Hassan Ali | Engineering | Best Researcher Award

Published on by Young Scientists Awards

Best Researcher Award

Hassan Ali
Affiliation Polytechnic Institute of Viana do Castelo
Country Portugal
Google Scholar ID 7I_DwpYAAAAJ
Citations 134
h-index 6
i10-index 1
Subject Area Engineering
Event International Young Scientist Awards

Hassan Ali

Polytechnic Institute of Viana do Castelo, Portugal

The Best Researcher Award profile recognizes the scholarly activities, engineering research engagement, and academic contributions associated with Hassan Ali of the Polytechnic Institute of Viana do Castelo. This article presents a structured overview of the research profile, publication record, scholarly impact indicators, and relevance to academic recognition programs. The profile is prepared in a neutral encyclopedic format consistent with academic recognition documentation and researcher assessment practices.[1][2]

Abstract

This academic profile summarizes the research activities of Hassan Ali within the field of Engineering. The assessment incorporates scholarly visibility metrics, publication activity, citation indicators, and institutional affiliation. The objective is to provide a concise overview of the researcher’s academic standing and suitability for professional recognition through scholarly awards and international research distinctions.[1][3]

Keywords

Engineering, Research Excellence, Scholarly Impact, Citation Analysis, Academic Recognition, Research Evaluation, Higher Education, Scientific Contributions, Research Metrics, Best Researcher Award.

Introduction

Academic awards frequently evaluate researchers using a combination of publication output, citation performance, research innovation, and institutional engagement. Within this framework, Hassan Ali’s profile reflects active participation in engineering-related scholarly activities. Research assessment indicators such as citation counts, h-index values, and publication visibility are commonly employed to evaluate academic influence and contribution to scientific knowledge.[2][4]

Research Profile

Hassan Ali is affiliated with the Polytechnic Institute of Viana do Castelo in Portugal. The research profile demonstrates engagement with engineering-focused academic investigations and scholarly dissemination activities. According to available scholarly indexing information, the profile records 134 citations, an h-index of 6, and an i10-index of 1. These indicators provide measurable evidence of research visibility and scholarly utilization within the academic community.[1][5]

Research Contributions

The research contributions associated with this profile are situated within the broad discipline of Engineering. Contributions may include scholarly publications, technical investigations, collaborative research activities, methodological development, and dissemination of findings through peer-reviewed venues. Such activities support the advancement of scientific understanding and practical engineering applications while contributing to the broader academic ecosystem.[3]

Publications

Publication activity represents a core component of scholarly evaluation. Peer-reviewed journal articles, conference proceedings, technical reports, and collaborative research outputs contribute to knowledge dissemination and scientific communication. Publication visibility through indexing platforms and citation databases supports the measurement of academic reach and impact.[2]

Research Impact

Research impact is often assessed through citation-based indicators and evidence of scholarly engagement. The citation record associated with this profile suggests that published work has been referenced within the academic literature. Metrics such as the h-index provide a balanced measure that combines productivity and citation influence, while citation counts reflect the degree to which research outputs are utilized by other scholars.[4][5]

Award Suitability

Based on the available academic indicators and documented scholarly activity, Hassan Ali demonstrates characteristics commonly considered in research recognition programs. Evaluation committees may review publication quality, citation performance, institutional contribution, research relevance, and academic engagement when considering candidates for distinctions such as the Best Researcher Award. Final determinations remain subject to the specific criteria established by the awarding organization.

Conclusion

This profile provides an overview of Hassan Ali’s academic and research-related achievements within the Engineering discipline. Through scholarly publications, citation activity, and institutional affiliation, the profile demonstrates engagement with recognized academic practices. Continued research dissemination and scholarly collaboration are expected to further contribute to research visibility and academic development.[1]

References

  1. Google Scholar. (n.d.). Scholar profile and citation metrics for Hassan Ali.
    https://scholar.google.com/citations?user=7I_DwpYAAAAJ&hl=en
  2. Elsevier. (n.d.). Research assessment and scholarly publication indexing practices.
    https://www.scopus.com
  3. Moed, H. F. (2005). Citation Analysis in Research Evaluation.
  4. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output.
  5. Harzing, A. W. (2016). Publish or Perish and citation metrics.

