sensors Journal (2024).
  • Experimental Testing of Additively Manufactured Embedded Fiber Optic Smart Devices for Clean Energy Applications. Smart Materials and Structures (2024).
  • Corrosion of Silica-Based Optical Fibers in Various Environments. Corrosion and Materials Degradation (2023).

Research Impact

Although the current Scopus metrics indicate an emerging publication profile, the research addresses strategically important engineering problems involving resilient optical sensing technologies for nuclear facilities, superconducting systems, and clean-energy infrastructures. The interdisciplinary integration of photonics, machine learning, and materials engineering demonstrates practical relevance and establishes a foundation for future scientific development.[1][2]

Award Suitability

Based on the available publication record and documented research activities, Steven Rountree demonstrates meaningful contributions to optical sensing technologies relevant to physics, photonics, and quantum-enabled instrumentation. His work aligns with the objectives of the International Physics and Quantum Physics Awards by advancing measurement methodologies applicable to high-performance scientific infrastructure. This assessment reflects the available bibliographic evidence without implying comparative ranking among nominees.[1][2]

Conclusion

Steven Rountree’s research portfolio illustrates continued engagement in optical sensing, distributed fiber technologies, and advanced instrumentation for demanding operational environments. His publications contribute to ongoing developments in applied physics and engineering while supporting improvements in monitoring accuracy, reliability, and safety within nuclear and clean-energy systems. The documented scholarly record supports recognition within innovation-focused scientific award programs.[2]

References

  1. Elsevier. (n.d.). Scopus Author Details: Steven Rountree, Author ID 57212292067.
    https://www.scopus.com/authid/detail.uri?authorId=57212292067
  2. ORCID. (2026). Steven Rountree (0000-0002-2151-3556): Works and Research Activities.
    https://orcid.org/0000-0002-2151-3556
  3. Experimental Testing of Additively Manufactured Embedded Fiber Optic Smart Devices for Clean Energy Applications. Smart Materials and Structures (2024).
    DOI:https://doi.org/10.1088/1361-665X/ad7aeb

Antoine Druilhe | Quantum Information Science | Quantum Theory Award

Published on by Physics and Quantum Physics

Quantum Theory Award

Antoine Druilhe
Électricité de France Research and Development

                         Antoine Druilhe
Affiliation Électricité de France Research and Development
Country France
Scopus ID 39761201700
Documents 4
Citations 6
h-index 1
Subject Area Quantum Information Science
Event International Physics and Quantum Physics Awards
ORCID 0009-0004-7239-1095

The Quantum Theory Award recognizes researchers contributing to the advancement of quantum information science and related theoretical developments. Antoine Druilhe has established a documented research profile through publications indexed in Scopus and professional research identification systems. His scholarly activities contribute to the broader understanding of quantum systems, computational methods, and theoretical physics applications within industrial and research environments.[1][2]

Abstract

Antoine Druilhe is a researcher affiliated with Électricité de France Research and Development whose scholarly activities are associated with quantum information science and theoretical physics. His publication record indexed in Scopus demonstrates engagement with topics relevant to quantum systems, computational modelling, and advanced physical methodologies. Although compact in scale, his research portfolio reflects participation in contemporary scientific investigations and contributes to ongoing academic discussions within quantum-related disciplines. Bibliometric indicators, including indexed documents, citations, and author identifiers, provide evidence of recognized scholarly output and support consideration for professional recognition within international physics and quantum science award programs.[1][2]

Keywords

Quantum Information Science; Quantum Theory; Theoretical Physics; Quantum Systems; Computational Physics; Scientific Research Evaluation; Physics Awards; Research Impact.

