ソウル大学、KAIST、延世大学など韓国QSトップ10大学の研究室情報です。
Professor Jang-hoon Kim's research lab specializes in cerebrovascular and spinal disorders, with a focus on hemodynamic mechanisms in intracranial aneurysms, clinical outcomes of acute ischemic stroke, and degenerative spinal conditions. The lab employs advanced imaging and computational fluid dynamics to investigate hemodynamic risk factors in aneurysm rupture and evaluates interventional strategies such as STA-MCA bypass for large vessel occlusion. It also explores clinical differentiation of subdural fluid collections in intracranial hypotension and the impact of cervical spine alignment on neck pain. The research integrates clinical neurology, neuroradiology, and biomechanical modeling to improve diagnosis and treatment of cerebrovascular diseases.
Professor Jungmo Yoon's research lab specializes in econometric methods and empirical industrial organization, with a strong focus on developing robust statistical techniques for panel data and quantile regression. The lab investigates the performance and governance of business groups—particularly Korean chaebols—through the lens of productivity, technological capabilities, and investment efficiency, especially in the context of economic crises and institutional change. It also contributes to legal and institutional economics by analyzing the impact of litigation rules, such as the English rule, on settlement outcomes and legal incentives. The lab's work bridges theoretical econometrics with real-world policy and firm-level performance analysis.
Professor Jeong-Kyung Lee's research lab focuses on microbial stress responses, particularly the molecular mechanisms underlying bacterial adaptation to oxidative and acid stress. The lab investigates regulatory systems involving transcription factors like CadC and SoxR, and their roles in controlling stress-responsive genes such as cadBA and MnSOD. A central theme is the interplay between metabolic pathways—especially lysine decarboxylation and cadaverine production—and redox homeostasis, with cadaverine shown to function as both a pH buffer and a superoxide scavenger. The lab also explores the role of key enzymes like chlorophyllide a reductase and superoxide dismutases in redox balance and photosynthetic metabolism under stress conditions.
Professor Taesik Gong's research lab specializes in mobile sensing and intelligent human-computer interaction, focusing on developing adaptive, context-aware systems that leverage deep learning and sensor technologies for real-world applications. The lab explores test-time adaptation, meta-learning, and on-device AI to address distribution shifts and individual variability in user behaviors and device characteristics. Key research directions include wearable sensing for health monitoring (e.g., eating detection), gesture and object recognition via passive sensing (e.g., knock-based interaction), and emoji recommendation in conversational AI, all aimed at creating efficient, personalized, and privacy-preserving mobile applications. The lab emphasizes practical deployment, energy efficiency, and robustness in real-world, non-i.i.d. environments.
Professor Eung-Joon Lee's research lab specializes in cerebrovascular and neurological disorders, with a focus on acute ischemic stroke, post-stroke complications, and the impact of systemic conditions on stroke outcomes. The lab investigates pre-hospital delay, biomarkers such as clonal hematopoiesis of indeterminate potential (CHIP), and renal dysfunction in relation to cerebral small vessel disease and stroke severity. It also explores mental health outcomes, particularly post-stroke and pandemic-related depression, using large-scale population-based data. The lab integrates clinical registries, genetic analysis, and neuroimaging to identify predictors and improve patient outcomes.
Professor Sun-Young Seo's research lab focuses on cancer stem cell biology, particularly in glioblastoma and salivary gland disorders, with an emphasis on molecular mechanisms driving tumorigenesis, therapy resistance, and tissue regeneration. The lab investigates key transcription factors such as SOX2, OCT4, and NANOG in cellular reprogramming and malignant transformation, as well as signaling pathways like Notch and TGF-β in tumor progression. Using integrative 'omics' approaches—transcriptomics, ChIP-seq, and proteomics—the lab aims to identify novel therapeutic targets and develop effective treatments for aggressive cancers, especially through targeting glioblastoma stem cells and modulating the tumor microenvironment. The lab also explores regenerative and anti-inflammatory strategies in salivary gland diseases using animal models and organoids.
