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 Eun Kyoung Seo's research lab specializes in natural product chemistry and neuropharmacology, focusing on the isolation, structural elucidation, and biological evaluation of bioactive compounds from medicinal plants. The lab investigates the neuroprotective and anticancer properties of natural molecules, particularly resveratrol derivatives, xanthones, and phenylbutenoids, with an emphasis on their mechanisms in treating neurodegenerative diseases and cancer. The research also integrates advanced analytical techniques such as NMR, FT-IR, and bioassay-guided fractionation to bridge natural product discovery with therapeutic applications.
Professor Seung-Yeop Kwak's research lab specializes in the design and fabrication of advanced functional materials for environmental and energy applications. Key research directions include the development of novel thin-film composite membranes for water purification, with a focus on enhancing permeability and anti-fouling properties through nanomaterial integration. The lab also pioneers the synthesis of mesoporous and quantum-sized materials—such as TiO₂, hematite, magnetite, and carbon quantum dots—for efficient photocatalytic degradation of pollutants and improved performance in separation processes. Additionally, the group explores sustainable polymer additives, exemplified by phthalate-free plasticizers for flexible PVC, reflecting a commitment to green chemistry and materials innovation.
Professor Young Min Rhee's research lab specializes in theoretical and computational chemistry, with a focus on quantum chemical methods for excited states and nonadiabatic processes. The lab develops advanced electronic structure methods—such as SCS-CIS(D) and SOS-CIS(D)—to improve the accuracy of excited-state calculations, particularly for systems with strong electron correlation and spin-fluctuation effects. A key research direction involves understanding reverse intersystem crossing (RISC) dynamics in thermally activated delayed fluorescence (TADF) materials, aiming to enable rational design of high-efficiency organic light-emitting diodes (OLEDs). The lab also investigates the role of solvent, especially water, in biomolecular processes like protein folding, using explicit-solvent molecular dynamics simulations to probe the microscopic origins of hydration and hydrophobic effects.
Professor Danbee Kang's research lab focuses on the psychosocial and metabolic factors influencing long-term health outcomes in chronic disease survivors, particularly in oncology and metabolic health. The lab investigates the psychological impact of treatment-related sequelae—such as chemotherapy-induced alopecia—and explores how stress, hope, and life purpose affect quality of life and disease progression. A key research direction involves understanding the role of perceived stress in the development of non-alcoholic fatty liver disease (NAFLD) among apparently healthy populations. The lab integrates epidemiological, psychological, and clinical data to inform patient-centered interventions and improve long-term well-being.
Professor Hoo-Jeong Lee's research lab specializes in the development and characterization of advanced functional thin films and nanostructured materials for microscale and nanoscale applications. The lab focuses on understanding the structure-property relationships in materials such as NiTi shape memory alloys, aluminum-based alloys, and graphene-supported electrocatalysts, with an emphasis on in situ microscopy and mechanical testing at the micro/nano scale. Key research directions include phase transformation kinetics, grain growth dynamics, and the design of high-performance electrocatalysts for sustainable energy applications.
Professor Youjae Yi's research lab specializes in consumer behavior, with a focus on how contextual factors, cognitive and emotional priming, and social influences shape consumer evaluations and decision-making. The lab investigates the role of expectations, loyalty, prior knowledge, and interpersonal dynamics—particularly the influence of other customers—in determining brand attitudes and repurchase intentions. Key research directions include the impact of ad context on interpretation of ambiguous product information, the mediating role of adjusted expectations, and the effects of social information and identity on customer citizenship behavior.
Professor Chang Yun Son's research lab specializes in computational and molecular-level studies of ion transport, electrostatic interactions, and interfacial phenomena in complex electrolyte systems, with a focus on energy storage materials such as solid-state and high-concentration liquid electrolytes, ionic liquids, and charged block copolymers. The lab develops advanced atomistic and polarizable molecular dynamics models to understand and predict ion dynamics, phase behavior, and interfacial structuring in confined and heterogeneous environments relevant to batteries and bioelectrochemical systems. A key emphasis is placed on bridging simulation methodologies with experimental validation to guide the design of next-generation electrolytes with enhanced ionic conductivity and stability.