Introduction

Antoine Druilhe contributes to research associated with quantum information science through investigations connected to theoretical and computational physics. His affiliation with Électricité de France Research and Development reflects engagement in scientific activities supporting innovation, modelling, and advanced analytical approaches within modern physics disciplines.[1]

Research Profile

The research profile of Antoine Druilhe is documented through internationally recognized researcher identification systems, including Scopus and ORCID. Available bibliometric information indicates a developing publication record focused on scientific inquiry, knowledge dissemination, and contributions relevant to quantum and computational research domains.[1][2]

Research Contributions

His scholarly contributions support the advancement of scientific understanding in areas associated with quantum information science. Through peer-reviewed publications and collaborative research efforts, he has participated in investigations that strengthen theoretical frameworks and encourage further exploration of complex physical systems.[1]

Publications

The Scopus author profile reports four indexed documents associated with Antoine Druilhe. These publications contribute to the visibility of his research activities and provide a measurable record of scholarly engagement within recognized scientific communication channels.[1]

Research Impact

Research impact may be evaluated through citations, publication visibility, and participation in scholarly networks. The documented citation record and indexed publications indicate that Antoine Druilhe’s work has received measurable academic attention and contributes to the broader scientific literature.[3]

Award Suitability

Antoine Druilhe demonstrates characteristics relevant to consideration for the Quantum Theory Award, including an established research affiliation, indexed publications, scholarly citations, and engagement with quantum information science. These factors collectively support recognition within international programs celebrating contributions to theoretical physics research.[1][4]

Conclusion

The available scholarly record identifies Antoine Druilhe as a researcher contributing to quantum information science through recognized academic outputs. His documented publications, citations, and professional affiliations provide an objective foundation for academic recognition and continued participation in scientific advancement.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Antoine Druilhe, Author ID 39761201700. Scopus.https://www.scopus.com/authid/detail.uri?authorId=39761201700
  2. ORCID. (n.d.). Antoine Druilhe researcher profile. ORCID Registry.https://orcid.org/0009-0004-7239-1095
  3. Antoine Druilhe. (n.d.). Toward a tripartite taxonomy of entropy in physics.https://doi.org/10.3390/e28060704
  4. International Physics and Quantum Physics Awards. (n.d.). Award program information and evaluation framework.https://physicsandquantumphysics.com/

Adeeba Arooj | Research Excellence | Research Excellence Award

Published on by Physics and Quantum Physics

Research Excellence Award

Adeeba Arooj
University of Lahore

Adeeba Arooj
Affiliation University of Lahore
Country Pakistan
Scopus ID 58871669100
Documents 11
Citations 181
h-index 5
Subject Area Research Excellence
Event International Physics and Quantum Physics Awards

The Research Excellence Award recognizes researchers who demonstrate sustained scholarly productivity, measurable academic impact, and meaningful contributions to scientific advancement. Adeeba Arooj of the University of Lahore has established a growing research profile supported by peer-reviewed publications, citation impact, and interdisciplinary scientific contributions. Her academic work reflects engagement with contemporary scientific challenges and contributes to the dissemination of evidence-based knowledge within the global research community.[1]

Abstract

Adeeba Arooj is an emerging researcher affiliated with the University of Lahore, Pakistan. Her scholarly portfolio includes peer-reviewed publications that have contributed to the advancement of scientific understanding within her research domain. With a documented citation record and measurable academic impact, her work demonstrates consistent engagement with contemporary research challenges. The combination of publication productivity, citation performance, and interdisciplinary relevance highlights her commitment to knowledge generation and scientific dissemination. These achievements support recognition under the Research Excellence Award category and reflect meaningful contributions to academic research and professional scholarship.[1]

Keywords

Research Excellence, Scientific Research, Academic Publications, Citation Impact, Scholarly Contributions, Interdisciplinary Research, Research Productivity, Evidence-Based Science, Academic Recognition, Scientific Advancement

Introduction

Research excellence is measured through scholarly productivity, citation influence, and meaningful scientific contributions. Adeeba Arooj has developed an academic profile characterized by peer-reviewed publications and recognized research outputs. Her work contributes to scientific knowledge dissemination while supporting the advancement of evidence-based methodologies across contemporary research environments.[1]

Research Profile

Affiliated with the University of Lahore, Adeeba Arooj maintains an active research presence supported by eleven indexed publications. Her scholarly record includes measurable citation performance and a growing academic footprint. The profile reflects consistent participation in scientific inquiry, collaboration, and publication activities relevant to advancing contemporary research objectives.[2]

Research Contributions

The researcher has contributed to scientific literature through studies addressing relevant academic questions and evidence-driven investigations. Her publications demonstrate analytical rigor, methodological application, and scholarly engagement. These contributions support knowledge expansion, encourage future research directions, and strengthen interdisciplinary understanding within the broader scientific community.[2]

