Kwangwoo Kim
Kyung Hee University · 工学
研究室紹介
Professor Kwangwoo Kim's research lab specializes in the genetic and immunological mechanisms underlying autoimmune diseases, particularly rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). The lab focuses on identifying gene-environment interactions, such as the interplay between HLA polymorphisms and smoking in RA pathogenesis, using advanced genomic imputation and statistical modeling. Additionally, the lab explores the clinical and engineering applications of predictive control systems in building energy efficiency, particularly in radiant floor heating. A secondary but significant research direction involves the mechanical performance of construction materials, especially warm-mix asphalt under extreme temperature conditions.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Our findings provide useful insights regarding RA genetic aetiology and variant-driven RA pathogenesis.
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of complex etiology that primarily affects women of childbearing age. The development of SLE is attributed to the breach of immunological tolerance and the interaction between SLE-susceptibility genes and various environmental factors, resulting in the production of pathogenic autoantibodies. Working in concert with the innate and adaptive arms of the immune system, lupus-related autoantibodies mediate immune-complex deposition i
OBJECTIVE: To define the interaction between cigarette smoking and HLA polymorphisms in seropositive rheumatoid arthritis (RA), in the context of a recently identified amino acid-based HLA model for RA susceptibility. METHODS: We imputed Immunochip data on HLA amino acids and classical alleles from 3 case-control studies (the Swedish Epidemiological Investigation of Rheumatoid Arthritis [EIRA] study [1,654 cases and 1,934 controls], the Nurses' Health Study [NHS] [229 cases and 360 controls], an
The objective of this study is to improve the control performance of the radiant floor heating system in apart-ment buildings. For this, predictive control, which is simple and also compatible with the existing system, is suggested, and its performance is evaluated. The control system of radiant floor heating should be easily adapted to thermal mass characteristics and building load variations without complication in real application. In this study, predictive control using the ANN (Artificial N