世界の主要大学の研究室を探索 — 研究分野と主要論文を一目で確認できます。
Professor Yong-Hoon Cho's research lab specializes in optoelectronic materials and nanophotonics, with a focus on nitride-based semiconductors such as InGaN/GaN multiple quantum wells for high-efficiency blue and white light emitters. The lab also investigates graphene-based quantum dots, particularly the role of oxygen functionalization in tuning their luminescent properties, and explores advanced photonic structures such as gallium nitride metasurfaces that leverage quasi-guided mode resonances for enhanced light manipulation. Their work bridges fundamental optoelectronic phenomena with practical applications in next-generation lighting and display technologies.
Professor Shin-Young Park's research lab specializes in regenerative medicine and biomaterials, with a focus on bone and periodontal tissue engineering. The lab investigates innovative strategies for bone regeneration using 3D-printed scaffolds, growth factors like BMP-2, and nanomaterials such as gold nanoparticles and polydopamine coatings. Key research directions include optimizing delivery systems for osteoinductive proteins, understanding molecular mechanisms in cellular signaling (e.g., RAFTK/Pyk2), and improving clinical outcomes in dental implantology and periodontal therapy through personalized, patient-specific solutions.
Professor Younghak Kim's research lab specializes in quantum materials and 2D magnetism, focusing on the emergence of topological spin textures, magnetic anisotropy, and exotic quantum phases in ultrathin and van der Waals layered materials. The lab investigates the interplay of electron correlation, spin-orbit coupling, and lattice effects to engineer novel spintronic and topological materials, including magnetic skyrmions, electrides, and doped transition metal dichalcogenides. A central theme is the atomic-scale control of magnetic properties—such as Curie temperature and anisotropy—through strain, doping, and growth engineering, enabling applications in next-generation spintronic and quantum devices.
Professor Joon Hwan Jang's research lab specializes in neuropsychiatry and neuroimaging, focusing on the neurobiological underpinnings of psychiatric disorders such as obsessive-compulsive disorder (OCD), schizophrenia, and prodromal psychosis. The lab employs advanced neuroimaging techniques—particularly structural and functional MRI—to investigate cortical morphology, brain connectivity, and neurodevelopmental abnormalities in key brain regions including the anterior cingulate cortex, insula, and thalamus. A central theme is understanding how early brain development and structural brain changes contribute to the onset and progression of psychiatric conditions.
Professor Hyuntae Park's research lab specializes in women's health, with a primary focus on the metabolic and cardiovascular implications of menopause and hormonal changes. The lab investigates the complex interplay between menopause, metabolic syndrome, obesity, and related disorders such as type 2 diabetes, fatty liver disease, and cardiovascular disease. Using large-scale population-based data and advanced analytical methods—including artificial intelligence—researchers explore risk factors, comorbidities, and early warning signs like vasomotor symptoms and uric acid levels. The lab also examines the impact of medical interventions, such as tamoxifen, on uterine and metabolic health in women with breast cancer.
Professor Jin Man Jeong's research lab specializes in cerebrovascular disease, with a focus on stroke mechanisms, secondary prevention, and prognostic prediction. The lab conducts clinical and translational research using advanced imaging, machine learning, and systematic reviews to improve outcomes in ischemic and hemorrhagic stroke. Key research directions include identifying predictors of stroke recurrence, evaluating the role of medications like cilostazol and statins, and assessing thrombolysis outcomes based on vascular territory. The lab emphasizes evidence-based approaches through multicenter registries and rigorous meta-analyses.
Professor So Yeon Jeon's research lab focuses on the neurobiological mechanisms underlying aging-related brain disorders, particularly Alzheimer’s disease and chronic pain syndromes. The lab employs advanced neuroimaging techniques—such as PET with specific radioligands (e.g., [11C]Pittsburgh compound-B, [11C]PK11195) and MRI—to investigate in vivo brain pathologies, including amyloid deposition, neuroinflammation, and white matter hyperintensities. A key research direction involves identifying modifiable lifestyle factors—such as coffee consumption, cognitive and physical activity, and caregiving stress—that influence the trajectory of neurodegeneration in aging populations. The lab also explores biomarkers and early disease predictors in non-demented older adults, aiming to improve early diagnosis and prevention strategies.
Professor Junyeop Lee's research lab specializes in computer vision and deep learning, with a strong focus on scene understanding, text recognition, and image super-resolution. The lab develops advanced neural network architectures for challenging tasks such as recognizing arbitrary-shaped text, enhancing low-resolution images, and editing scene text while preserving style. Their work emphasizes model generalization, efficiency, and real-world applicability, particularly in autonomous driving and mobile computing environments.
Professor Se-Young Yun's research lab specializes in the intersection of wireless networking, machine learning, and data science, with a focus on designing efficient and scalable systems for next-generation communication networks. The lab investigates fundamental problems in community detection and network clustering using statistical and spectral methods, while also exploring economic and game-theoretic models for resource allocation in femtocell and heterogeneous networks. Recent work emphasizes the application of deep learning to biomedical signal processing, particularly in respiratory sound classification for contact-free lung disease diagnosis. The lab combines theoretical rigor with practical applications, addressing challenges in data scarcity and system optimization through innovative algorithm design and model generalization.
Professor Se-Young Yun's research lab specializes in interdisciplinary research at the intersection of wireless communications, data science, and machine learning. The lab focuses on economic and game-theoretic modeling of next-generation wireless networks—particularly femtocell and small-cell systems—to optimize operator revenue, user satisfaction, and social welfare. It also explores advanced statistical and algorithmic methods for community detection in complex networks, leveraging spectral and learning-based approaches. Additionally, the lab applies deep learning and self-supervised representation learning to biomedical signal processing, especially in respiratory sound analysis for contact-free lung disease diagnosis.