Professor Byung Chul Cho's research lab specializes in clinical oncology and translational cancer research, with a focus on improving outcomes in aggressive malignancies such as anaplastic thyroid cancer, small cell lung cancer, and non-small cell lung cancer. The lab investigates prognostic biomarkers—such as C-reactive protein and EGFR gene polymorphisms—to guide personalized treatment strategies and enhance patient survival. It also explores cancer incidence and mortality in special populations, including patients on dialysis, and examines rare vascular anomalies that may contribute to cancer-related complications. The lab integrates clinical data with molecular analysis to support precision oncology and evidence-based treatment decisions.
Professor Seung-Moon Joo's research lab specializes in interventional radiology and hepatobiliary interventions, focusing on image-guided therapies for liver malignancies and biliary strictures. The lab investigates advanced embolization techniques such as transarterial chemoembolization (TACE) and novel stent technologies like fully covered self-expandable metal stents (FCSEMS) for refractory anastomotic biliary strictures after liver transplantation. Research also emphasizes the integration of advanced imaging software—such as FlightPlan for Liver—for improved tumor-feeding artery detection in cone-beam CT angiography, enhancing treatment precision. The lab's work consistently emphasizes clinical outcomes, safety, and patient-centered innovation in hepatobiliary disease management.
Professor Kyungjae Lee's research lab specializes in computer vision and machine learning with a focus on image and video understanding under challenging conditions. The lab explores thermal and infrared image enhancement, weakly-supervised anomaly detection, and heterogeneous face recognition to address domain shifts and limited supervision. Additionally, the lab investigates depth completion using sparse LiDAR and guided images, emphasizing robustness to degraded visual inputs. Their work bridges deep learning with real-world applications in autonomous systems, surveillance, and robotics.
Professor Jin Won Kim's research lab specializes in urban and environmental sociology, with a focus on spatial access to recreational resources, transnational cultural spaces in global cities, and the impact of socio-political disruptions—such as pandemics—on mental health and education. The lab also engages in cultural studies of folklore and narrative structures, particularly Russian heroic legends, and develops AI-driven tools for academic research support. Current research integrates qualitative and quantitative methods, including spatial analysis, discourse analysis, and machine learning applications in higher education.
Professor Taekyoon Kim's research lab focuses on global governance, development cooperation, and welfare politics with an emphasis on institutional resilience, accountability mechanisms, and state-society collaboration in development and crisis governance. The lab explores how democratic transitions, technological innovation, and civic engagement shape effective policy implementation, particularly in East Asian contexts such as South Korea. It also investigates the institutional design of international development cooperation frameworks, including post-2015 development agendas and Sustainable Development Goals (SDGs), with a critical lens on fragmentation and coordination challenges in global governance networks.
Professor Cheong Juyoung's research lab specializes in empirical international economics and educational psychology, with a strong focus on trade policy evaluation and adolescent development. The lab investigates the economic impacts of preferential trade agreements, particularly the estimation biases in trade creation and diversion effects, while also exploring longitudinal dynamics in students' self-regulated learning, stress, and academic outcomes. Using advanced econometric models such as multivariate latent growth curve models and cross-lagged panel models, the lab analyzes large-scale educational and trade datasets to uncover causal relationships and temporal dynamics.
Professor Jinwoo Park's research lab specializes in intelligent systems and human-centered computing, focusing on the integration of machine learning, computer vision, and embedded systems to solve real-world challenges in healthcare, mixed reality, and networking. The lab develops innovative solutions that combine deep learning with physical sensing—such as in wearable cardiovascular monitoring and real-time illumination estimation for augmented reality—while also advancing efficient and adaptive networking protocols using reinforcement learning. A recurring theme is creating seamless, immersive, and intelligent user experiences through minimal hardware intervention and high system autonomy.