Abirami Karthikeyan | Engineering | Young Scientist Award

Published on by Young Scientists Awards

Dr. Abirami Karthikeyan | Engineering | Young Scientist Award

Assistant Professor | SASTRA Deemed University | India.

Dr. Abirami Karthikeyan is a researcher specializing in RF and microwave systems with a strong focus on non-invasive microwave sensors for Industrial IoT and biomedical applications. Her work advances smart sensing, metasurface-enhanced resonators, and near-field radio-frequency techniques for food, agriculture, and healthcare industries. She has published in high-impact journals and contributed to multiple conferences, book chapters, and patent innovations in microwave sensing. Her research includes integrated sensing-communication systems, 5G/6G antenna design, and intelligent RF systems for precision monitoring. She has secured competitive funding and earned notable awards for her research excellence and innovation. Her projects emphasize practical, application-driven microwave solutions supported by strong simulation, prototyping, and measurement expertise. She actively collaborates on interdisciplinary sensor development bridging electromagnetics, IoT, and smart industrial technologies. her published 10 research documents that have received 10 citations, resulting in an h-index of 2.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
10
Documents
10

h-index
2


View Scopus  Profile
 View Google Scholar Profile

Featured Publications

 

Heba Afify | Engineering | Editorial Board Member

Published on by Young Scientists Awards

Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

Published on by Young Scientists Awards

Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

Uwayesu Happy Edwards | Engineering | Excellence in Research Award

Published on by Young Scientists Awards

Mr. Uwayesu Happy Edwards | Engineering | Excellence in Research Award

Suzhou university of science and technology | China

Mr. Uwayesu Happy Edwards the research focuses on environmental engineering, natural resource assessment, wastewater treatment modeling, hydropower system analysis, and climate-related environmental degradation across East and Central Africa. Recent work investigates the factors driving water quality changes in Lake Bunyonyi, integrating ecological metrics with habitat-impact assessments. Studies on wastewater treatment processes include large-scale evaluation of ASM1 parameters under subtropical climatic conditions, using long-term WWTP monitoring data to improve predictive reliability and optimize treatment efficiency. Broader environmental impact assessments examine risk patterns in natural resource zones across Southern Nigeria, Ibo regions, and Uganda’s Kitezi landfill, applying quantitative environmental models to evaluate pollution, habitat stress, and human–ecosystem interaction. Additional research explores deforestation-driven climate change in Morogoro, Tanzania, emphasizing the environmental implications for EPA-related conservation missions. Work on hydropower comparability analyzes the performance, sustainability, and environmental footprints of hydropower relative to fossil fuels and other energy systems in developing countries, contributing to renewable-energy assessment frameworks. Complementary studies investigate biomass arrangement effects on aquatic ecosystems, using vibrational analysis to evaluate impacts on fish habitats in Lake Victoria. Across these projects, the research integrates environmental modeling, climate assessment, water-resource analytics, and sustainable energy evaluation to support data-informed environmental management and policy development.

Featured Publications

Uwayesu, H. E., & Mulangila, J. (2025). Factor contributing to change of water in Lake Bunyonyi [Dataset]. Figshare. https://doi.org/10.6084/m9.figshare.30041587

Uwayesu, H. E. (2025). Address of Edwards line of emissions in reducing/positive impact to climate [Dataset]. OSF. https://doi.org/10.17605/osf.io/csz8x

 Uwayesu, H. E. (2025). Environmental impact and risk assessment of natural resource areas around Southern Nigeria, particularly Ibo and Uganda in the Kitezi landfill [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/EJ4Z7E

 Uwayesu, H. E. (2025). Evaluation of ASM1 parameters using large-scale WWTP monitoring data from a subtropical climate in Entebbe [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/BG5VJB

