Quality-aware mobile graphics workload characterization for energy-efficient DVFS design. - Jurn-Gyu Park; Chen-Ying Hsieh; Nikil D. Dutt; Sung-Soo Lim (ESTIMedia, 2014)

Memory-aware cooperative CPU-GPU DVFS governor for mobile games. - Chen-Ying Hsieh; Jurn-Gyu Park; Nikil D. Dutt; Sung-Soo Lim (ESTIMedia, 2015)

HiCAP: Hierarchical FSM-based Dynamic Integrated CPU-GPU Frequency Capping Governor for Energy-Efficient Mobile Gaming. - Jurn-Gyu Park; Nikil D. Dutt; Hoyeonjiki Kim; Sung-Soo Lim (ISLPED, 2016)

Co-Cap: energy-efficient cooperative CPU-GPU frequency capping for mobile games. - Jurn-Gyu Park; Chen-Ying Hsieh; Nikil D. Dutt; Sung-Soo Lim (SAC, 2016)

ML-Gov: a machine learning enhanced integrated CPU-GPU DVFS governor for mobile gaming. - Jurn-Gyu Park; Nikil D. Dutt; Sung-Soo Lim (ESTIMedia, 2017)

Cooperative CPU-GPU Dynamic Power Management Methodologies for Energy-efficient Mobile Gaming. - Jurn-Gyu Park (2017)

MEMCOP: memory-aware co-operative power management governor for mobile games. - Chen-Ying Hsieh; Jurn-Gyu Park; Nikil D. Dutt; Sung-Soo Lim (Des. Autom. Embed. Syst., 2018)

Synergistic CPU-GPU Frequency Capping for Energy-Efficient Mobile Games. - Jurn-Gyu Park; Chen-Ying Hsieh; Nikil D. Dutt; Sung-Soo Lim (ACM Trans. Embed. Comput. Syst., 2018)

A Case Study: Characterization of Performance Inconsistency for Reinforcement Learning on Flappy Bird Game. - Aidar Shakerimov; Dmitriy Li; Jurn-Gyu Park (ICTC, 2021)

An Interpretable Machine Learning Model Enhanced Integrated CPU-GPU DVFS Governor. - Jurn-Gyu Park; Nikil D. Dutt; Sung-Soo Lim (ACM Trans. Embed. Comput. Syst., 2021)

A CNN Inference micro-benchmark for Performance Analysis and Optimization on GPUs. - Jurn-Gyu Park; Zhumakhan Nazir; Beknur Kalmakhanbet; Saidgaffor Sabyrov (SMC, 2022)

Offline RL oriented Functions Design for Dynamic Power Management on CNN Workloads. - Jurn-Gyu Park (BigComp, 2023)

Feed-forward Design vs. Mimic Learning for Interpretable Deep Models: A Comparative Study. - Jurn-Gyu Park; Damir Seit; Kuanysh Tokayev (BigComp, 2023)

Effects of Brightness and Class-Unbalanced Dataset on CNN Model Selection and Image Classification Considering Autonomous Driving. - Zhumakhan Nazir; Vladislav Yarovenko; Jurn-Gyu Park (ICONIP (15), 2023)

Interpretable ML enhanced CNN Performance Analysis of cuBLAS, cuDNN and TensorRT. - Zhumakhan Nazir; Vladislav Yarovenko; Jurn-Gyu Park (SAC, 2023)

CNN Workloads Characterization and Integrated CPU-GPU DVFS Governors on Embedded Systems. - Meruyert Karzhaubayeva; Aidar Amangeldi; Jurn-Gyu Park (IEEE Embed. Syst. Lett., 2023)

Uniformly Distributed Data Effects in Offline RL: A Case Study in Gridworld Setting. - Kuanysh Tokayev; Jurn-Gyu Park (BigComp, 2024)

Patch and Model Size Characterization for On-Device Efficient-ViTs on Small Datasets Using 12 Quantitative Metrics. - Jurn-Gyu Park; Aidar Amangeldi; Nail Fakhrutdinov; Meruyert Karzhaubayeva; Dimitrios Zorbas (IEEE Access, 2025)