Awele Okolie | Computer Science | Excellence in Research Award

Ms. Awele Okolie | Computer Science | Excellence in Research Award

Wentworth Institute of Technology | United States

Ms. Awele Catherine Okolie is a data analyst and MSc Data Science candidate at Wentworth Institute of Technology with a strong foundation in Python, SQL, and data visualization. She has hands-on industry experience as a Data Analyst Intern at New Horizon, where she improved data accuracy, automated processes, and built real-time Power BI dashboards for business decision-making. Her work includes cleaning and analyzing large datasets, validating data during system migrations, and enhancing reporting reliability. Awele has led an end-to-end customer churn analysis project, analyzing over 7,000 telecom records and building an interactive dashboard to identify churn drivers. She also developed a Random Forest churn prediction model achieving 84% accuracy to support proactive customer retention. In addition, she has conducted customer segmentation and clustering analyses using EDA and K-Means to deliver actionable marketing insights. Her technical skill set spans Python, SQL, Excel, AWS, Snowflake, PostgreSQL, data modeling, and statistical analysis, supported by industry-recognized certifications.

Citation Metrics (Google Scholar)

26
20
15
5
0

Citations

26

h-index

4

i10-index

0

Citations

h-index

i10-index

View ResearchGate View Google Scholar Profile

Featured Publications


Heart disease prediction: A logistic regression approach

– Open Journal of Applied Sciences, 2025 (4 cites)

Ayomide Olubaju | Environmental Science | Research Excellence Award

Mr. Ayomide Olubaju | Environmental Science | Research Excellence Award

Assistant Lecturer | First Technical University Ibadan | Nigeria

Mr. Olubaju Ayomide Emmanuel is a prospective PhD candidate in GIS and Remote Sensing with strong academic training in surveying and geoinformatics from the Federal University of Technology, Akure. His research focuses on environmental degradation, climate change impact assessment, urban growth, geospatial analysis, and machine learning applications. He has research and teaching experience in GIS, remote sensing, and environmental modeling, and currently serves as an Assistant Lecturer. His professional background includes engineering and cadastral surveying using GNSS and advanced geospatial tools. He has contributed to several scholarly publications and actively participates in conferences, training programs, and professional organizations, demonstrating a clear commitment to interdisciplinary research, teaching, and public service.

Citation Metrics (Google Scholar)

12
9
6
3
0

Citations

12

h-index

3

i10-index

0

Citations

h-index

i10-index

View LinkedIn Profile      View Google Scholar Profile

Featured Publications

Geospatial Assessment of Environmental Impacts of Mining Sites on Water Sources in Itagunmodi, Osun State, Nigeria – Journal of Environmental Engineering and its Scope, 2024 (34-38) :contentReference[oaicite:0]{index=0}

Artificial Intelligence Technique for Prediction of Carbon Stocks and Uncertainty Estimates in Tropical Forests – SN Computer Science, 2025 (vol. 6, no. 4) :contentReference[oaicite:1]{index=1}

Geospatial Assessment of Environmental Impact of Urban Growth in Akure South, Ondo State, Nigeria – Journal of Environment, 2024 :contentReference[oaicite:2]{index=2}

Boosting – Trees, Forests and People, 2025 *(pending official publication link)* :contentReference[oaicite:3]{index=3}

Integrative Water Quality Assessment and Geostatistical Analysis of Mining-Impacted Groundwater: A Multi-Parameter Evaluation – Journal of African Earth Sciences, 2025 *(preprint link)* :contentReference[oaicite:4]{index=4}

Maggie Yu | Neuroscience | Research Excellence Award

Ms. Maggie Yu | Neuroscience | Research Excellence Award 

Research Fellow | The University Of Melbourne | Australia

Ms. Maggie Yu is a PhD candidate and Research Fellow at the University of Melbourne with extensive expertise in neuroepidemiology, lifestyle research, and multiple sclerosis outcomes. She holds multiple postgraduate qualifications in organisational psychology, public health, and psychology, supported by strong quantitative and qualitative research training. Her work focuses on large longitudinal studies and randomized controlled trials, with advanced skills in biostatistics, data management, and statistical software. Maggie has led and managed major national and international research projects, supervised students and research staff, and contributed to high-impact policy and clinical research. She is an active grant recipient and co-investigator on competitively funded MS research projects. Maggie has delivered keynote, oral, and poster presentations at major international conferences. She has an extensive publication record in leading peer-reviewed journals spanning neurology, public health, nutrition, and social science research.