Publications

Adeeba Arooj has authored and co-authored multiple peer-reviewed research articles indexed within recognized academic databases. Her publication portfolio demonstrates sustained scholarly activity and reflects contributions to research quality, scientific communication, and the dissemination of findings that support academic progress and professional knowledge exchange.[1]

Research Impact

With 181 citations and an h-index of 5, the researcher demonstrates measurable influence within the academic community. Citation performance indicates that published findings have been referenced by other scholars, reflecting visibility, relevance, and the ability to contribute meaningfully to ongoing scientific discussions and research developments.[1]

Award Suitability

Adeeba Arooj’s publication record, citation metrics, and demonstrated commitment to scientific research align with the objectives of the Research Excellence Award. Her academic achievements illustrate sustained scholarly engagement and support recognition for contributions that advance scientific understanding, professional development, and the broader research ecosystem.[1]

Conclusion

The academic profile of Adeeba Arooj reflects research productivity, scholarly impact, and dedication to scientific advancement. Through publications, citations, and continued engagement in research activities, she demonstrates qualities associated with research excellence and professional scholarship, making her a suitable candidate for recognition within international academic award programs.[3]

References

  1. Elsevier. (n.d.). Scopus author details: Adeeba Arooj, Author ID 58871669100. Scopus.https://www.scopus.com/authid/detail.uri?authorId=58871669100
  2. Sharif, M., Gul, M. Z., & Arooj, A. (2025). Feasible stellar interiors beyond Einstein gravity: Insights from non-metricity-matter coupled gravitational theory. Physics of the Dark Universe, 47, 101795.
    https://www.sciencedirect.com/science/article/abs/pii/S0003491626000229
  3. International Physics and Quantum Physics Awards. (n.d.). Award Program Information and Recognition Criteria.https://physicsandquantumphysics.com/

wei zhu | high energy physics and astronomy | Innovative Research Award

Published on by Physics and Quantum Physics

Innovative Research Award

Wei Zhu
Affiliation East China Normal University
Country China
Documents 68
Citations 2546
h-index 24
Subject Area High Energy Physics and Astronomy
Event International Physics and Quantum Physics Awards

Wei Zhu is a researcher associated with East China Normal University whose scholarly activities span artificial intelligence, language modeling, medical informatics, and computational methodologies relevant to modern scientific and technological applications. The researcher has contributed to multiple interdisciplinary studies involving large language models, natural language processing, machine learning optimization, and intelligent healthcare systems. Academic metrics indicate sustained citation performance and a significant publication record in internationally recognized conferences and journals.[1]the Innovative Research Award recognizes scholarly contributions that demonstrate methodological innovation, interdisciplinary impact, and measurable influence within scientific research communities.and scalable language model optimization.[2]

Abstract

Wei Zhu has established a research profile centered on machine learning systems, large language model optimization, medical natural language processing, and parameter-efficient adaptation methodologies. Published studies demonstrate involvement in advanced computational architectures including prompt tuning, low-rank adaptation frameworks, multimodal learning systems, and scalable transformer optimization techniques. The researcher’s publication portfolio includes conference proceedings from ACL, EMNLP, NAACL, ICASSP, and related international computational linguistics venues. Citation metrics further indicate notable academic visibility and continuing influence within applied artificial intelligence research domains.[1][3]

Keywords

Artificial Intelligence; Large Language Models; Prompt Tuning; Natural Language Processing; Medical Informatics; Low-Rank Adaptation; Transformer Models; Machine Learning; Computational Linguistics; Deep Learning

Introduction

The researcher’s publication record reflects consistent engagement with high-impact computational research topics including prompt engineering, adaptive parameter tuning, architecture search, early exiting mechanisms, medical decision extraction, and language model acceleration. These studies contribute to ongoing efforts aimed at improving computational efficiency and expanding the practical applicability of artificial intelligence systems in real-world scientific and industrial environments.[4]

Research Profile

Academic metrics derived from publicly available scholarly profiles indicate more than 2,500 citations and an h-index of 24, reflecting measurable influence within the computational research community. Published studies have appeared in internationally recognized venues including ACL, EMNLP, ICASSP, NAACL, and major machine learning conferences.[1]

  • Research focus on large language model optimization and parameter-efficient fine-tuning.
  • Contributions to biomedical natural language processing and healthcare AI systems.
  • Development of scalable prompt tuning and adaptation strategies.
  • Studies involving architecture search and efficient transformer inference.

