Farhad Hossain Sojib | Data Science | Best Researcher Award

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Mr. Farhad Hossain Sojib | Data Science | Best Researcher Award 

University of Hull | Bangladesh

Mr. Farhad Hossain Sojib is an engineer with a strong foundation in electronics and communication engineering and a growing specialization in data science and artificial intelligence. He is currently pursuing his M.Sc. in Artificial Intelligence and Data Science at the University of Hull, United Kingdom, following the completion of his B.Sc. in Engineering from Hajee Mohammad Danesh Science and Technology University, Bangladesh, where he conducted notable research on explainable AI in educational data mining and machine learning applications in 5G antenna optimization. With professional experience as an IELTS Instructor at Lexicon Plus, he has trained over 50 students, developed course materials, and mentored junior instructors. His leadership and organizational skills were further demonstrated through his role as a Program Committee Member at the IEEE Student Branch, HSTU, where he managed events, seminars, and competitions. Additionally, his internship at BRACNet Limited provided hands-on experience in ISP operations, ICT technologies, and server management. Farhad combines his technical expertise, research acumen, and collaborative mindset to contribute meaningfully to the fields of machine learning and data-driven innovation.

Profiles: Orcid 

Featured Publications

"The integration of explainable AI in Educational Data Mining for student academic performance prediction and support systems", Md. Mahmudul Islam; Farhad Hossain Sojib; Md. Fazle Hasan Mihad; Mahmudul Hasan; Mahfujur Rahman, Telematics and Informatics Reports, 2025.

"A Bioinformatics Approach to Uncover Hub Genes and Potential Drug Targets of Stroke, Heart-Disease, Hyperglycemia, and Hypertension", Md. Emran Biswas; M D. Fazle Hasan Mihad; Farhad Hossain Sojib; Mohammad Jubair Ahmmed; M D Galib Hasan; Md. Jobare Hossain; Md. Abul Basar; Md. Mehedi Islam; Md. Delowar Hossain; Md. Selim Hossain et al., 27th International Conference on Computer and Information Technology (ICCIT), 2024.

"An Explainable Educational Data Mining System for Predicting Student Academic Performance", Md. Mahmudul Islam; Farhad Hossain Sojib; Md. Fazle Hasan Mihad; Mahmudul Hasan; Mahfujur Rahman; FARHAD HOSSAIN SOJIB, 2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, 2024.

Lin Yu Rou |  Machine Learning | Best Researcher Award

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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.