Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani, Undergraduate Researcher, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Ms. Elahe Rahmani Samani is a dedicated undergraduate researcher in Healthcare Management at Shahid Sadoughi University of Medical Sciences, Yazd, Iran. With a strong commitment to advancing health systems through innovative technologies, she has emerged as a promising young voice in the intersection of healthcare and artificial intelligence. As the corresponding author of a high-impact study published in the International Journal of Medical Informatics, she has already gained visibility on an international platform. Elahe is also an editorial board member of a university-affiliated journal and actively engages in research collaboration, demonstrating leadership and academic excellence early in her career.

Publication Profile

ORCID

๐ŸŽ“ Education Background

Ms. Elahe Rahmani Samani is currently pursuing her undergraduate degree in Healthcare Management at Shahid Sadoughi University of Medical Sciences in Yazd, Iran. Her academic journey has been marked by an early passion for healthcare innovation and policy development. As a student member of the Health Policy and Management Research Center, she has access to extensive research mentorship and academic resources, which support her pursuits in AI integration in health systems. Her education equips her with both practical management knowledge and technical understanding essential for modern health leadership. She continues to excel academically, contributing meaningfully to her institutionโ€™s research mission.

๐Ÿ’ผ Professional Experience

Although still an undergraduate student, Ms. Rahmani Samani has demonstrated remarkable initiative by leading and collaborating on several research projects. Her standout experience includes serving as the primary researcher and corresponding author for a study on AI adoption in hospital settings, presented at the International Congress on Artificial Intelligence in Health. She also serves on the editorial board of a university-affiliated journal, where she helps shape academic content for peer learning. Elaheโ€™s active involvement in health systems projects, poster sessions, and ongoing collaborations reflect her deep engagement with practical and theoretical aspects of healthcare management.

๐Ÿ† Awards and Honors

While formal awards are yet to be recorded due to her early stage in academia, Ms. Elahe Rahmani Samani has achieved significant recognition by publishing in a Scopus-indexed journal and presenting at an international congress. She earned certificates of participation from the International Congress on Artificial Intelligence in Health and is continuously contributing to scholarly work in health systems. Her selection for the editorial board role and involvement in a university-level book project highlight the academic communityโ€™s acknowledgment of her talents. Her publication is already accessible through global platforms and is poised to gain academic citations in the near future.

๐Ÿ”ฌ Research Focus

Elahe Rahmani Samaniโ€™s research interests revolve around hospital and healthcare management, particularly in leveraging artificial intelligence to optimize health systems for both patients and staff. She has successfully completed one major research project that analyzes hospital managers’ perspectives on AI integrationโ€”an innovative topic reflecting current global trends. Her work aims to influence strategic decision-making within health institutions by promoting the adoption of intelligent systems. She is also contributing to an ongoing book project in healthcare management and continues to work on four other health-related research studies, exploring themes of efficiency, technology adoption, and patient-centered care in health policy.

๐Ÿงญ Conclusion

Ms. Elahe Rahmani Samani exemplifies the drive and intellect of a next-generation healthcare researcher. Her early publication in a high-impact journal and involvement in both local and international academic platforms underscore her potential to become a leader in the field. With a unique blend of management insight and technological perspective, she aims to transform how healthcare institutions approach innovation. Her commitment to research excellence, combined with her growing professional network and academic contributions, positions her as a strong contender for the Young Researcher Award. Her journey is only beginning, and she is already contributing to global discussions in health innovation.

๐Ÿ“š Top Publication Note

Title: Managersโ€™ perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings
Authors: Mousavi SM, RahmaniSamani E, Raadabadi M, DehghaniTafti A
Journal: International Journal of Medical Informatics
Year: 2025

Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

Assist. Prof. Dr. Yuchae Jung, Open Cyber University of Korea , South Korea.

Dr. Yuchae Jung is an accomplished Affiliated Professor at KAIST School of Computing, Seoul, South Korea. With an interdisciplinary background spanning computer science, medical sciences, and artificial intelligence, she brings a unique integration of biomedical knowledge and computational innovation to her research. Over the years, Dr. Jung has held key academic and research roles in prestigious institutions, including Harvard Medical School and State University of New York. Her professional journey reflects a strong commitment to advancing digital healthcare, AI-driven diagnostics, and computational biology. ๐Ÿง ๐Ÿ’ป๐Ÿงฌ

Professional Profile

Google Scholar

๐ŸŽ“ Education Background

Dr. Jung earned her Ph.D. and M.S. in Medical Science from The Catholic University of Korea (2008, 2002), following her undergraduate degree in Computer Science from Sookmyung Womenโ€™s University in 2000. This solid academic foundation has enabled her to contribute innovatively to both computer science and medical informatics. ๐ŸŽ“๐Ÿ“š