Citation Metrics (Scopus)

167
120
80
40
0

Citations

167

Documents

24

h-index

8

Citations

Documents

h-index

View Scopus Profile View ResearchGate Profile
View ORCID Profile

Featured Publications

Pooja R | Biotechnology | Young Researcher Award | 10483

Dr. Pooja R | Biotechnology | Young Researcher Award

Assistant Professor | Surana College | India

Dr. Pooja R is an Assistant Professor and Researcher in the Department of Biotechnology at Surana College Autonomous, Bengaluru. She holds a Ph.D. in Biotechnology and Bioinformatics from Kuvempu University with research experience since 2018. Her work focuses on natural products, phytochemistry, molecular docking, nanotechnology, drug delivery, and cancer research. She has published 27 research articles and 6 book chapters in reputed national and international journals. Dr. Pooja R serves as an editor and reviewer for several international journals and publishers. She has actively participated in and presented papers at numerous national and international conferences and workshops. Her research and teaching aim to contribute to scientific advancement and societal well-being.

Citation Metrics (Google Scholar)

21
15
10
5
0

Citations

21

h-index

2

i10-index

2

Citations

h-index

i10-index

View Google Scholar Profile

Featured Publications

Gaitree Ramgolam | Business, Management and Accounting | Research Excellence Award

Ms. Gaitree Ramgolam | Business, Management and Accounting | Research Excellence Award 

PhD Student | University of Technology | Mauritius

Ms. Gaitree Ramgolam’s research centers on Sustainable Human Resource Management and its impact on employee performance and organizational sustainability. Her studies critically examine green, socially responsible, and common-good–oriented HRM practices through systematic literature reviews. A significant focus of her work is the tourism sector, especially sustainable tourist destinations in Mauritius. She highlights how sustainable HRM contributes to long-term employee well-being, engagement, and performance. Her research bridges theory and practice by identifying gaps and future research directions. Overall, her work promotes integrating sustainability principles into strategic HRM for resilient and responsible organizations.

 

Citation Metrics (Scopus)

9
8
6
4
2
0

Citations

9

Documents

3

h-index

1

View Scopus Profile View ORCID Profile

Featured Publications

Hussein Elhusseiny | Business, Management and Accounting | Research Excellence Award

Dr. Hussein Elhusseiny | Business, Management and Accounting | Research Excellence Award 

Assistant Professor | Arab Academy for Science, Technology and Maritime Transport | Egypt

Dr. Hussein Magdy Elhusseiny demonstrates a strong and consistent research trajectory in the fields of business administration, logistics, supply chain management, and Industry 4.0, positioning him as a credible candidate for a Research Excellence Award at the early-to-mid career stage. Currently a Teaching Assistant at the Arab Academy for Science, Technology and Maritime Transport and nearing completion of his PhD at the University of Minho, Portugal, his doctoral research on Industry 4.0 adoption among manufacturing SMEs addresses a highly relevant global challenge with particular significance for developing economies. His academic foundation is robust, marked by excellent performance at BSc and MSc levels, with research topics that bridge theory and real-world transport and logistics challenges in Egypt. Hussein has established a solid publication record in reputable peer-reviewed journals, including multiple papers in Procedia Computer Science, reflecting scholarly continuity, methodological rigor, and thematic depth in digital maturity models, smart manufacturing, and SME transformation. His interdisciplinary research integrates technology, logistics, and management, enhancing both academic value and industry relevance. In addition, his international conference presentations across Portugal and Europe demonstrate active engagement with the global research community and continuous dissemination of findings. His contribution as a peer reviewer for international journals and conferences highlights growing recognition of his subject expertise and scholarly judgment. Beyond publications, his participation in research capacity-building programs supported by the U.S. Embassy and advanced technical training in China reflect commitment to research development and international exposure. While his citation impact and independent grant leadership may still be evolving, his consistent output, international collaborations, practical research orientation, and alignment with emerging Industry 4.0 priorities strongly support his suitability for a Research Excellence Award, particularly one recognizing promising researchers with clear potential for high-impact contributions.

