Lin Yu Rou |  Machine Learning | Best Researcher Award

Ms. Lin Yu Rou |  Machine Learning | Best Researcher Award

Software Development Engineer, China Trust Commercial Bank, Taiwan

Yuruo Lin is a passionate researcher and aspiring data scientist with a strong foundation in information and finance management. With hands-on experience in data analytics, machine learning, and healthcare informatics, she actively engages in interdisciplinary research projects, focusing on practical applications that merge technology and social impact. Her academic journey is marked by leadership, innovation, and a commitment to empowering communities through data-driven solutions.

🔹Professional Profile:

Orcid Profile

🎓Education Background

  1. Master’s in Information and Finance Management
    National Taipei University of Technology, Taiwan
    Sep 2022 – Jun 2024

    • Honorable Mention in 2023 Capstone Project Competition

    • Participant in “STEM & Female Research Talent Cultivation Program (2022)”

  2. Bachelor’s in Information Management
    National Taipei University of Nursing and Health Sciences, Taiwan
    Sep 2018 – Jun 2022

    • 2nd Place, 2021 National Collegiate Information Application Innovation Competition

    • Published research on the impact of COVID-19 on hospital quality

    • President, IT Volunteer Club; led USR project and received Outstanding Club and Officer Scholarship

💼 Professional Development

Yuruo has collaborated on diverse academic and practical research projects, combining statistical methods with machine learning and data visualization to address real-world problems. She developed predictive models for ESG performance using ensemble learning, analyzed hospital service quality amid the COVID-19 pandemic, and experimented with algorithmic trading strategies. Her work spans financial analytics, public health equity, and VR-based elderly care solutions.

🔬Research Focus

  • Data Science and Machine Learning

  • Financial and Investment Analytics

  • Healthcare Informatics and Public Health Data

  • Human-Computer Interaction (HCI)

  • Media Analytics for ESG Performance

  • Social Impact Technology (VR, USR Projects)

📈Author Metrics:

Yuruo Lin is the first author of a peer-reviewed research article titled “How can media attention reveal ESG improvement opportunities? A multi-algorithm ML-based approach for Taiwan’s electronics industry,” published in the Elsevier journal Expert Systems with Applications in 2025. This journal is indexed in SCI and Scopus, with a strong impact factor in the fields of artificial intelligence and applied computing. Her publication explores media-driven ESG analytics using ensemble machine learning and clustering techniques, demonstrating both technical depth and relevance to sustainability research. The work has garnered academic attention and serves as a foundation for her growing research profile in data science and ESG modeling.

🏆Awards and Honors:

  • Honorable Mention – 2023 Capstone Project Competition, NTUT

  • 2nd Place – 2021 National Collegiate Information Application Innovation Competition (VR Therapy)

  • Outstanding Club Leadership – IT Volunteer Club, USR Project, Ministry of Education

  • Multiple Awards – National Innovation Proposal Competitions (2020–2021)

  • Scholarship – Officer Scholarship for Club Leadership

📝Publication Top Notes

1. How can media attention reveal ESG improvement opportunities? A multi-algorithm machine learning-based approach for Taiwan’s electronics industry

Journal: The North American Journal of Economics and Finance
Publisher: Elsevier
Publication Date: May 2025
DOI: 10.1016/j.najef.2025.102431
ISSN: 1062-9408
Contributors: Shu Ling Lin, Yu Rou Lin, Xiao Jin
Indexing: Scopus, SSCI
Abstract Summary:
This study applies ensemble machine learning algorithms—including Naive Bayes, Support Vector Machines, Random Forest, and Neural Networks—combined with clustering and semi-supervised learning to investigate how media attention can serve as a predictive signal for ESG performance changes in Taiwan’s electronics industry. The findings highlight the potential of media-driven analytics in enhancing ESG investment strategies and corporate monitoring.

2. Exploring the Relationship between Corporate ESG Ratings and Media Attention through Machine Learning: Predictive Model for the Taiwanese Electronics Industry

Author: Yu Rou Lin
Institution: National Taipei University of Technology
Degree: Master’s in Information and Finance Management
Status: Completed (June 2024)
Contribution: Original draft, research design, and full implementation of machine learning pipeline
Focus: The thesis investigates the correlation between ESG ratings and media sentiment, using real market data and various machine learning models, and serves as the foundational research for the later published journal article.

Conclusion:

In summary, Ms. Yu Rou Lin is an outstanding candidate for the Best Researcher Award in Machine Learning. Her work exemplifies the fusion of technical rigor and societal relevance, with achievements that reflect intellectual curiosity, practical application, and academic leadership.

Her potential for future growth is immense, especially as she continues to refine her research contributions and engage with global scientific communities.

Basil Duwa| Machine learning | Best Researcher Award

Assist. Prof. Dr. Basil Duwa | Machine learning | Best Researcher Award

Operational Center in Healthcare at Near East University, Turkey

Dr. Basil B. Duwa is a results-oriented biomedical data scientist and engineer with expertise in clinical bioinformatics, machine learning for disease prediction, and medical device innovation. With over five years of research and practical experience in healthcare data science, Dr. Duwa has made notable contributions to parasitology-focused AI, wearable sensor analysis, and multi-criteria decision-making in healthcare. He currently serves as an Assistant Professor and Postdoctoral Fellow at the Operational Research Center in Healthcare, Near East University, where he integrates AI and biomedical engineering for real-world medical applications.