Professor Sung Oh Cho's research lab specializes in the design, synthesis, and application of advanced nanomaterials for energy and environmental technologies. Key research directions include plasmonic photocatalysts for solar energy conversion, quantum dot-sensitized photoelectrodes for solar fuel generation, and nanostructured materials for hydrogen storage and superhydrophobic surfaces. The lab employs innovative fabrication techniques such as sonochemistry, electron beam irradiation, and solution-based deposition to create functional nanoarchitectures with tunable optical, electronic, and surface properties.
Professor Ho Lee's research lab specializes in medical imaging, computational modeling, and energy systems, with a focus on advancing diagnostic technologies and energy recovery. The lab develops innovative deep learning and signal processing techniques for medical image analysis—particularly in chest X-ray and cone-beam CT—enabling low-dose, high-accuracy imaging for disease detection. It also explores laser-tissue interactions for ophthalmic therapies and designs efficient thermodynamic cycles for recovering low-grade heat and cold energy. The integration of AI, imaging science, and sustainable energy systems defines the lab’s interdisciplinary approach.
Professor Yongseok Hong's research lab specializes in environmental chemistry and biogeochemistry, focusing on the fate, transformation, and toxicity of mercury and other contaminants in aquatic and terrestrial ecosystems. The lab investigates mercury methylation, speciation, and biomagnification in food webs, particularly in coastal and estuarine environments such as Sarasota Bay and the Mekong Delta. Key research directions include the role of microbial communities in mercury cycling, the impact of geochemical conditions on metal speciation, and the development of advanced monitoring techniques for trace metals and plasticizers in sediments and water. The lab also explores innovative solutions for mercury control in industrial wastewater and air emissions, emphasizing the formation and re-emission of volatile mercury species.
Professor Baek Hwan Cho's research lab specializes in the development and application of advanced machine learning and artificial intelligence techniques in medical imaging and cognitive neuroscience. The lab focuses on leveraging deep learning, support vector machines, and novel kernel methods for accurate medical diagnosis and risk factor analysis, particularly in ophthalmology, cardiology, and musculoskeletal radiology. A key research direction involves integrating virtual reality and neurofeedback for non-invasive cognitive training and attention enhancement in adolescents. The lab also emphasizes interpretability and clinical usability of AI models through innovative visualization tools such as nomograms and localized kernel functions.
Professor Jong Hoon Ryu's research lab specializes in neuropharmacology and neuroinflammation, focusing on the therapeutic potential of natural compounds in neurological disorders. The lab investigates how bioactive phytochemicals, such as eupatilin and tanshinone I, modulate microglial activation and neuroinflammatory pathways to exert neuroprotective effects. Current research directions include elucidating the molecular mechanisms of these compounds in stroke (e.g., focal cerebral ischemia) and cognitive impairment models, particularly through modulation of intracellular signaling pathways like ERK. The lab also explores the role of microglia in neurodegenerative and neurodevelopmental conditions, aiming to develop natural product-based therapies.
Professor Seokhee Kim's research lab specializes in the discovery, characterization, and engineering of natural products, with a focus on ribosomally synthesized and post-translationally modified peptides (RiPPs). The lab investigates the enzymatic mechanisms underlying complex macrocyclic and biaryl linkages in natural products, particularly those catalyzed by cytochrome P450 enzymes and other tailoring enzymes. Using a combination of genomics, biochemistry, structural biology, and synthetic biology, the lab explores the biosynthesis of diverse natural products with potential therapeutic applications, including antibiotics and bioactive peptides. They also develop innovative tools for in vivo protein evolution to accelerate the discovery and optimization of novel enzymes and biomolecules.
