Jong Jin Oh | Data-Driven Decision Making | Best Researcher Award

Best Researcher Award

JONG JIN OH
Seoul National University Bundang Hospital, Seoul National College of Medicine
JONG JIN OH
Affiliation Seoul National University Bundang Hospital, Seoul National College of Medicine
Country South Korea
Scopus ID 24468588100
Documents 164
Citations 2122
h-index 25
Subject Area Data-Driven Decision Making
Event International AI Data Scientists Award
Scopus Profile View Profile

JONG JIN OH, affiliated with Seoul National University Bundang Hospital and Seoul National College of Medicine in South Korea, has demonstrated significant research productivity in the field of Data-Driven Decision Making through scholarly publications, citation impact, and international scientific engagement.[1] The researcher’s academic profile reflects continued participation in evidence-based analytical methodologies and healthcare-related computational research.[2]

Abstract

This article presents an academic overview of JONG JIN OH and the scholarly contributions associated with the Best Researcher Award. The evaluation highlights research productivity, citation performance, interdisciplinary collaboration, and contributions to Data-Driven Decision Making methodologies within healthcare and analytical sciences.[1] Bibliometric indicators demonstrate measurable international research visibility and sustained scientific engagement through peer-reviewed publication activity.[3]

Keywords

Data-Driven Decision Making, Healthcare Analytics, Medical Informatics, Artificial Intelligence, Clinical Research, Computational Medicine, Evidence-Based Analysis, Machine Learning, Predictive Modeling, Scientific Research

Introduction

Data-Driven Decision Making has become increasingly significant across healthcare, biomedical research, and artificial intelligence applications. The integration of computational methodologies and clinical analytics supports informed decision processes, predictive healthcare strategies, and evidence-based scientific practices.[4]

JONG JIN OH has contributed to research activities involving analytical methodologies, healthcare-oriented computational systems, and scientific evaluation frameworks. Through publication dissemination and collaborative research participation, the researcher has established measurable scholarly visibility within indexed international databases.[1]

Research Profile

The research profile of JONG JIN OH demonstrates sustained scholarly engagement in Data-Driven Decision Making and interdisciplinary healthcare research. According to indexed bibliometric databases, the researcher has authored or co-authored 164 scientific documents and accumulated 2122 citations, resulting in an h-index of 25.[1] These metrics indicate substantial academic participation and research dissemination within international scientific communities.

  • Total indexed publications: 164
  • Total citations: 2122
  • h-index value: 25
  • Research specialization in Data-Driven Decision Making and healthcare analytics

Research Contributions

The scholarly contributions associated with JONG JIN OH include participation in analytical healthcare research, predictive methodologies, computational medical systems, and evidence-based clinical evaluation frameworks.[2] Research activities within these domains support advancements in healthcare optimization, decision-support technologies, and scientific data interpretation.

Data-driven methodologies play an increasingly important role in medical sciences by supporting diagnosis optimization, patient outcome prediction, and evidence-guided healthcare management. Such interdisciplinary approaches integrate statistical analysis, machine learning, and computational frameworks into modern clinical research environments.[5]

  • Contribution to healthcare-oriented analytical methodologies.
  • Participation in computational medical research initiatives.
  • Research involving evidence-based decision-support systems.
  • Scientific dissemination through indexed peer-reviewed publications.

Publications

The publication record associated with JONG JIN OH reflects extensive scholarly activity within healthcare analytics, computational medicine, and data-driven scientific evaluation. Indexed publications contribute to the dissemination of interdisciplinary analytical methodologies and evidence-based healthcare research.[1]

  1. Research articles related to healthcare analytics and computational medicine.
  2. Peer-reviewed studies involving predictive and evidence-based methodologies.
  3. Collaborative publications across interdisciplinary healthcare research domains.
  4. Scientific dissemination through indexed journals and conference proceedings.

Research Impact

Research impact can be evaluated through citation performance, publication dissemination, collaborative engagement, and interdisciplinary relevance. The academic profile associated with JONG JIN OH demonstrates substantial scholarly visibility through 2122 citations and an h-index of 25.[1]

These bibliometric indicators suggest sustained scientific recognition and continued participation in international healthcare and analytical research discourse. Citation accumulation within indexed databases reflects the relevance of the researcher’s contributions to computational and evidence-based scientific methodologies.

Award Suitability

The Best Researcher Award recognizes scholars demonstrating sustained academic productivity, measurable scientific impact, and interdisciplinary research excellence. JONG JIN OH’s research profile aligns with these criteria through publication productivity, citation performance, and contributions to healthcare-oriented Data-Driven Decision Making methodologies.[3]

Recognition through international academic award platforms supports broader scientific visibility and encourages continued innovation within healthcare analytics and evidence-based computational research. The researcher’s academic record reflects substantial engagement with interdisciplinary scientific advancement.

