首尔大学、KAIST、延世大学等韩国QS前10名大学的研究室信息。
Professor Minsoo Park's research lab specializes in leveraging artificial intelligence, particularly deep learning and computer vision, to address critical environmental and societal challenges. The lab focuses on early detection and monitoring of wildfires, construction site safety through advanced object detection, and climate-related disaster prediction using big data analytics. Key research directions include developing robust AI models for small and overlapping object detection, addressing data imbalance in imbalanced datasets via generative models like CycleGAN, and creating multilabel classification systems for comprehensive disaster response. The lab emphasizes real-world applicability, integrating transfer learning, data augmentation, and explainable AI to enhance model performance and reliability in complex, dynamic environments.
Professor Ki-Suk Lee's research lab specializes in spintronics and nanomagnetic systems, focusing on the manipulation of spin waves and magnetic vortices for next-generation ultrafast and energy-efficient logic and memory devices. The lab investigates traveling spin waves in magnonic crystals and interferometric structures for reconfigurable logic gates, while also exploring ultrafast vortex-core switching dynamics driven by tailored magnetic fields. A key research direction involves designing functional nanostructures—such as conductivity-gradient hosts—for stable lithium-metal anodes in high-energy-density batteries, bridging spintronic and energy storage applications. The lab combines micromagnetic simulations, analytical modeling, and experimental validation to uncover fundamental mechanisms in dynamic magnetic phenomena.
Professor Ja Yil Lee's research lab specializes in single-molecule biophysics, focusing on the dynamic structures and functional mechanisms of nucleic acids and DNA-processing proteins. The lab investigates G-quadruplex formation and stability in telomeric DNA, the recognition dynamics of DNA repair factors like XPC-RAD23B, and the translocation mechanisms of molecular motors such as FtsK. Using advanced single-molecule techniques including FRET and high-throughput imaging, the lab uncovers real-time conformational dynamics and regulatory mechanisms underlying genome maintenance and stability.
Professor Ngo Phong Nguyen's research lab specializes in advanced robust control methodologies for nonlinear and disturbed dynamical systems, with a strong focus on sliding mode control, disturbance observation, and finite-time stability. The lab develops innovative control frameworks—particularly continuous, nonsingular, and finite-time sliding mode controllers—tailored for complex engineering systems such as UAVs, rotary inverted pendulums, offshore cranes, and high-order integrator chains. Key research directions include disturbance observer design, chattering reduction, and robustness enhancement under matched and mismatched disturbances. The lab emphasizes practical implementation through fuzzy logic integration and multivariable control structures to ensure high precision and stability in real-world applications.
Professor Fahad Khan's research lab focuses on exploring natural compounds and their mechanisms in cancer therapy, with an emphasis on plant-derived molecules such as rutin, carvacrol, and garlic metabolites. The lab investigates their anticancer, anti-proliferative, and pro-apoptotic effects in various cancer types, particularly prostate cancer, while also examining the role of signaling pathways like PDGF/PDGFR and immune checkpoints in tumor progression. Additionally, the lab contributes to understanding rare clinical phenomena like Purple Urine Bag Syndrome, highlighting its translational and clinical relevance. The overarching goal is to develop effective, low-toxicity therapeutic strategies derived from natural sources to overcome drug resistance and improve patient outcomes.
Professor Kenkera Rayappa Naveen's research lab specializes in the design and development of advanced organic semiconductors for next-generation optoelectronic devices, with a primary focus on thermally activated delayed fluorescence (TADF) emitters. The lab pioneers the synthesis of boron-based multi-resonance TADF materials—particularly double boron-embedded systems—aimed at achieving narrowband, high-efficiency emission across the full color spectrum, including pure blue and red. Their work emphasizes molecular engineering to control frontier orbital distributions, enhance photoluminescence quantum yields, and enable hyperfluorescence architectures for high-color-purity displays. The lab also explores scalable synthetic routes to facilitate practical applications in OLEDs.
Professor Woo Young Choi's research lab specializes in next-generation semiconductor devices, focusing on low-power and high-performance transistors for advanced integrated circuits. The lab pioneers innovations in tunneling field-effect transistors (TFETs) and I-MOS (Independent Gate MOS) devices, aiming to overcome the limitations of conventional MOSFETs, such as subthreshold swing constraints and high leakage. Their work emphasizes novel device structures, advanced materials, and integration techniques to enable ultra-scaled, energy-efficient electronics. The lab also explores post-CMOS memory technologies, particularly electro-mechanical non-volatile memories, for high-density embedded applications.