Research Contributions

One of the researcher’s highly cited contributions involves the Ultrafeedback project, which examined methods for improving language model performance through high-quality and scaled artificial intelligence feedback systems.Such approaches are increasingly relevant to reducing computational cost while preserving inference quality in large-scale transformer systems.

  • Ultrafeedback frameworks for language model enhancement.
  • Prompt tuning architectures for efficient language adaptation.
  • Transformer acceleration and early exiting methodologies.

Publications

Selected publications associated with Wei Zhu include internationally recognized conference papers and journal articles in machine learning and natural language processing domains.[1]

    1. Cui, G., Yuan, L., Ding, N., Yao, G., Zhu, W., et al. “Ultrafeedback: Boosting Language Models with Scaled AI Feedback.” arXiv, 2023.
    2. Zhu, W. “LeeBERT: Learned Early Exit for BERT with Cross-Level Optimization.” Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, 2021.
    3. Zhu, W., Tan, M. “SPT: Learning to Selectively Insert Prompts for Better Prompt Tuning.” Proceedings of EMNLP, 2023.
    4. Zhang, J., Gao, J., Ouyang, W., Zhu, W., et al. “Time-LLaMA: Adapting Large Language Models for Time Series Modeling.” ACL Proceedings, 2025.

Research Impact

The research impact associated with Wei Zhu is reflected through citation performance, collaborative publication output, and contributions to emerging areas of artificial intelligence. Studies involving efficient fine-tuning, adaptive prompt systems, and scalable language model architectures continue to influence ongoing research in natural language processing and machine learning engineering.[1]

Award Suitability

Wei Zhu’s interdisciplinary publication record and measurable research influence align with the objectives commonly associated with innovation-focused scientific recognition programs. Contributions to language model optimization, efficient adaptation methodologies, and healthcare-oriented computational systems demonstrate technical originality and broad applicability across scientific and industrial domains.[3]

Conclusion

Wei Zhu has contributed to contemporary developments in machine learning, natural language processing, and intelligent computational systems through research involving efficient transformer optimization, prompt adaptation, healthcare AI, and scalable language modeling techniques. The researcher’s publication portfolio and citation metrics indicate continuing influence within interdisciplinary artificial intelligence research communities. These achievements support the recognition of scholarly contributions through the Innovative Research Award and related international academic distinctions.[1]

References

  1. Google Scholar. (2026). Wei Zhu citation profile and publication metrics.
    https://scholar.google.com/citations?user=EF5J_BYAAAAJ&hl=en&oi=sra
  2. Cui, G., Yuan, L., Ding, N., et al. (2023). Ultrafeedback: Boosting Language Models with High-Quality Feedback.
    https://openreview.nhttps://doi.org/10.48550/arXiv.2310.01377et/
  3. Wang, P., Zheng, H., Xu, Q., Dai, S., Wang, Y., Yue, W., Zhu, W., Qian, T., & Zhao, L. (2025). TS-HTFA: Advancing time-series forecasting via hierarchical text-free alignment with large language models. Symmetry.
    https://doi.org/10.3390/sym17030401
  4. Elsevier. (2020). Medical knowledge graph applications in healthcare analytics.
    https://doi.org/10.2196/17653

Marcus Jager | Orthopadie und Unfallchirurgie | Excellence in Innovation Award

Published on by Physics and Quantum Physics

Excellence in Innovation Award

Marcus Jager
Affiliation Universität Duisburg-Essen
Country Germany
Scopus ID 7103272586
Documents 247
Citations 5,446
h-index 39
Subject Area Orthopadie und Unfallchirurgie
Event International Physics and Quantum Physics Awards