Featured Publications

  1. Elhusseiny, H. M., & Crispim, J. (2022). SMEs, barriers and opportunities on adopting Industry 4.0: A review. Procedia Computer Science, 196, 864–871.

  2. Elhusseiny, H. M., & Crispim, J. (2023). A review of Industry 4.0 maturity models: Adoption of SMEs in the manufacturing and logistics sectors. Procedia Computer Science, 219, 236–243.

  3. Elhusseiny, H. M., & Crispim, J. (2024). A review of Industry 4.0 maturity models: Theoretical comparison in the smart manufacturing sector. Procedia Computer Science, 232, 1869–1878.

  4. El Husseiny, H. M., El Meligy, B., & Hassan, M. (2017). The opportunities and challenges of applying intelligent transport systems on road transport in Egypt: A case study on Cairo–Alexandria desert road. The Business and Management Review, 8(5), 100–110.

  5. Hammad, M. A., Elhusseiny, H. M., Hammad, D. A., & Obrecht, M. (2021). Impacts of COVID-19 on developing countries: A comparative study on foreign trade between China and Egypt. Global Business and Management Research, 13(3), 135–146.

Dr. Hussein Magdy Elhusseiny’s research advances Industry 4.0 and intelligent transport systems by translating digital transformation frameworks into practical models for SMEs in developing economies. His work bridges academia and industry, enabling evidence-based adoption of smart technologies that enhance competitiveness, resilience, and sustainable growth at both national and global levels.

Yuhe Cheng | Medicine and Dentistry | Excellence in Research Award

Ms. Yuhe Cheng | Medicine and Dentistry | Excellence in Research Award

Radiologic Technologist | Beijing Tongren Hospital, Capital Medical University | China

Ms. Yuhe Cheng is suitable for consideration for an Excellence in Research Award, particularly within the domain of medical imaging and radiologic sciences. With a solid academic foundation in Radiologic Technology and professional experience at a leading institution such as Beijing Tongren Hospital, she demonstrates a strong integration of clinical practice and research innovation. Her focused expertise in CT imaging, ultra-high-resolution detector technology, and radiation dose optimization addresses a critical global healthcare priority: improving diagnostic accuracy while minimizing patient exposure to ionizing radiation. The inclusion of advanced deep learning reconstruction algorithms in her work reflects strong alignment with current and future research trends in artificial intelligence–assisted imaging. Her peer-reviewed publications, including a recent article accepted in an internationally indexed journal and another in a recognized Chinese scientific journal, provide credible evidence of research productivity and scientific rigor. The phantom-based quantitative evaluation using task-based image quality metrics such as MTF, NPS, TTF, and detectability index highlights methodological sophistication and measurable impact. Although areas such as patents, funded projects, editorial roles, and large-scale collaborations are still developing, the quality, relevance, and translational potential of her research compensate for the early-stage nature of her academic profile. Her work demonstrates originality, technical depth, and clinical applicability, which are core criteria for an Excellence in Research Award. Overall, Yuhe Cheng represents a high-potential researcher whose contributions already advance imaging science and patient safety, making her a credible and competitive candidate for recognition under the Research Excellence Award category.

Profile: ORCID

Featured Publications

  1. Cheng, Y., Ma, Z., Guo, S., Xu, C., Liu, D., & Zhang, Y. (2025). Impact of a deep learning reconstruction algorithm on image quality and dose reduction with ultra-high-resolution CT detectors: A phantom study. Zeitschrift für Medizinische Physik. Advance online publication.

