Soo-jeong Park
Yonsei University · Environmental Science
About the Lab
Professor Soo-jeong Park's research lab specializes in environmental and climate science, with a focus on extreme weather event modeling, particularly intense rainfall and its climatic trends. The lab applies advanced statistical methods—such as non-stationary generalized extreme value (GEV) distributions and Wakeby distributions—combined with L-moments and bootstrap resampling techniques to analyze historical and projected precipitation extremes across South Korea. Their work supports the development of reliable design rainfall estimates for infrastructure planning and climate adaptation strategies. Additionally, the lab contributes to biomedical research, especially in stem cell therapy for spinal cord injury and the pathophysiology of neurogenic bladder, as well as exploring therapeutic targets in aggressive cancers like triple-negative breast cancer.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Abstract This paper examines the usefulness of the non‐stationary generalized extreme value (GEV) distribution in modelling extreme rainfall. We modelled the annual maxima of daily (AMP1) and 2‐day (AMP2) rainfall data observed during the summer rainy season, dating up to 2007 in 28 stations in South Korea. We fitted the GEV distribution to the data for each location. The location parameter of the GEV distribution was formulated as a function of time to explore the temporal trends in maximum pre
BACKGROUND: Mesenchymal stem cells are widely used for transplantation into the injured spinal cord in vivo model and for safety, many human clinical trials are continuing to promote improvements of motor and sensory functions after spinal cord injury. Yet the exact mechanism for these improvements remains undefined. Neurogenic bladder following spinal cord injury is the main problem decreasing the quality of life for patients with spinal cord injury, but there are no clear data using stem cell
Abstract Attempts to use the Wakeby distribution (WAD) with the method of L‐moments estimates (L‐ME), on the summer extreme rainfall data (time series of annual maximum of daily and 2‐day precipitation) at 61 gauging stations over South Korea have been made to obtain reliable quantile estimates for several return periods. The 90% confidence intervals for the quantiles determined by WAD have been obtained by the bootstrap resampling technique. The isopluvial maps of estimated design values corres
Triple-negative breast cancer (TNBC) is a subset of breast cancer with aggressive characteristics and few therapeutic options. The lack of an appropriate therapeutic target is a challenging issue in treating TNBC. Although a high level expression of epidermal growth factor receptor (EGFR) has been associated with a poor prognosis among patients with TNBC, targeted anti-EGFR therapies have demonstrated limited efficacy for TNBC treatment in both clinical and preclinical settings. However, with th
ABSTRACT Senescent cells have been generally characterized to have improper responsiveness to external stimuli and inefficient uptake of materials compared with presenescent cells, probably by down‐regulation of receptor‐mediated endocytosis. Using transferrin‐uptake assay and Western blot of endocytosis‐related proteins, we found that a significant decrease of amphiphysin‐1 is strongly related to the reduction of receptor‐mediated endocytosis in both human diploid fibroblasts of multipassages a
ABSTRACT Attempts to assess the changes between the observed (or historical) and future projected daily rainfall extremes for 59 stations throughout Korea have been made with descriptive statistics and extreme value analysis. For the comparison, three different periods and four different data sets are considered: observation and historical data from 1976 to 2005 (period 0), simulation from 2021 to 2050 (period 1) and from 2066 to 2095 (period 2). The historical and projected rainfalls are obtain
In regression models with multiplicative error, estimation is often based on either the log-normal or the gamma model. It is well known that the gamma model with constant coefficient of variation and the log-normal model with constant variance give almost the same analysis. This article focuses on the discrepancies of the regression estimates between the two models based on real examples. It identifies that even though the variance or the coefficient of variation remains constant, but regression
Research Areas
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