Young Geun Kim

Young Geun Kim

Ph.D. Candidate in Department of Statistics

Sungkyunkwan University (SKKU)

Biography

Welcome to Young Geun Kim’s long-range dependent academic path! Young-geun Kim is a Ph.D. candidate in statistics at Sungkyunkwan University (SKKU). His research interest mainly begins with a time series. It includes high-dimensional time series, long-range dependency, Bayesian VAR modeling, et cetera. He is developing forecasting models based on Bayesian VAR having Minnesota prior and various shrinkage priors.

Interests
  • Long-range dependence
  • Vector autoregression (VAR)
  • Heterogeneous autoregression (HAR)
  • Bayesian econometrics
  • Anomaly detection
  • and more 🤔
Education

  • Ph.D. in Statistics, 2025 (expected)

    Sungkyunkwan University, Seoul, Korea

  • BEc in Statistics, 2019

    Sungkyunkwan University, Seoul, Korea

Recent Publications

Bayesian Vector Heterogeneous Autoregressive Modeling
Journal of Statistical Computation and Simulation
PDF Cite Dataset Project DOI R Package Codes
Bayesian Vector Heterogeneous Autoregressive Modeling
Residual Size is Not Enough for Anomaly Detection: Improving Detection Performance using Residual Similarity in Multivariate Time Series
SAC 2022 - Virtual Event
PDF Cite Project DOI Data - SWaT SWaT - seq2seq Data - WADI Data - HAI
Residual Size is Not Enough for Anomaly Detection: Improving Detection Performance using Residual Similarity in Multivariate Time Series
Revitalizing Self-Organizing Map: Anomaly Detection using Forecasting Error Patterns
IFIP SEC 2021 - Oslo, Norway
PDF Cite Code Project Slides DOI Data - SWaT Data - HAI
Revitalizing Self-Organizing Map: Anomaly Detection using Forecasting Error Patterns
Contextual Anomaly Detection by Correlated Probability Distributions using Kullback-Leibler Divergence
5th Workshop on Mining and Learning from Time Series, held in conjunction with KDD'19 Aug 5, 2019 - Anchorage, Alaska, USA
PDF Cite Code Dataset Project
Contextual Anomaly Detection by Correlated Probability Distributions using Kullback-Leibler Divergence

Recent Projects

Bayesian Modeling for Vector Heterogeneous Autoregressive Model
Extend Bayesian VAR (BVAR) to Vector Heterogeneous Autoregressive (VHAR) model
Last updated on Apr 26, 2024 project
Data - ETF VIX R
Bayesian Modeling for Vector Heterogeneous Autoregressive Model
Anomaly detection in Cyber-Physical Systems
Anomaly detection based on the deep neural network error.
Last updated on Oct 2, 2023 project
Data - SWaT Data - HAI R Python Team
Anomaly detection in Cyber-Physical Systems