Professor Ernest K. Ryu's research lab specializes in optimization theory and its applications, with a focus on first-order methods, monotone operator theory, and algorithmic frameworks for large-scale and distributed optimization. The lab develops provably convergent algorithms for convex and non-convex problems, including plug-and-play priors, splitting methods like ADMM and Douglas-Rachford, and stochastic optimization techniques. Recent work emphasizes theoretical foundations of modern machine learning methods—such as GANs and denoising-based optimization—through continuous-time analysis and variance reduction. The lab bridges theory and practice by designing scalable, parallelizable, and data-efficient algorithms for real-world applications in imaging, machine learning, and scientific computing.
Professor Yongdai Kim's research lab specializes in high-dimensional statistical modeling, with a focus on variable selection, regularization methods, and nonparametric Bayesian inference. The lab develops computationally efficient algorithms for sparse estimation in high-dimensional regression, such as SCAD and LASSO, and investigates their theoretical properties, including oracle and model selection consistency. It also explores Bayesian nonparametric methods for survival analysis and point processes, particularly using Lévy processes and neutral-to-the-right priors. The lab integrates statistical theory with applications in medical imaging and real-world data analysis.
Professor JaHyun Kang's research lab focuses on infection prevention and control in healthcare settings, with a strong emphasis on optimizing the use of personal protective equipment (PPE) and implementing effective surveillance strategies for multidrug-resistant organisms such as MRSA. The lab conducts experimental and data-driven studies to evaluate and improve PPE donning and doffing protocols, aiming to reduce contamination risks among healthcare personnel. Additionally, the lab investigates hospital policies related to visitor isolation precautions and advocates for standardized, evidence-based guidelines to enhance patient and staff safety during infectious disease outbreaks.
Professor Doo Hyun Chung's research lab focuses on the tumor microenvironment and immune evasion mechanisms in lung cancer, particularly exploring the interplay between oncogenic drivers like EML4-ALK and immune checkpoint molecules such as PD-L1. The lab investigates how tumor-intrinsic signaling pathways regulate immune cell infiltration and function, with a special emphasis on innate lymphoid cells (ILCs) and their plasticity in promoting tumor progression. Key research directions include the role of IL-23 in reprogramming ILC1 to ILC3-like cells to drive IL-17-mediated inflammation and immunosuppression in squamous cell carcinoma. The lab integrates molecular oncology, immunology, and translational research to identify novel therapeutic targets for improving immunotherapy outcomes in lung cancer.
Professor Jeong Yoon Park's research lab specializes in spinal disorders, with a focus on degenerative spinal diseases, including ossification of the posterior longitudinal ligament (OPLL), spondylolisthesis, and adjacent-segment degeneration (ASD). The lab investigates the genetic, biomechanical, and molecular mechanisms underlying spinal degeneration and aging, integrating clinical spine surgery with molecular biology and genetic analysis. Key research directions include the role of pelvic parameters in spinal sagittal balance, gene expression profiles in intervertebral disc degeneration, and the genetic susceptibility to spinal and systemic diseases such as lung cancer and premature aging. The lab also explores DNA repair pathways and their implications in aging and cancer, particularly through animal models of nucleotide excision repair deficiency.
Professor Do Sik Min's research lab focuses on the molecular mechanisms of phospholipase D (PLD) in cellular signaling, particularly its regulation by tyrosine phosphorylation and interaction with kinases such as c-Src and PDGF receptor. The lab investigates PLD's role in signal transduction pathways linked to cell proliferation, transformation, and cancer progression, with a strong emphasis on the functional implications of PLD isoforms (PLD1 and PLD2) in tumorigenesis. Additional research explores the interplay between PLD and neurodegenerative disease-related proteins, such as alpha-synuclein, highlighting its potential role in neurodegeneration. The lab employs molecular biology, biochemistry, and cell culture models to dissect PLD's enzymatic regulation and downstream effects in both cancer and neurodegenerative contexts.