Professor Seong-Mi Park's research lab focuses on molecular mechanisms underlying cancer progression and treatment resistance, with a central emphasis on signaling pathways involving NF-κB, p53, mTOR, and RIP1. The lab investigates how key regulatory proteins such as receptor-interacting protein 1 (RIP1) modulate tumor suppressor functions and oncogenic signaling, particularly in glioblastoma and other malignancies. Additional research explores translational control via internal ribosomal entry sites (IRES) and their role in viral and cellular gene expression. The lab also examines cardiovascular implications of molecular signaling, including arterial stiffness and endothelial dysfunction in hypertension.
Professor Jaekyeong Kim's research lab specializes in data-driven intelligent systems with a focus on natural language processing, computer vision, and machine learning applications in real-world domains such as human resource management, travel recommendation, advertising, and healthcare. The lab develops advanced recommender systems that integrate multimodal data—text, images, and facial expressions—while emphasizing semantic understanding, sentiment analysis, and user preference modeling. A key research direction involves overcoming data sparsity and improving prediction accuracy by leveraging complementary information from diverse data sources and enhancing the consistency between textual reviews and numerical ratings.
Professor Bombi Lee's research lab focuses on the neuropharmacological mechanisms underlying neuropsychiatric disorders, with a primary emphasis on neuroinflammation, neurotrophic factors, and monoaminergic systems. The lab investigates natural compounds—such as berberine, quercetin, baicalein, and acupuncture—to understand their potential in treating cognitive deficits, depression, anxiety, and stress-related disorders. Key research directions include modulating the HPA axis, cholinergic function, BDNF/CREB signaling, and pro-inflammatory cytokines in rodent models of neurodegeneration and psychiatric disease. The lab integrates behavioral tests, neurochemical analyses, and molecular biology to identify novel therapeutic targets and mechanisms.
Professor Eun-Jung Park's research lab focuses on molecular mechanisms underlying inflammatory diseases, DNA repair, and metabolic disorders, with a particular emphasis on transcriptional regulation, stem cell therapy, and natural product discovery. The lab investigates the therapeutic potential of PPAR-gamma agonists in neuroinflammation, explores adipose-derived stem cells for regenerative medicine in conditions like Parry-Romberg disease, and examines the role of chromatin structure in DNA double-strand break repair. Additionally, the lab studies bioactive compounds from medicinal plants for their antioxidant and cytoprotective properties, and evaluates probiotics in non-alcoholic fatty liver disease. These interdisciplinary efforts integrate molecular biology, stem cell biology, and natural product chemistry to develop novel therapeutic strategies.
Professor Hyo Suk Nam's research lab specializes in clinical and translational research focused on stroke outcomes, cardiovascular disease biomarkers, and predictive modeling. The lab investigates pathophysiological mechanisms such as trimethylamine N-oxide (TMAO) in atherosclerosis and post-stroke prognosis, integrating biomarkers with clinical data. Using advanced statistical methods like Bayesian networks, the lab develops interpretable, high-accuracy prediction models for functional outcomes and mortality after stroke, aiming to improve clinical decision-making. The research also emphasizes quality improvement in stroke care through implementation of clinical decision support systems.
Professor Sang Woo Kim's research lab specializes in intelligent fault diagnosis and condition monitoring, with a strong focus on advanced signal processing, machine learning, and deep learning techniques for industrial applications. The lab develops innovative methods for defect detection in steel surfaces using optimized lighting and filtering, diagnostic systems for lithium-ion batteries combining capacity and fault co-diagnosis, and novelty detection frameworks for soft fault identification in electrical systems. Their work bridges theoretical advancements in algorithms—such as recursive prototype reduction and analysis of convolutional neural network behavior—with practical solutions in manufacturing and energy systems.
Professor Soohee Han's research lab specializes in advanced battery management systems and intelligent estimation techniques for electrochemical energy storage systems, with a strong focus on state-of-charge (SOC) and state-of-health (SOH) estimation. The lab integrates model-based approaches with data-driven methods such as machine learning and reinforcement learning to enhance accuracy and robustness under real-world operating conditions. It also develops efficient software platforms for robotics and control systems, emphasizing real-time performance, system integration, and simulation-driven development. The lab’s work bridges theoretical modeling with practical applications in electric vehicles, energy storage, and autonomous systems.