Professor Ji Hyun Lee's research lab specializes in medical imaging and body composition analysis, focusing on the interplay between adiposity, muscle mass, and systemic inflammation in cancer patients. The lab investigates the obesity paradox in oncology using advanced imaging techniques such as MRI-electrical properties tomography (MR-EPT), micro-MRI, and quantitative CT to assess skeletal muscle and fat distribution. Their work spans multiple cancers, including melanoma, non-small cell lung cancer, and thyroid cancer, with an emphasis on prognostic biomarkers and personalized treatment strategies. The lab also explores tissue-level zonal differentiation in articular cartilage using multimodal imaging, contributing to orthopedic and rheumatic disease research.
Professor Insu Han's research lab specializes in computational modeling and optimization for industrial processes, with a strong focus on polymer processing, rubber curing, and large-scale matrix computations. The lab develops advanced numerical algorithms—such as randomized trace estimation, Chebyshev approximation, and stochastic methods—for efficient solution of large-scale problems in machine learning, materials science, and chemical engineering. Key research directions include black-box modeling of polymerization processes, dynamic optimization of curing cycles, and scalable computation of matrix functions like traces and log-determinants. The lab also contributes to analog circuit design, particularly in tunable transconductance amplifiers for low-power signal processing applications.
Professor Nam Yoonjae's research lab specializes in tourism behavior, digital media, and cultural consumption, with a focus on how technology and social media influence tourist decision-making, cultural perception, and sustainable tourism practices. The lab investigates the role of social networking sites, virtual reality, and user-generated content in shaping travel intentions, national image, and visitor satisfaction. It also examines longitudinal media adoption trends and the socio-cultural dimensions of urban tourism experiences such as graffiti tours.
Professor Min Soo Kim's research lab specializes in computational mechanics and fluid dynamics, with a focus on advanced numerical methods for simulating complex free-surface flows using the Volume of Fluid (VOF) method. The lab also engages in data-driven drug discovery through deep generative models, particularly conditional variational autoencoders (CVAE), to design novel molecular structures with desired pharmacological properties. In organizational psychology, the lab investigates interpersonal dynamics in the workplace, including psychological contracts, emotional labor, and job crafting, using mixed-methods and experience sampling approaches to capture real-time employee experiences. These interdisciplinary efforts reflect a strong commitment to solving practical challenges in engineering, healthcare, and organizational behavior through innovative modeling and empirical research.
Professor Hyun Oh Song's research lab specializes in deep learning for computer vision, with a strong focus on metric learning, domain adaptation, and weakly supervised object detection. The lab develops novel neural network architectures and training strategies that enhance generalization under distribution shifts, improve feature embedding quality, and enable effective learning from limited or noisy supervision. Key research directions include end-to-end learning of similarity metrics, unsupervised domain adaptation, and submodular optimization for weakly supervised instance segmentation and detection.
Professor Mi Seon Han's research lab focuses on pediatric infectious diseases, particularly the transmission dynamics, virological characteristics, and clinical manifestations of SARS-CoV-2 in children. Her work emphasizes viral persistence in various bodily fluids, including feces and saliva, and the role of asymptomatic or mildly symptomatic children in silent community transmission. The lab also investigates viral load kinetics in neonates and pediatric patients, contributing critical insights into infection control and public health strategies. These studies are pivotal in understanding pediatric contributions to SARS-CoV-2 spread and informing targeted interventions.
Professor Kyujeong Jeon's research lab specializes in computational materials science and machine learning for energy materials, with a focus on solid-state batteries, ion conductors, and interatomic potentials. The lab develops advanced machine learning interatomic potentials (MLIPs) such as CHGNet and investigates ion conduction mechanisms in solid electrolytes, including structural and dynamic factors that govern superionic conductivity. Their work bridges atomistic simulations, materials design, and experimental validation to address challenges in next-generation energy storage technologies.
Professor Ji-Young Park's research lab specializes in advanced materials development with a focus on sustainable photopolymer systems, functional nanomaterials for construction durability, and bioactive natural product applications. The lab investigates environment-friendly photolithography materials, including water-processable resists and holographic recording films, while also developing corrosion-resistant materials like calcium-iron layered double hydroxides for reinforced concrete. Additionally, the lab explores the biochemical mechanisms of traditional herbal extracts in relation to oxidative stress and aging-related enzymes. These interdisciplinary efforts bridge materials science, environmental sustainability, and biomedical applications.
Professor Chulhee Lee's research lab specializes in statistical signal processing, machine learning, and data-driven analysis with applications in speech recognition, hyperspectral image compression, and socioeconomic data analysis. The lab focuses on optimizing feature extraction and classification techniques—particularly using Gaussian models, mel-cepstrum transformations, and principal component analysis—while emphasizing information preservation and discriminative power in high-dimensional data. Additionally, the lab conducts empirical socioeconomic research, analyzing household income inequality and fertility trends using longitudinal and regional data, with a focus on structural and behavioral drivers of social change.
Professor Ji-Hoon Kim's research lab specializes in energy-efficient computing architectures and advanced memory technologies, with a focus on optimizing hardware for next-generation wireless communications and deep learning workloads. The lab develops innovative processing-in-memory (PIM) systems, such as Z-PIM, that enable flexible, low-power inference for deep neural networks through bit-serial arithmetic and sparse computation support. It also designs high-throughput, multi-standard turbo decoders for 4G and beyond, emphasizing hardware sharing and energy reduction. Additionally, the lab explores novel memory devices and biosensors, demonstrating expertise in both electronic systems and bio-integrated sensing technologies.