The Excellence in Innovation Award recognizes researchers whose scholarly activities demonstrate sustained contributions to scientific development, interdisciplinary innovation, and academic leadership within their respective fields. Marcus Jager of Universität Duisburg-Essen has established a substantial research profile in orthopaedic surgery, trauma surgery, motion analysis, regenerative medicine, and clinical biomechanics through an extensive body of peer-reviewed publications and collaborative research initiatives.[1] His academic record reflects continued engagement with emerging technologies in orthopaedics, including artificial intelligence-assisted gait analysis, extracellular vesicle research, and biologically integrated biomaterials.[2]

Abstract

Marcus Jager is a German academic researcher associated with Universität Duisburg-Essen whose research activities encompass orthopaedics, trauma surgery, regenerative medicine, extracellular vesicle biology, gait analysis,His publication portfolio includes peer-reviewed studies addressing musculoskeletal biomechanics, hip arthroplasty, biomaterials, and artificial intelligence applications in orthopaedic diagnostics.[1] With 247 indexed documents, 5,446 citations, and an h-index of 39, his research output demonstrates substantial visibility within the international scientific community.[1]

Keywords

Orthopaedics; Trauma Surgery; Regenerative Medicine; Artificial Intelligence; Gait Analysis; Extracellular Vesicles; Biomaterials; Hip Arthroplasty; Clinical Biomechanics; Medical Innovation

Introduction

Innovation within clinical orthopaedics increasingly relies upon interdisciplinary integration involving biomechanics, biomedical engineering, regenerative medicine, and data-driven computational methodologies. Researchers operating within this environment contribute not only to surgical advancement but also to translational healthcare applications capable of improving patient outcomes and rehabilitation strategies.[3]

Marcus Jager has participated in multiple research initiatives focusing on technologically assisted orthopaedic evaluation systems, biologically enhanced biomaterials, extracellular vesicle characterization, and clinical musculoskeletal reconstruction. His work reflects broader contemporary developments in evidence-based orthopaedic innovation and translational biomedical science.[2] Through collaborations spanning surgery, computational analysis, and biomaterials research, his academic activities demonstrate a multidisciplinary orientation relevant to modern medical research frameworks.

Research Profile

According to Scopus author records, Marcus Jager is affiliated with Universität Duisburg-Essen in Duisburg, Germany.[1] His indexed scholarly output includes 247 documents with citation metrics exceeding 5,400 citations and an h-index of 39, reflecting sustained academic productivity and influence within orthopaedic and trauma-related medical research.[1]

  • Research specialization in orthopaedic surgery and trauma medicine
  • Interdisciplinary collaborations involving biomechanics and computational analysis
  • Clinical studies related to hip arthroplasty and motion analysis
  • Research on extracellular vesicles and regenerative biomaterials

Research Contributions

One of the significant themes within Jager’s recent research activities concerns the integration of artificial intelligence into orthopaedic motion analysis. Publications such as AI in instrumental gait analysis: Challenges and solution approaches and Orthopaedics of the future: AI meets motion analysis: opportunities and risks examine methodological considerations surrounding machine learning implementation in clinical gait assessment systems.[2]

His research portfolio also includes studies investigating extracellular vesicles and regenerative biomaterials. Publications addressing CD9+ and CD82+ extracellular vesicles in synovial fluid and osteogenically induced mesenchymal stromal cell-derived vesicles illustrate interest in translational regenerative medicine and inflammatory differentiation within prosthetic orthopaedics. Such work aligns with broader scientific efforts to improve implant integration and tissue regeneration through biologically informed therapeutic strategies.

Publications

Selected publications associated with Marcus Jager include the following scholarly works:

  1. Leg length and offset in short-stem total hip arthroplasty: is a single offset implant sufficient to restore the hip rotation centre within a range of 5 mm?, Archives of Orthopaedic and Trauma Surgery, 2026.
  2. Colormap augmentation: a novel method for cross-modality domain generalization, International Journal of Computer Assisted Radiology and Surgery, 2026.
  3. AI in instrumental gait analysis: Challenges and solution approaches,Orthopadie, 2025.
  4. Orthopaedics of the future: AI meets motion analysis: opportunities and risks, 2025.