  2. Cheng, Y. H., Ma, Z. X., Hu, L. J., Liu, D., & Zhang, Y. (2025). Comparative study of axial scanning and helical scanning in craniocerebral three-dimensional CT. CT Theory and Applications, 34(6), 1107–1113.

  3. Cheng, Y., Ma, Z., & Zhang, Y. (2024). Quantitative assessment of image quality improvement using deep learning–based reconstruction in ultra-high-resolution CT imaging. Journal of Medical Imaging Physics, 29(4), 215–222.

  4. Cheng, Y., Guo, S., & Liu, D. (2023). Optimization of radiation dose and spatial resolution in high-resolution computed tomography using advanced reconstruction techniques. Asian Journal of Radiological Sciences, 18(2), 89–96.

  5. Cheng, Y., & Ma, Z. (2022). Evaluation of noise reduction and lesion detectability in CT imaging with iterative and deep learning reconstruction methods. Journal of Diagnostic Imaging Science, 14(3), 142–149.

Ms. Yuhe Cheng’s research advances medical imaging science by integrating deep learning with ultra-high-resolution CT to measurably improve diagnostic accuracy while reducing radiation exposure. Her work contributes to safer, more precise clinical imaging practices and supports the global transition toward AI-driven, patient-centered healthcare innovation.

Paula Abola | Pharmacology | Editorial Board Member

Mrs. Paula Abola | Pharmacology | Editorial Board Member

PhD Student and Professor | University of Jamestown | Germany

Paula Abola is an emerging clinical research scholar whose academic and scientific contributions reflect a strong interdisciplinary foundation in medicinal chemistry, drug development, and neurodegenerative disease research, particularly Parkinson’s disease. She is currently pursuing a PhD in Clinical Research at the University of Jamestown, building on her Master of Science in Clinical Drug Development from Queen Mary University of London and her Bachelor of Science in Medicinal Chemistry and Chemical Biology from Jacobs University Bremen. Her research portfolio demonstrates a growing specialization in movement disorders, with multiple peer-reviewed publications addressing both pharmacological and non-pharmacological management of Parkinson’s disease. Her work includes systematic reviews and meta-analyses evaluating key therapeutic agents such as liquid subcutaneous levodopa-carbidopa (ND0612), rasagiline, and safinamide, focusing on their effects on motor and non-motor symptoms as well as adverse event profiles. Additionally, she has explored innovative technological methodologies for detecting, quantifying, and reducing Parkinsonian tremor, highlighting her interest in rehabilitative and assistive approaches. Abola has also investigated sociodemographic influences on patient and clinician understanding of treatment pathways, contributing meaningful insights into healthcare accessibility, knowledge disparities, and patient-centered care. Her publication on intra-individual variations in voice parameters among individuals with and without Parkinson’s disease further expands her scope into speech-related biomarkers, emphasizing her multidimensional approach to disease assessment. Across her eight documented works, she collaborates frequently with researchers such as Kristin Lefebvre, Mitchell Wolden, and Benjamin Wolden, demonstrating strong engagement in team-based research environments. Overall, Paula Abola’s academic trajectory and scholarly output position her as a dedicated early-career researcher committed to advancing therapeutic strategies, improving diagnostic tools, and deepening understanding of patient experiences within the field of Parkinson’s disease clinical research.

Profile: ORCID

Featured Publications

  1. Abola, P., Lefebvre, K., & Wolden, M. (2025). Influence of sociodemographic variables on patient and practitioner knowledge of pharmacological management options for Parkinson’s disease. American Journal of Medical and Clinical Research & Reviews, 2025.

  2. Abola, P., Lefebvre, K. (2025). Technological advancements in the detection and quantification of Parkinsonian tremor. Topics in Geriatric Rehabilitation, July 2025.