Conclusion

JONG JIN OH has established a distinguished academic profile through contributions to Data-Driven Decision Making, healthcare analytics, and computational medical research. Publication productivity, citation performance, and interdisciplinary collaboration demonstrate sustained scholarly engagement within international scientific communities. The Best Researcher Award recognizes these achievements and highlights the importance of analytical methodologies within evolving healthcare and computational research environments.[1]

References

  1. Elsevier. (n.d.). Scopus author details: JONG JIN OH, Author ID 24468588100. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=24468588100&source=sd-apx
  2. Seoul National University Bundang Hospital. (n.d.). Research and clinical innovation overview.
    https://www.snubh.org/
  3. International AI Data Scientists Award. (n.d.). International recognition framework for scientific excellence.
    https://aidatascientists.com/
  4. Provost, F., & Fawcett, T. (2013). Data Science and its relationship to big data and data-driven decision making.
    https://doi.org/10.1089/big.2013.1508
  5. Topol, E. (2019). High-performance medicine: the convergence of human and artificial intelligence.
    https://doi.org/10.1038/s41746-019-0195-0

Yanyu Wang | Innovation Management | Best Paper Award

Prof. Yanyu Wang | Innovation Management | Best Paper Award

Professor and The chair of the department at Beijing University of Posts and Telecommunications, China

Yanyu Wang currently serves as an Associate Professor and Supervisor of Master’s Candidates at the School of Economics and Management, Beijing University of Posts and Telecommunications. With a deep academic grounding in innovation strategy and enterprise digital transformation, Dr. Wang has established a reputation for advancing organizational studies within the realm of technology and management. Her research output, coupled with an active teaching portfolio, has positioned her as a leading voice in understanding how firms navigate complex innovation environments. Through her extensive academic career, she has remained committed to blending rigorous theoretical insights with practical applications that aid enterprises in addressing modern economic and technological challenges.

Profile

Scopus

Education

Yanyu Wang’s academic journey reflects a consistent pursuit of excellence and expertise across management disciplines. She earned her Ph.D. in Business Administration, focusing on Innovation, Entrepreneurship, and Strategy, from Tsinghua University, China, where she developed a strong research foundation in enterprise strategy and innovation systems. Prior to her doctoral studies, she completed an M.A. in Management Science and Engineering with a concentration in Quality Management at the Nanjing University of Aeronautics and Astronautics, China. Her academic journey commenced with a B.A. in Marketing from the same institution, where she was recognized as the top student in her cohort, having been admitted without examination. This diverse educational background provided her with a solid interdisciplinary understanding of technology management and business innovation.

Experience

Dr. Wang’s professional experience is rich and multifaceted, combining academic research, teaching, and international exposure. She has been serving as an Associate Professor since December 2019 and previously worked as a Lecturer from July 2016 to December 2019 at the School of Economics and Management, Beijing University of Posts and Telecommunications. Earlier, she broadened her academic horizons as a Visiting Scholar at the Rotman School of Management, University of Toronto, Canada, where she engaged with global scholars and enriched her perspectives on innovation strategy. Throughout her academic career, Dr. Wang has been deeply involved in delivering core courses such as Applied Statistics, Digital Innovation Strategy, and Corporate Technology Strategy, nurturing a new generation of business leaders and researchers.

Research Interest

Yanyu Wang’s research interests are primarily centered on innovation strategy, digital transformation of enterprises, and overseas R&D investments. She has explored how organizational characteristics, political influences, and policy interventions shape corporate innovation behaviors and strategies. Her work often adopts an interdisciplinary approach, merging concepts from organizational theory, strategic management, and technology studies to offer nuanced insights into enterprise growth and adaptation in dynamic environments. Dr. Wang is particularly interested in the imprinting effects of early-stage organizational experiences on long-term innovation outcomes, as well as the strategic considerations behind multinational enterprises’ R&D investments in foreign markets.

Award

Over the course of her career, Dr. Wang has received several prestigious honors recognizing her academic leadership and excellence. She was named a Youth Academic Leader by the Beijing Social Sciences Fund and recognized as a National Governance Youth Talent in Beijing. At the institutional level, she received multiple Outstanding Undergraduate Thesis Supervisor awards and was honored as an Advanced Individual of the School of Economics and Management. Her contributions to teaching were acknowledged with the First Prize and Second Prize in Teaching Achievements at BUPT. Additionally, during her doctoral studies at Tsinghua University, she was recognized as one of the Top 10 Academic Rising Stars, received the Outstanding Graduate Award, and won the First Prize for her Outstanding Doctoral Dissertation.

Publication

Yanyu Wang’s research contributions are reflected through impactful publications, often cited for their novel insights. Selected major works include:

“Policy Imprints: The impact of national innovation policy in firms’ founding period on subsequent innovation strategies,” published in R&D Management (2025, online);

“Visible hands: The impact of subsidy withdrawal on new energy vehicle enterprises’ innovation behaviors,” published in Energy Policy (2025, online);

“Excess IPO funds as an imprint: An imprinting perspective of acquisition activity,” in Asia Pacific Journal of Management (2023, early access);

“Political genes drive innovation: political endorsements and low-quality innovation,” in Structural Change and Economic Dynamics (2022, vol.60);

“Driving Factors of Digital Transformation for Manufacturing Enterprises: A Multi-case Study from China,” published in International Journal of Technology Management (2021, vol.87);

“What factors determine the subsidiary mode of overseas R&D by developing-country MNEs?” in R&D Management (2018, vol.48);

“Technological Capabilities, Political Connections and Entry Mode Choices of EMNEs Overseas R&D Investments,” published in International Journal of Technology Management (2019, vol.80); each of these articles has been cited in subsequent studies addressing corporate innovation strategies and digital enterprise development.

Conclusion

Dr. Yanyu Wang’s scholarly contributions in the fields of innovation strategy and digital transformation have established her as a significant figure in contemporary management research. By blending theoretical rigor with empirical investigation, she has provided valuable frameworks for understanding enterprise growth, technological capability development, and strategic adaptation. Her dedication to mentoring students, combined with her active research and participation in national-level projects, underscores her commitment to advancing academic and practical knowledge. Moving forward, her work promises to continue influencing both scholarly discussions and enterprise practices in the evolving digital economy landscape.