๐Ÿงช Professional Experience

Dr. Jung is currently affiliated with KAISTโ€™s School of Computing as a professor. She has previously held significant roles at The Catholic University of Korea, Boin IT, Seoul National University, and Sookmyung Womenโ€™s University. She has also conducted postdoctoral research at Brigham & Womenโ€™s Hospital (Harvard Medical School) and State University of New York. Her professional engagements include lectures, research leadership, and AI-based system development across medical and computing fields. ๐Ÿฅ๐Ÿ–ฅ๏ธ๐Ÿ“Š

๐Ÿ… Awards and Honors

Dr. Jung has been the Principal Investigator of several prestigious grants from organizations such as the Ministry of SMEs and Startups, National Library of Korea, Ministry of Science, and Ministry of Education. Her projects span from NLP-based clinical dialogue systems to cancer therapy algorithms and bioinformatics applications in glioblastoma research. She was also honored as a keynote speaker by The Korean Society of Pathologists. ๐Ÿ†๐Ÿ“œ๐Ÿ‡ฐ๐Ÿ‡ท

๐Ÿ”ฌ Research Focus

Her core research interests lie in Medical AI, including deep transfer learning for digital pathology image analysis, clinical Natural Language Processing (Bio-NLP), and cancer genomics (TFs, repeat sequences, miRNAs). She also explores gene expression network analysis in cancer and functional informatics for precision diagnostics. Her work bridges cutting-edge AI with real-world healthcare applications. ๐Ÿงฌ๐Ÿค–๐Ÿ“ˆ

โœ… Conclusion

Dr. Yuchae Jung is a pioneering figure in interdisciplinary AI and bioinformatics, contributing impactful research to cancer genomics and healthcare AI. With a dynamic academic trajectory and a clear focus on translational science, she continues to be a driving force in computational medicine and smart health systems. Her extensive contributions position her as a deserving candidate for recognition in digital healthcare innovation. ๐ŸŒ๐Ÿ’ก๐Ÿ‘ฉโ€โš•๏ธ

๐Ÿ“ Top Publications Highlights

  1. Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning
    ๐Ÿ“… Published: 2021 in MDPI Sensors
    ๐Ÿ“Š Cited by: 39 articles (Google Scholar)
    ๐Ÿ” A groundbreaking study applying deep transfer learning for pathology image classification.

  2. Impact of tumor purity on immune gene expression and clustering analyses across multiple cancer types
    ๐Ÿ“… Published: 2018 in Cancer Immunology Research
    ๐Ÿ“Š Cited by: 107 articles
    ๐Ÿ”ฌ Investigates how tumor purity affects gene expression in cancer immunology.

  3. Hybrid-Aware Model for Senior Wellness Service in Smart Home
    ๐Ÿ“… Published: 2017 in MDPI Sensors
    ๐Ÿ“Š Cited by: 25 articles
    ๐Ÿก Explores smart health monitoring using a hybrid AI model in smart homes.

  4. Aneuploidy meets network analysis: leveraging copy number alterations
    ๐Ÿ“… Published: 2017 in Translational Cancer Research
    ๐Ÿ“Š Cited by: 15 articles
    ๐Ÿงฌ Integrates systems biology with cancer genomics.

  5. Cancer stem cell targeting: Are we there yet?
    ๐Ÿ“… Published: 2015 in Archives of Pharmacal Research
    ๐Ÿ“Š Cited by: 55 articles
    ๐Ÿ’ก Reviews strategies to target elusive cancer stem cells.

  6. Systemic approaches identify Z-ajoene as a GBM stem cell-specific targeting agent
    ๐Ÿ“… Published: 2014 in Molecules and Cells
    ๐Ÿ“Š Cited by: 40+ articles
    ๐Ÿงช Identifies garlic-derived compound with anti-glioblastoma activity.

  7. Numb regulates glioma stem cell fate and growth
    ๐Ÿ“… Published: 2012 in Stem Cells
    ๐Ÿ“Š Cited by: 100+ articles
    ๐Ÿ“ˆ A critical study in stem cell regulation in glioma.

  8. GEAR: Genomic Enrichment Analysis of Regional DNA Copy Number Changes
    ๐Ÿ“… Published: 2008 in Bioinformatics
    ๐Ÿ“Š Cited by: 80+ articles
    ๐Ÿงฌ Proposes a novel method for regional DNA copy number analysis.

  9. DNA methylation patterns of ulcer-healing genes in gastric cancers
    ๐Ÿ“… Published: 2010 in Journal of Korean Medical Science
    ๐Ÿ“Š Cited by: 35 articles
    ๐Ÿ”ฌ Connects epigenetics with cancer pathology.

  10. PathCluster: a framework for gene set-based hierarchical clustering
    ๐Ÿ“… Published: 2008 in Bioinformatics
    ๐Ÿ“Š Cited by: 90+ articles
    ๐Ÿ“‚ Presents a tool widely adopted in gene expression analysis.