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. πŸ§ πŸ’»πŸ§¬

Professional Profile

Google Scholar

πŸŽ“ 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 Women’s University in 2000. This solid academic foundation has enabled her to contribute innovatively to both computer science and medical informatics. πŸŽ“πŸ“š

πŸ§ͺ Professional Experience

Dr. Jung is currently affiliated with KAIST’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 Women’s University. She has also conducted postdoctoral research at Brigham & Women’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. πŸ₯πŸ–₯οΈπŸ“Š

πŸ… 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. πŸ†πŸ“œπŸ‡°πŸ‡·

πŸ”¬ 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. πŸ§¬πŸ€–πŸ“ˆ

βœ… 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. πŸŒπŸ’‘πŸ‘©β€βš•οΈ

πŸ“ Top Publications Highlights

  1. Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning
    πŸ“… Published: 2021 in MDPI Sensors
    πŸ“Š Cited by: 39 articles (Google Scholar)
    πŸ” 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
    πŸ“… Published: 2018 in Cancer Immunology Research
    πŸ“Š Cited by: 107 articles
    πŸ”¬ Investigates how tumor purity affects gene expression in cancer immunology.

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

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

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

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

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

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

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

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

 

Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

Dr. Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

lecturer, iran university of science and technology, Iran

Seyed Abolfazl Aghili is a passionate civil engineer with a strong focus on construction engineering and management. With a Ph.D. in Civil Engineering from the prestigious Iran University of Science and Technology (IUST), he specializes in using artificial intelligence for enhancing the resilience of HVAC systems in hospitals. His research integrates cutting-edge technologies such as machine learning and deep learning to optimize building systems and improve decision-making in construction projects. Seyed’s dedication to his field has earned him a reputation as a driven academic and professional in the civil engineering community. πŸ—οΈπŸ€–

Publication Profile

ORCID

Education Background

Seyed Abolfazl Aghili completed his Ph.D. in Civil Engineering with a specialization in Construction Engineering and Management from Iran University of Science and Technology (IUST) between 2019 and 2024. His doctoral thesis focused on developing a framework to assess the long-term resilience of hospital air conditioning systems using artificial intelligence. Prior to that, he earned his M.Sc. in Civil Engineering with a focus on Construction Engineering and Management at IUST, where he investigated employee selection methods in construction firms. He also holds a B.Sc. in Civil Engineering from Isfahan University of Technology (IUT). πŸŽ“πŸ“š

Professional Experience

Seyed Abolfazl Aghili has extensive experience in both academic research and practical applications of civil engineering, particularly in construction management. He has worked on various projects involving energy management, risk management, and resilience within the construction industry. His academic journey has seen him contribute significantly to the research community, particularly in the areas of AI in construction systems and HVAC performance. Furthermore, he has been an integral part of various conferences and publications, sharing his insights on improving construction management processes through technology. πŸ’ΌπŸ’

Awards and Honors

Seyed Abolfazl Aghili has earned several prestigious awards throughout his academic journey. He was ranked 5th among 2200 participants in the Nationwide University Entrance Exam for the Ph.D. program in Iran in 2019. Additionally, he ranked 2nd among all construction management students at Iran University of Science and Technology during his M.Sc. studies. He was also ranked in the top 1% (220th out of 32,663) in the Nationwide University Entrance Exam for the M.Sc. program in Iran in 2013. πŸ†πŸ₯‡

Research Focus

Seyed’s primary research interests lie in the application of machine learning and deep learning techniques in construction engineering. His work focuses on enhancing the resilience of building systems, especially HVAC systems in healthcare settings. He also explores risk management, sustainability, lean construction, and decision-making systems for project managers. His interdisciplinary research combines civil engineering with advanced AI methodologies, driving innovations in construction management and systems optimization. πŸ”πŸ’‘

Conclusion

Seyed Abolfazl Aghili’s academic and professional journey reflects his commitment to advancing civil engineering through innovative solutions. His focus on integrating artificial intelligence into construction systems is helping to create smarter, more sustainable, and resilient built environments. Through his work, he continues to contribute valuable insights to both the academic world and the practical sector of construction engineering. πŸŒπŸ”§

Publications Top Notes

Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review. Journal of Buildings, 15.7 (2025).

Data-driven approach to fault detection for hospital HVAC system. Journals of Smart and Sustainable Built Environment, ahead-of-print (2024).

Feasibility Study of Using BIM in Construction Site Decision Making in Iran. International Conference on Civil Engineering, Architecture and Urban Infrastructure, July 2015.

Review of digital imaging technology in safety management in the construction industry. 1st National Conference on Development of Civil Engineering, Architecture, Electricity and Mechanical in Iran (December, 2014).

The role of insurance companies in managing the crisis after earthquake. 1st National Congress of Engineering, Construction, and Evaluation of Development Projects, May 2013.

The need for a new approach to pre-crisis and post-crisis management of earthquake. 1st National Conference on Seismology and Earthquake, February 2013.