Professor Jisun Kim's research lab specializes in educational psychology and language education, with a strong focus on promoting learner autonomy and reflective thinking in second language learning contexts. The lab explores innovative pedagogical models such as blended learning, collaborative learning, and metacognitive strategy development, particularly in Japanese language education. It also investigates practical tools for youth empowerment, including standardized assessment instruments for at-risk youth, and engages in interdisciplinary studies on cultural and aesthetic values in historical Chinese texts. The lab emphasizes the design and validation of educational tools that support self-regulated learning and social-emotional development.
Professor Woo Young Kang's research lab specializes in medical imaging and geriatric health, focusing on the application of artificial intelligence—particularly deep learning—in diagnostic imaging for aging populations and musculoskeletal disorders. The lab conducts population-based studies on frailty and geriatric syndromes in rural communities, while also advancing automated, AI-driven quantitative imaging techniques such as deep learning-based bone mineral density (BMD) measurement from routine CT scans. Their work bridges clinical geriatrics with cutting-edge medical image analysis, aiming to improve early detection of osteoporosis and spinal conditions through non-invasive, opportunistic screening methods. The lab also explores smart materials and structural actuation using piezoelectric polymers, demonstrating interdisciplinary innovation in biomedical engineering.
Professor Sinhaen Han's research lab specializes in higher education policy, teacher education, and innovative pedagogical practices. The lab focuses on enhancing teaching effectiveness through evidence-based reforms in university course evaluation, teacher recruitment systems like principal selection by competition, and the implementation of student-centered learning models such as problem-based learning. A central theme is improving educational quality and institutional accountability by strengthening faculty development, teacher readiness, and inclusive education practices.
Professor Suk-Kyu Lee's research lab specializes in consumer behavior and marketing strategy, with a strong focus on customer reward programs and their psychological underpinnings. The lab investigates how reward design—particularly the type, timing, and selection criteria of rewards—affects customer loyalty, preference, and brand engagement across different consumer segments. Key research directions include the impact of utilitarian versus hedonic reward attributes, effort-reward consistency, and situational factors such as user status (e.g., potential vs. loyal customers) on reward preference and program effectiveness.
Professor Heon Gil Lim's research lab focuses on cardiovascular and metabolic health, with a strong emphasis on the interplay between arterial stiffness, blood pressure variability, and target organ damage in hypertension and diabetes. The lab investigates biomarkers and clinical parameters—such as the Augmentation Index (AASI), bone mineral density (BMD), and left ventricular mass—across diverse populations to improve risk prediction and understanding of cardiovascular outcomes. Key research directions include the pathophysiology of diabetic cardiomyopathy, the impact of chronic diseases on health-related quality of life, and the role of systemic factors in vascular and cardiac remodeling.
Professor Won-Sang Jeong's research lab specializes in surgical innovation and experimental transplantation, with a focus on minimally invasive robotic surgery and microsurgical techniques. The lab investigates advanced approaches in thyroid and gastrointestinal surgery, including robotic thyroidectomy using novel access routes, and explores long-term outcomes of organ transplantation in animal models. Research also extends to rare thoracic and esophageal pathologies, such as traumatic pulmonary pseudocysts and phlegmonous esophagogastritis, emphasizing radiological diagnosis and clinical management. The lab’s work bridges experimental surgery with translational applications, particularly in urological and reproductive organ transplantation.
Professor Hui Yong Kim's research lab specializes in next-generation video coding and perceptual quality assessment, with a strong focus on optimizing compression efficiency for both human visual quality and machine vision applications. The lab explores advanced coding techniques for high-efficiency video coding (HEVC/VVC), including perceptual artifact reduction, false contour detection, and frame-rate adaptation based on human perception. A key direction involves video coding for machine (VCM), where compression is tailored to preserve machine-readable features rather than human visual fidelity, especially in deep learning-driven vision systems. The lab also investigates holographic video compression, addressing the unique challenges of compressing massive computer-generated hologram data for 3D display applications.