Professor Kyoung Min Kim's research lab focuses on the pathophysiology of age-related musculoskeletal disorders, with a central emphasis on the interplay between skeletal muscle and bone in aging. The lab investigates molecular mechanisms underlying sarcopenia and osteoporosis, particularly the roles of oxidative stress, transcription factors like FoxO1, and microRNAs in regulating bone and muscle homeostasis. It also explores the clinical implications of drug-induced bone diseases such as bisphosphonate-related osteonecrosis of the jaw and leverages artificial intelligence to improve early detection of osteoporosis and vertebral fractures through routine imaging.
Professor Jae Myun Lee's research lab focuses on viral pathogenesis, particularly the molecular mechanisms of Epstein-Barr virus (EBV) and its interactions with host cell signaling pathways. The lab investigates viral oncoproteins like EBNA2 and their roles in B-cell immortalization, apoptosis evasion, and immune evasion, with a strong emphasis on host-virus interactions involving transcription factors such as Nur77. Additionally, the lab explores vaccine development, including microneedle-based delivery systems for viral vaccines, and examines host genetic factors influencing drug response, particularly in antidepressant therapy via MRP1 polymorphisms. The research integrates virology, immunology, and translational medicine to uncover novel therapeutic targets and strategies.
Professor Dal Woong Choi's research lab specializes in environmental and food safety, with a focus on identifying and assessing chemical hazards in everyday consumer products. The lab investigates volatile organic compounds (VOCs) in indoor air, mineral oil hydrocarbons (MOH) in food contact materials, and condensed phosphates in marine and processed foods, emphasizing their health implications. A key research direction involves developing rapid, selective analytical methods—such as ion chromatography and GC-MS/MS—for detecting food adulterants and toxicants. The lab also explores the biochemical impacts of environmental chemicals, including protein oxidation by cytochrome P-450 enzymes, linking chemical exposure to disease mechanisms.
Professor Youn-Jea Kim's research lab specializes in multiphase flow simulations and fluid-structure interactions, with a strong focus on numerical modeling of complex fluid systems involving particles, magnetic fluids, and high-intensity arcs. The lab employs advanced computational techniques such as CFD-DEM coupling, turbulence modeling, and machine learning for condition monitoring and failure diagnosis in rotating machinery and energy systems. Key research directions include wear prediction in pumps, thermomagnetic convection in ferrofluids, oil-free compressor design, and arc discharge modeling for industrial applications.
Professor Jaesook Yun's research lab specializes in the development of transition metal-catalyzed borylation and hydrosilylation reactions, with a strong focus on asymmetric synthesis and regioselective transformations of unsaturated carbon–carbon bonds. The lab pioneers innovative copper- and titanium-based catalytic systems for the efficient synthesis of alkenylboronic esters and chiral alcohols, emphasizing high enantio- and diastereoselectivity. Their work centers on designing novel ligands and catalysts to enable selective borylcupration of alkynes and alkenes, contributing to the synthesis of versatile organoboron and organosilicon intermediates for pharmaceutical and fine chemical applications.
Professor Kyunga Kim's research lab specializes in statistical genetics and bioinformatics, focusing on the identification and prediction of genetic factors underlying complex human diseases. The lab develops advanced computational and statistical methods—particularly in genome-wide association studies (GWAS) and multifactor dimensionality reduction (MDR)—to detect gene-gene interactions and improve the prediction of disease outcomes such as dementia conversion in mild cognitive impairment. A key emphasis is on enhancing evaluation metrics for genetic classifiers by incorporating effect size and ordinal associations, thereby increasing statistical power, especially in high-dimensional genomic data. The lab also applies machine learning techniques, such as the IML (Interpretable Machine Learning) framework, to generate clinically actionable, individualized predictions for patient prognosis.
Professor Jeong Kon Seo's research lab specializes in the development of innovative chemical tools and methodologies for probing and manipulating biological systems at the molecular level. The lab focuses on designing bioactive peptides, fluorescent probes, and functional catalysts to study key cellular processes such as cell signaling, oxidative stress responses, and protein-protein interactions. A central theme is the creation of selective, non-radioactive assays for phosphatases and the application of advanced photochemical techniques for live-cell proteomics. The lab also pioneers synthetic methodologies for complex arene frameworks and transition-metal-catalyzed reactions with practical operational advantages.