Research Impact

The citation profile associated with Marcus Jager’s scholarly activities indicates substantial engagement by the international academic community.[1] Citation-based indicators, including more than 5,446 citations and an h-index of 39, suggest that his research has contributed meaningfully to discussions surrounding orthopaedic biomechanics, regenerative medicine, and translational clinical science.The international visibility of his publications through indexed databases and peer-reviewed journals further supports the broader dissemination of his scientific findings across orthopaedic and biomedical research communities.[1]

Award Suitability

The Excellence in Innovation Award emphasizes scholarly achievement, interdisciplinary advancement, and measurable scientific contribution. Marcus Jager’s research profile demonstrates alignment with these criteria through his sustained publication activity, integration of technological methodologies into orthopaedic medicine, and translational contributions connecting clinical practice with computational and biological sciences.[2]

Particularly notable is his engagement with artificial intelligence applications in motion analysis and regenerative approaches utilizing extracellular vesicles and biomaterial biologization techniques. These research areas reflect contemporary innovation trends within healthcare systems and translational medicine.His publication metrics and collaborative output further support recognition within an international academic award framework.

Conclusion

Marcus Jager has developed an extensive academic profile characterized by interdisciplinary orthopaedic research, translational biomedical investigation, and integration of computational methodologies within clinical medicine. His publication record, citation metrics, and collaborative scientific activities indicate sustained engagement with evolving challenges in musculoskeletal healthcare and regenerative medicine.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Marcus Jager, Author ID 7103272586. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7103272586
  2. Jäger, M., et al. (2025). Intraoperative biologization of β-TCP and PCL-TCP by autologous proteins..Orthopadie.
    https://doi.org/10.3390/jfb16090340
  3. Dračić, A., Zeravica, D., Becirbegovic, S., Jäger, M., & Beck, S. (2025). Steep tibial slope correlates with inferior patient-reported knee function independent of tunnel widening.
    https://doi.org/10.1002/ksa.70096

Shahwar Yasir | Neuroscience | Best Researcher Award

Published on by Physics and Quantum Physics

Best Researcher Award

Shahwar Yasir
Affiliation University of Electronic Science and Technology of China
Country China
Scopus ID 58820146400
Documents 2
Citations 2
h-index 1
Subject Area Neuroscience
Event International Physics and Quantum Physics Awards

The Best Researcher Award recognition highlights the academic and scientific contributions of Shahwar Yasir, a researcher affiliated with the University of Electronic Science and Technology of China. His research activities primarily focus on neuroscience, electroencephalography (EEG), neuroimaging, and the neurological effects associated with COVID-19-related brain dysfunctions. His scholarly work includes interdisciplinary studies integrating computational neuroscience, connectomics, and electrophysiological signal analysis.[1] The award recognition is associated with the International Physics and Quantum Physics Awards platform and acknowledges emerging contributions to contemporary neuroscience and brain dynamics research.[2]

Abstract

Shahwar Yasir is recognized for his contributions to neuroscience research, particularly in the analysis of EEG biomarkers, neural connectivity, and COVID-induced neurological dysfunctions. His work demonstrates interdisciplinary integration between computational modeling, neurophysiology, and clinical neuroscience. Published studies associated with his academic profile investigate electrophysiological signatures, lifespan EEG development, and neurological outcomes following SARS-CoV-2 infection.[3] The award recognition acknowledges emerging scientific contributions with measurable academic visibility in indexed scholarly databases and collaborative international research environments.

Keywords

  • Neuroscience
  • Electroencephalography (EEG)
  • COVID-19 Brain Dysfunction
  • Brain Imaging

Introduction

Modern neuroscience increasingly relies on computational and electrophysiological methods to understand the structural and functional mechanisms underlying cognitive and neurological disorders. Within this context, Shahwar Yasir has contributed to collaborative investigations addressing EEG signal analysis, neural stability, and COVID-related neurological effects.[4] His research activities reflect growing interdisciplinary convergence between neuroscience, biomedical engineering, and data-driven neuroimaging methodologies.