Professional Profile:

Orcid

Google Scholar

Education Background

    • Ph.D. in Biomedical Engineering (Specialization: Biomedical Data Science & Bioinformatics)
      Near East University, Nicosia, Cyprus (2021–2023)

    • M.Sc. in Biomedical Engineering (Specialization: Data Science & Decision Analysis)
      Near East University, Nicosia, Cyprus (2019–2021)

    • Postgraduate Diploma in Education
      National Teacher’s Institute, Kaduna (2018–2019)

    • B.Sc. in Biological Sciences (Zoology & Parasitology)
      Adamawa State University, Nigeria (2014–2018)

Professional Development
  • Assistant Professor & Postdoctoral Fellow
    Near East University, Cyprus (2024–Present)

    • Lead AI research in healthcare, predictive modeling, and telemedicine systems.

    • Co-authored a book on medical device applications published by Elsevier.

  • Clinical Informatics Researcher
    Operational Research Center in Healthcare (2022–2024)

    • Developed AI models for disease prediction including malaria and COVID-19.

    • Integrated MCDM methods into healthcare analytics.

  • Research Assistant – Biomedical Data Science
    Near East University (2020–2022)

    • Focused on predictive models and decision systems for biomedical challenges.

  • Monitoring & Evaluation Data Analyst
    Plan International & Save the Children (2012–2018)

    • Evaluated child health and education data; developed analytical dashboards.

Research Focus

Dr. Duwa’s interdisciplinary research combines machine learning, bioinformatics, data visualization, and medical device design. His key interests include:

  • AI-driven disease prediction and diagnostics

  • Wearable sensor data analytics

  • Explainable AI in biomedical decision-making

  • Multi-criteria decision analysis (MCDM) in healthcare

  • Federated learning and clinical applications of AI

Author Metrics:

  • ORCID: 0000-0002-1690-6830

  • Google Scholar Citations: View Profile

  • Publications: 25+ in peer-reviewed journals including Diagnostics, Journal of Instrumentation, and Springer Conference Proceedings

  • Books & Chapters: Co-authored over 10 chapters in books published by Academic Press and Springer

  • Notable Works:

    • Quantitative Forecasting of Malaria Parasite Using Machine Learning

    • Computer-Aided Detection of Monkeypox Using Deep Learning

    • Brain PET Scintillation Crystal Evaluation using MCDM

Awards and Honors:

  • 🏆 Young Researcher Award – Near East University, Cyprus (2023 & 2022)

  • 🥇 Best Essay Award – NAFDAC Consumer Safety Club, Nigeria (2004)

  • 🎓 Article Reviewer – MDPI, Taylor & Francis, Expert Systems, Applied Mathematics in Science & Engineering (2020–2025)

Publication Top Notes

1. Second-Order Based Ensemble Machine Learning Technique for Modelling River Water Biological Oxygen Demand (BOD): Insights into Improved Learning

Authors: A.G. Usman, M. Almousa, H. Daud, B.B. Duwa, A.A. Suleiman, A.I. Ishaq, …
Journal: Journal of Radiation Research and Applied Sciences
Volume: 18(2)
Article: 101439
Year: 2025
Summary: Developed a second-order ensemble machine learning framework to model and predict BOD levels in rivers, improving environmental monitoring accuracy.

🧠 Focus Area: Environmental ML Modeling / Ensemble Learning

2. Enhanced Drug Classification for Cancers of the Liver with Multi-Criteria Decision-Making Method – PROMETHEE

Authors: B.B. Duwa, N. Usanase, B. Uzun
Journal: Global Journal of Sciences
Volume: 2(1), pp. 24–36
Year: 2025
Summary: Applied PROMETHEE (MCDM) for liver cancer drug classification, improving clinical decision-making through structured and explainable evaluation.

💊 Focus Area: Drug Classification / MCDM / Oncology

3. Improving Telemedicine with Digital Twin-Driven Machine Learning: A Novel Framework

Authors: I. Goni, B. Bali, B.M. Ahmad, B.B. Duwa, C. Iwendi
Journal: Global Journal of Sciences
Volume: 1(2), pp. 58–70
Year: 2025
Summary: Introduces a digital twin-powered machine learning architecture to enhance predictive diagnostics in telemedicine systems.

🌐 Focus Area: Telemedicine / Digital Twins / AI in Healthcare

4. Reply to Graña et al. Comment on “Uzun Ozsahin et al. COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach”

Authors: D. Uzun Ozsahin, E. Precious Onakpojeruo, B. Bartholomew Duwa, …
Journal: Diagnostics
Volume: 14(22), Article: 2529
Year: 2024
Summary: A formal response clarifying methodological insights and addressing critiques on a previously published AI model for COVID-19 prediction.

🧬 Focus Area: Model Interpretability / COVID-19 Forecasting

5. Ensemble Predictive Modeling for Dementia Diagnosis

Authors: B.B. Duwa, E.P. Onakpojeruo, B. Uzun, A.J. Hussain, I. Ozsahin, L.R. David, …
Conference: 17th International Conference on Development in eSystem Engineering (DeSE)
Year: 2024
Summary: Demonstrates the power of ensemble ML techniques in diagnosing dementia, integrating multiple model architectures for increased diagnostic precision.

🧠 Focus Area: Medical AI / Cognitive Disorders / Ensemble Learning

Conclusion

Assist. Prof. Dr. Basil B. Duwa is a highly accomplished and innovative biomedical researcher whose work has real-world impact in predictive healthcare, disease diagnostics, and AI-based decision systems. His multi-disciplinary approach, prolific publishing, and novel applications of machine learning in both clinical and environmental contexts make him a strong and deserving candidate for the Best Researcher Award.

Verdict:
Recommended with distinction for the Best Researcher Award in Biomedical Data Science and Machine Learning in Healthcare.