Young Myoung Ko

Associate Professor

Pohang University of Science and Technology

South Korea

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About

Young Myoung Ko is an Associate Professor at Pohang University of Science and Technology in South Korea. His research focuses on queueing theory, stochastic simulation, and data analysis, as evidenced by his recent articles. Notable topics include time-varying many-server queues, maintenance policies, and optimization techniques in cloud computing and data imputation.

Articles (15)

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2025

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2025

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2025

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2025

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2025

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2024

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2023

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2022

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2021

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2021

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2021

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2020

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2020

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2020

Collaborators (3)

Eunshin Byon

University of Michigan

UNITED STATES

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Yongkyu Cho

Assistant Professor

Kyungpook National University

SOUTH KOREA

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Stephane Barde

Assistant Professor

Hanyang University

SOUTH KOREA

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Young Myoung Ko

Research Interests

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About

Articles (15)

Overlap approximation schemes in time-varying many-server queues

The number of overlapping customers in Erlang-A queues: an asymptotic approach

Queueing management for reducing the overlaps of customers in service systems

Strata Design for Variance Reduction in Stochastic Simulation

Analysis on Nonmonotone Control-Limit Condition-Based Maintenance Policies

Condition-Based Selective Maintenance Optimization for Large-Scale Systems Consisting of Many Homogeneous Units

Constrained Density-Based Spatial Clustering of Applications with Noise (DBSCAN) using hyperparameter optimization

Reliability Improvement of Circular k-Out-of-N: G Balanced Systems Through Center of Gravity

Power- and QoS-Aware Job Assignment With Dynamic Speed Scaling for Cloud Data Center Computing

Missing data imputation using mixture factor analysis for building electric load data

Uncertainty Quantification for Extreme Quantile Estimation With Stochastic Computer Models

Short-term electric load forecasting for buildings using logistic mixture vector autoregressive model with curve registration

Economic Design and Maintenance of a Circular k-Out-of-n: G Balanced System With Load-Sharing Units

Stabilizing the virtual response time in single-server processor sharing queues with slowly time-varying arrival rates

Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models

Collaborators (3)

Eunshin Byon

Yongkyu Cho

Stephane Barde

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