Mujeeb Abiola Abdulrazaq | engineering | Young Scientist Award

Published on by Young Scientists Awards

Mr. Mujeeb Abiola Abdulrazaq l engineering
| Young Scientist Award

University of North Carolina at Charlotte | United States

Mr. Mujeeb Abiola’s research focuses on advancing transportation safety and efficiency through data-driven methodologies and emerging technologies. His work extensively employs large-scale traffic and crash data, including millions of federal highway administration records, to investigate the spatiotemporal dynamics of pedestrian crashes and the evolution of crash hotspots. Utilizing advanced statistical and machine learning models, he has developed predictive frameworks that outperform traditional Highway Safety Manual standards, providing robust insights into risk factors and injury severity in both human-driven and autonomous vehicle contexts. His research on connected and autonomous vehicles (CAVs) has led to the development of traffic control algorithms that significantly enhance safety, operational efficiency, and environmental sustainability in freeway work zones. Furthermore, his studies integrate GPU-accelerated data processing, simulation-based optimization, and multi-level heterogeneity modeling to evaluate vulnerable road user behavior and assess dynamic collision risks. Through simulation platforms such as VISSIM and SUMO, combined with Python-based data analysis and GIS applications, his work systematically addresses complex traffic scenarios, including merging, diverging, and weaving segments, while also accounting for seasonal variations and temporal constraints in crash determinants. His contributions include empirical analyses of autonomous vehicle incidents, methodological advancements in microsimulation accuracy, and development of actionable strategies for real-world traffic management, ultimately aiming to improve roadway safety, inform policy, and guide evidence-based planning in modern transportation systems.

Profile:  Google Scholar 

Featured Publications

  • Abdulrazaq, M. A., & Fan, W. D. (2024). Temporal dynamics of pedestrian injury severity: A seasonally constrained random parameters approach. International Journal of Transportation Science and Technology, 9.

  • Abdulrazaq, M. A., & Fan, W. (2025). A priority based multi-level heterogeneity modelling framework for vulnerable road users. Transportmetrica A: Transport Science, 1–34. https://doi.org/10.1080/23249935.2025.2516817

  • Abdulrazaq, M. A., & Fan, W. (2025). Seasonal instability in crash determinants: A partially temporally constrained modeling analysis. SSRN 5341417. https://doi.org/10.2139/ssrn.5341417

Sheharyar Khan | Engineering | Young Scientist Award

Published on by Young Scientists Awards

Dr. Sheharyar Khan l Engineering
| Young Scientist Award

Shandong University | Pakistan

Dr. Sheharyar Khan is a distinguished computer scientist and software engineer with extensive expertise in software engineering, artificial intelligence, and cybersecurity, specializing in IoMT edge-cloud frameworks and network intrusion detection systems. Currently a Postdoctoral Research Fellow at Shandong University, he leads independent and collaborative research initiatives, designing experiments, analyzing data, and publishing findings in high-impact journals. His doctoral research at Northwestern Polytechnical University focused on optimization-based hybrid offloading frameworks for IoMT in edge-cloud healthcare systems, demonstrating the integration of advanced computing techniques with practical healthcare applications. Dr. Khan has made significant contributions to explainable AI and hybrid ensemble machine learning, as seen in publications such as “HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems” and “Consensus hybrid ensemble machine learning for intrusion detection with explainable AI”. With prior experience as a lecturer and IT specialist, he combines academic rigor with practical software development expertise. Dr. Khan has 104 citations across 10 documents, an h-index of 6, an i10-index of 5, is indexed under Scopus Author ID 57221647889, and holds ORCID 0000-0002-0089-0168, reflecting his impact on the field. Recognized for his analytical skills, innovation, and interdisciplinary research, he continues to advance secure, intelligent, and explainable computing systems for both academic and real-world applications.

Profile: Scopus | Google Scholar | Orcid | Researchgate 

Featured Publications

Khan, S., Liu, S., Pan, L., & Mei, G. (2025). Optimization-based hybrid offloading framework for IoMT in edge-cloud healthcare systems. Future Generation Computer Systems, 108163. https://doi.org/

Ahmed, S. K. M. T. S., Jiangbin, Z., & Khan, S. (2025). HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems. Cluster Computing, 28(343). https://doi.org/

Ahmed, M. T. S., Jiangbin, Z., & Khan, S. (2024). Consensus hybrid ensemble machine learning for intrusion detection with explainable AI. Journal of Network and Computer Applications, 5*. https://doi.org/

Khan, S., Jiangbin, Z., & Ali, H. (2024). Soft computing approaches for dynamic multi-objective evaluation of computational offloading: A literature review. Cluster Computing, 27(9), 12459–12481. https://doi.org/