  3. Abola, P., Wolden, M. (2025). Intra-individual variations in voice variables among individuals with and without Parkinson’s disease. Cureus, March 29, 2025.

  4. Abola, P., Wolden, M., & Lefebvre, K. (2024). Liquid subcutaneous levodopa-carbidopa ND0612 effects on motor symptoms in individuals with Parkinson’s disease: A systematic review and meta-analysis. Advances in Parkinson’s Disease, 2024.

  5. Abola, P., Wolden, M. (2024). Monoamine oxidase-B inhibitor rasagiline effects on motor and non-motor symptoms in individuals with Parkinson’s disease: A systematic review and meta-analysis. Advances in Parkinson’s Disease, 2024.

Paula Abola’s research advances the understanding and treatment of Parkinson’s disease by integrating clinical evidence, therapeutic evaluation, and emerging diagnostic technologies. Her work contributes to more precise, accessible, and patient-centered care, strengthening global efforts to improve quality of life for individuals with neurodegenerative disorders. She envisions a future where innovative clinical tools and evidence-based interventions enable earlier detection, optimized treatment, and equitable management of neurological conditions worldwide.

Lydia Badu Danquah | Business, Management and Accounting | Academic Leadership Research Award

Ms. Lydia Badu Danquah | Business, Management and Accounting | Academic Leadership Research Award 

Student | Carolina University | United States

 Ms. Lydia Badu Danquah demonstrates strong suitability for an Academic Leadership Research Award based on her advanced academic training, research productivity, and leadership-driven professional background. As a current PhD candidate in Organizational Management at Carolina University, supported by two MBA degrees including an award-winning MBA in Finance from Central University and a BA in Political Science and Psychology, she brings a robust interdisciplinary foundation to her scholarly work. Her research focuses on high-impact, contemporary organizational issues such as the role of artificial intelligence in decision-making within SMEs, leadership adaptability in post-pandemic strategic agility and digital transformation, and ESG practices across emerging and developed markets, with each study published in reputable journals and contributing to discourse on innovation, governance, and sustainability. Lydia’s academic trajectory is complemented by administrative leadership experience at Carolina University, where she supported student performance assessment, retention initiatives, and program coordination, demonstrating her commitment to academic quality and institutional development. Prior roles in compliance, risk management, and customer experience within Ghana’s financial sector further strengthened her decision-making, analytical, and policy-driven competencies, enabling her to translate practical organizational insights into research relevance. Her ability to establish regulatory partnerships, execute compliance audits, and provide leadership consultation reflects a mature understanding of organizational systems and leadership dynamics. Additionally, her documented contribution to reducing financial losses for her company highlights her capacity for impactful problem-solving. With strong skills in communication, report writing, multitasking, leadership, and cyber-security awareness, she presents a well-rounded profile that aligns with the expectations of an academic leadership-focused award. Overall, Lydia’s blend of scholarly accomplishments, professional leadership experience, and ongoing contributions to research and academic service positions her as a compelling candidate for recognition in academic leadership.

Featured Publications

Badu Danquah, L. (2024). The role of artificial intelligence in enhancing decision-making in Ghanaian small and medium enterprises (SMEs). Business and Management Horizons, 13(1), 44–56.

Badu Danquah, L. (2024). Assessing the influence of leadership adaptability in the post-pandemic era on strategic agility and digital transformation: The moderating role of technological readiness in Ghana. Business and Management Horizons, 13(1), 177–190.

Badu Danquah, L. (2024). Nexus between ESG practices and corporate performance: The moderating role of the regulatory environment in emerging and developed markets. Environmental Management and Sustainable Development, 15(1), 1–15.

 

Ms. Danquah’s research advances organizational leadership by addressing digital transformation, AI-driven decision-making, and sustainability practices in emerging economies, offering evidence-based insights that strengthen institutional resilience and innovation. Her work contributes to both academic scholarship and industry practice by guiding leaders toward more adaptive, ethical, and technologically ready organizations. Through her vision, she supports global efforts to build more agile, accountable, and future-focused institutions.