Young-Chan Lee | Generative AI | Excellence in Research

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Prof. Young-Chan Lee | Generative AI | Excellence in Research

Professor, Dongguk University, South Korea

🌟 Dr. Young-Chan Lee is a distinguished professor at Dongguk University, Korea, where he has been serving since 2004. With a rich academic and leadership background, he also holds key roles such as Dean of the Continuing Education Institute and the Institute of Ecology Education. Dr. Lee’s contributions extend globally, including positions at universities in Vietnam and Malaysia. His dedication to information systems and management science has earned him a stellar reputation in both academia and industry.

Publication Profile

ORCID

Education

🎓 Dr. Lee completed his Ph.D. in Management Science from Sogang University in 2003, specializing in data mining, system dynamics, and e-commerce strategy. He also holds an M.A. in Management Science from the same institution, where he concentrated on multi-objective decision-making models, and a B.A. in Business Administration with a focus on finance, econometrics, and management science.

Experience

💼 Over his career, Dr. Lee has taken on leadership roles at Dongguk University, including Dean of the School of Business Administration and Office of International Affairs. He has also worked internationally as an Adjunct Professor at Ton Duc Thang University in Vietnam and as a Senior Researcher at INTI International University in Malaysia. His academic career is complemented by editorial roles in several prestigious journals.

Research Focus

🔬 Dr. Lee’s research interests lie in data mining, machine learning for business analytics, knowledge management, system dynamics, and fintech innovation. He is particularly known for applying systems thinking and multi-criteria decision-making to tackle complex business and management challenges.

Awards and Honours

🏆 Dr. Lee has received numerous accolades, including multiple Best Paper Awards from leading associations such as the Korea Association of Information Systems. His work has also earned recognition on a global scale, including the Most Cited Paper Award from Elsevier and the Top Downloaded Paper Award from Wiley.

Publication Top Notes

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives

Ethical AI in Financial Inclusion: The Role of Algorithmic Fairness on User Satisfaction and Recommendation

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes through SDL and AIDUA Perspectives

 

 

Tesfay Gidey | Artificial Intelligence | Best Researcher Award

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Dr. Tesfay Gidey | Artificial Intelligence | Best Researcher Award

Lecturer, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a highly skilled Information and Communication Engineer and data scientist with a passion for leveraging data to drive innovation and business insights. With expertise in computer science, software engineering, machine learning, and data analytics, he excels in problem-solving, leadership, and technology project management. Tesfay’s work focuses on indoor localization, signal processing, and health data applications, making him a forward-thinking leader in his field. His dedication to continuous learning and delivering actionable results underscores his impressive career in academia and industry. 💼🔧📊

Publication Profile

ORCID

Strengths for the Award:

  1. Diverse Expertise: Tesfay’s expertise spans across critical areas such as signal processing, indoor localization, machine learning, data fusion, and health informatics, aligning well with cutting-edge research areas.
  2. Impressive Academic Qualifications: Holding a Ph.D. in Information and Communication Engineering, along with two MSc degrees, he possesses deep knowledge in interdisciplinary fields.
  3. Research Contributions: He has authored numerous peer-reviewed publications in high-impact journals such as Sensors, Intelligent Information Management, and Journal of Biostatistics. His work in Wi-Fi indoor positioning, predictive modeling, and health informatics shows a broad application of research across industries.
  4. Leadership in Academia: His roles as Associate Dean and Head of Department demonstrate his leadership in driving research, improving curriculum quality, and promoting technology transfer.
  5. Innovative Research Focus: His Ph.D. dissertation on transfer learning for fingerprint-based indoor positioning and various data fusion methods reflect his innovative contributions to solving real-world problems with advanced technologies.

Areas for Improvement:

  1. Broader Industry Impact: While his research is highly academic, incorporating more industry-driven collaborations or commercial applications could strengthen the practical impact of his work.
  2. Public Engagement: Increasing public outreach and collaboration with non-academic sectors or public talks could elevate his visibility and expand the impact of his research findings.
  3. Global Collaboration: Expanding his research collaborations beyond local and regional levels, particularly with international industries, could further showcase the global relevance of his work.

Education 🎓

Tesfay holds a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China (2023), where his research centered on signal and information processing applied to indoor positioning using machine learning algorithms. He also earned an MSc in Software Engineering from HILCOE School of Computer Science and Information Technology (2018) and an MSc in Health Informatics and Biostatistics from Mekelle University (2013). Additionally, he completed his BSc in Statistics with a minor in Computer Science at Addis Ababa University (2006). 📚💻📈

Experience 💼

Tesfay has held several leadership positions, including Associate Dean at Addis Ababa Science and Technology University (AASTU), where he led research, technology transfer, student recruitment, and faculty training initiatives. He was also the Head of Department and Coordinator at Jimma University, contributing to curriculum enhancement and student retention programs. His experience spans research in manufacturing industries, project management, and academic administration. 🏫📊👨‍🏫

Research Focus 🔬

Tesfay’s research focuses on signal processing, indoor localization, machine learning, data mining, and information fusion. He specializes in developing advanced models for indoor positioning systems, predictive modeling, and statistical quality control, aiming to solve complex problems in health informatics, manufacturing industries, and public health. His work integrates cutting-edge technologies to advance both theoretical and applied fields. 📡📉🤖

Awards and Honors 🏆

Tesfay has been recognized for his contributions to the fields of information and communication engineering and data science. He has received multiple awards and honors for his research and leadership roles in academia, particularly in driving innovative projects that bridge the gap between technology and industry. 🌍🎖️

Publications Highlights 📚

Tesfay has published extensively in top-tier journals, with a focus on indoor positioning systems, data fusion, and health informatics. His research includes the development of novel machine learning models and statistical analysis tools. His works have been widely cited, showcasing his impact in the academic community. 📊✍️

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection (2023). Intelligent Information Management, 15, 391-425. Cited by 2 articles. Link

Data Fusion Methods for Indoor Positioning Systems Based on Channel State Information Fingerprinting (2022). Sensors, 22, 8720. Cited by 15 articles. Link

Heterogeneous Transfer Learning for Wi-Fi Indoor Positioning Based Hybrid Feature Selection (2022). Sensors, 22, 5840. Cited by 10 articles. Link

OHetTLAL: An Online Transfer Learning Method for Fingerprint-Based Indoor Positioning (2022). Sensors, 22, 9044. Cited by 5 articles. Link

A Multilevel Modeling Analysis of the Determinants and Cross-Regional Variations of HIV Testing in Ethiopia (2016). J Biom Biostat, 7, 277. Cited by 8 articles. Link

Conclusion:

Tesfay Gidey Hailu’s robust academic background, extensive research portfolio, and leadership roles make him a strong candidate for the Best Research Award. His work in signal processing, machine learning, and data-driven innovation in health informatics and communication systems demonstrates a clear commitment to advancing technology and solving societal problems. While his impact could be enhanced by deeper industry collaborations and global outreach, his current achievements already reflect substantial contributions to the field, making him deserving of recognition.