The International Physics and Quantum Physics Awards platform recognizes researchers whose work demonstrates scientific engagement and emerging impact across multidisciplinary domains. Yasir’s contributions to electrophysiological analysis and neural dynamics have positioned his work within broader discussions on computational neuroscience and neural systems modeling.[2]

Research Profile

According to Scopus author records, Shahwar Yasir is affiliated with the University of Electronic Science and Technology of China in Chengdu, China. His indexed scholarly profile includes publications in neuroscience-related journals and interdisciplinary collaborations involving EEG source analysis, brain dysfunction studies, and neural connectivity research.[1]

His documented research interests include EEG analysis, neuromaps, brain imaging, connectomics, and long-COVID neurological effects. The available metrics associated with his academic profile include indexed documents, citations, and an h-index reflecting early-stage research impact within collaborative scientific publications.[3]

Research Contributions

One of the notable research areas associated with Shahwar Yasir involves the investigation of COVID-induced neurological dysfunctions. Collaborative studies examined electrophysiological and neurobiological determinants linked with SARS-CoV-2 infection outcomes and post-hospitalization cognitive conditions.

Additional contributions include EEG alpha rhythm analysis and lifespan-related neural source development studies. Research published in National Science Review explored how EEG alpha and aperiodic component sources are influenced by connectomic structures and axonal delays, contributing to broader understanding of neural communication mechanisms.

Further collaborative work investigated qEEG-mediated effects associated with infection severity and COVID-induced brain dysfunction. These studies emphasize quantitative electrophysiological approaches for identifying neurofunctional biomarkers and neural response variability.

Publications

  • Yasir, S., Jin, Y., Razzaq, F.A., et al. “The determinants of COVID-induced brain dysfunctions after SARS-CoV-2 infection in hospitalized patients.” Frontiers in Neuroscience, 17, 1249282 (2024).
  • Garcia Reyes, R., Areces Gonzalez, A., Wang, Y., Jin, Y., Yasir, S., et al. “Lifespan development of EEG alpha and aperiodic component sources is shaped by the connectome and axonal delays.” National Science Review, 13(7), nwag076 (2026).
  • Qi, M., Yasir, S., Wang, Y., et al. “Neuro-EPO Preserves Neural Stability in Parkinson’s Disease: An EEG Paired t-Test Analysis.” International Journal of Psychophysiology (2025). DOI:

Research Impact

The available citation indicators associated with Shahwar Yasir demonstrate emerging scholarly visibility within neuroscience and EEG-related research areas. Indexed publications in recognized scientific journals contribute to broader scientific discussions regarding electrophysiological biomarkers, neural connectivity, and post-COVID neurological outcomes.[1]

Collaborative publication patterns also indicate participation in international research networks involving neuroscience, computational modeling, and neurophysiological signal analysis. Such interdisciplinary collaboration is increasingly relevant in contemporary brain research and translational neuroscience initiatives.

Award Suitability

The academic profile of Shahwar Yasir aligns with the evaluation principles commonly associated with emerging researcher recognitions and interdisciplinary scientific awards. His involvement in EEG-based neuroscience research, collaborative publications, and investigations into neurological implications of COVID-19 reflects active participation in contemporary scientific inquiry.

The International Physics and Quantum Physics Awards framework emphasizes research relevance, scholarly dissemination, and contribution to scientific advancement. Yasir’s research portfolio demonstrates engagement with these criteria through indexed publications and ongoing interdisciplinary collaborations involving neuroscience and computational methodologies.[2]

Conclusion

Shahwar Yasir represents an emerging researcher within the field of neuroscience whose scholarly activities include EEG analysis, neural connectivity modeling, and investigations into COVID-associated neurological dysfunctions. His indexed publications and collaborative contributions demonstrate growing academic engagement within interdisciplinary neuroscience research. Recognition through the Best Researcher Award category reflects the relevance of his scientific participation and research dissemination within international academic platforms.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Shahwar Yasir, Author ID 58820146400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58820146400
  2. International Physics and Quantum Physics Awards. (n.d.). Official Award Platform.
    https://physicsandquantumphysics.com/
  3. Google Scholar. (n.d.). Shahwar Yasir Research Profile and Citation Metrics.
    https://scholar.google.com/
  4. Garcia Reyes, R., Areces Gonzalez, A., Wang, Y., Jin, Y., Yasir, S., et al. (2026). Lifespan development of EEG alpha and aperiodic component sources is shaped by the connectome and axonal delays. National Science Review.
    https://doi.org/10.1093/nsr/nwag076