Seung-Woo Baek received his Ph.D. in Bioinformatics from the University of Science and Technology (UST) in 2022. He is currently an Associate Researcher at the Korea Research Institute of Bioscience and Biotechnology (KRIBB), where he focuses on precision oncology and AI-driven biomedical research. His work integrates multi-omics data, medical imaging, and clinical information to identify prognostic biomarkers and predict therapeutic responses, particularly in bladder cancer and metabolic disease-associated cancers. He has contributed to the development of machine learning and deep learning frameworks, including transformer-based models and multimodal analysis pipelines, for cancer subtype classification and treatment response prediction. Dr. Baek has published over 10 peer-reviewed articles and holds multiple patent applications in cancer biomarker discovery. His current research interests include multi-modal AI for precision medicine, tumor microenvironment analysis, and next-generation computational models such as large language models and quantum machine learning for biological data analysis.
Seung-Woo Baek received his Ph.D. in Bioinformatics from the University of Science and Technology (UST) in 2022. He is currently an Associate Researcher at the Korea Research Institute of Bioscience and Biotechnology (KRIBB), where he focuses on precision oncology and AI-driven biomedical research. His work integrates multi-omics data, medical imaging, and clinical information to identify prognostic biomarkers and predict therapeutic responses, particularly in bladder cancer and metabolic disease-associated cancers. He has contributed to the development of machine learning and deep learning frameworks, including transformer-based models and multimodal analysis pipelines, for cancer subtype classification and treatment response prediction. Dr. Baek has published over 10 peer-reviewed articles and holds multiple patent applications in cancer biomarker discovery. His current research interests include multi-modal AI for precision medicine, tumor microenvironment analysis, and next-generation computational models such as large language models and quantum machine learning for biological data analysis.