Publications

Journals
Conference Papers
Preprint Papers 

Journals 

[J9] Kalmakhanbet, Beknur, Jurn-Gyu Park, and Min-Ho Lee. "Deep Learning Library Performance Characterization and Optimization for Edge-AI on Mobile GPUs." IEEE Access (2026). DOI: https://doi.org/10.1109/ACCESS.2026.3707247 

[J8] Aruzhan Suleimenova, Barrett L. Burgess, Jaemin Choi, Jurn-Gyu Park, Taeil Kim,  "PiSO: Pipelined Selection Optimization Framework for Preprocessed Data and DL Models on ABP Estimation using MIMIC-IV" IEEE Access, DOI: https://doi.org/10.1109/ACCESS.2026.3665255 

[J7] Barrett L. Burgess, Aruzhan Suleimenova, Jaemin Choi, Chukwudum J. Maduako, Amanat H. Emon, Ellie Skaarer, James Hovanec, Jurn-Gyu Park, Taeil Kim, “AI-Based Non-Invasive Continuous Blood Pressure Monitoring and Estimation System”,  Advanced Sensor Research (ASR), Jan. 2026 (Volume 5, Issue 1). DOI: https://doi.org/10.1002/adsr.202500134 

[J6] Jurn-Gyu Park, Aidar Amangeldi, Nail Fakhrutdinov, Meruyert Karzhaubayeva, Dimitrios Zormpas,  "Patch and Model Size Characterization for On-device Efficient-ViTs on Small Datasets using 12 Quantitative Metrics". IEEE Access, (2025, Jan.) DOI: 10.1109/ACCESS.2025.3536471

[J5] Meruyert Karzhaubayeva, Aidar Amangeldi, Jurn-Gyu Park. CNN Workloads Characterization and Integrated CPU-GPU DVFS Governors on Embedded Systems. IEEE Embedded Systems Letters (ESL, SCIE), (2023, Sep.)   DOI: 10.1109/LES.2023.3299335

[J4] Zhumakhan Nazir, Temirlan Zarymkanov, Jurn-Gyu Park. A Machine Learning Model Selection Considering Tradeoffs between Accuracy and Interpretability. Advances in Science, Technology and Engineering Systems Journal (ASTESJ), 7(4), 72~78 (2022, Aug.) DOI: 10.25046/aj070410

[J3] Jurn-Gyu  Park,  Nikil  Dutt,  and  Sung-Soo  Lim.  “An  Interpretable Machine  Learning  Model  Enhanced Integrated CPU-GPU  DVFS  Governor”. ACM Transactions on Embedded Computing Systems (TECS, SCIE), 20(6): 108:1-28 (2021, Oct). https://doi.org/10.1145/3470974 

[J2] C-Y. Hsieh, J-G. Park, N. Dutt, S-S. Lim: “MEMCOP: Memory-Aware Co-operative Power Management Governor for Mobile Games”,  Design Automation for Embedded Systems (DAEM, SCIE), Springer, pp 1-22, March 2018 

[J1] J-G. Park, C-Y. Hsieh, N. Dutt, S-S. Lim: “Synergistic CPU-GPU Frequency Capping for Energy-efficient Mobile  Games”,  ACM Transactions on Embedded Computing Systems (TECS, SCIE),Volume 17, Issue2, January 2018.

Conference Papers  

[C14] Kuanysh Tokayev  and Jurn-Gyu Park, Uniformly Distributed Data Effects in Offline RL: A Case Study in Gridworld Setting, IEEE Big Data and Smart Computing (BigComp’24), Feb. 18-21, 2024 (Bangkok, Thailand)

[C13] Zhumakhan Nazir, Vladislav Yarovenko, Jurn-Gyu Park. Effects of Brightness and Class-unbalanced Dataset on CNN Model Selection and Image Classification considering Autonomous Driving.  In International Conference on Neural Information Processing (ICONIP 2023, Nov. 20-23.)

[C12] Zhumakhan Nazir, Vladislav Yarovenko, Jurn-Gyu Park. Interpretable ML enhanced CNN Performance Analysis of cuBLAS, cuDNN and TensorRT.  In ACM/SIGAPP Symposium on Applied Computing (ACM SAC 2023, Mar.) 

[C11] Jurn-Gyu Park, Damir Seit, Kuanysh Tokayev. Feed-forward Design vs. Mimic Learning for Interpretable Deep Models: A Comparative Study.  In IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2023, Feb.). 

[C10] Jurn-Gyu Park. Offline RL oriented Functions Design for Dynamic Power Management on CNN Workloads. In IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2023, Feb.). 

[C9] Jurn-Gyu Park, Zhumakhan Nazir, Beknur Kalmakhanbet, Saidgaffor Sabyrov, A CNN Inference micro-benchmark for Performance Analysis and Optimization on GPUs, In  IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2022, Oct.). 

[C8] Vladislav Yarovenko, Jurn-Gyu Park, Min-Ho Lee. Re-thinking Pitfalls of Premodel Building for Adaptive CNNs Model Selection on ImageNet. In the International Conference on Advances in Computer Technology, Information Science and Communications (IEEE CTISC 2022, Apr). DOI: 10.1109/CTISC54888.2022.9849779

[C7] Zhumakhan Nazir, Dinmukhamed Kaldykhanov, Kozy-Korpesh Tolep, Jurn-Gyu Park. 2021. “A Machine Learning Model Selection Methodology considering Tradeoffs between Accuracy and Interpretability”. In the 13th International Conference on Information Technology and Electrical Engineering (ICITEE 2021). (Oct. 14-15, 2021).

[C6] Aidar Shakerimov, Dmitriy Li, Jurn-Gyu Park. 2021. “A Case Study: Characterization of Performance Inconsistency for Reinforcement Learning on Flappy Bird Game”. In the 12th International Conference on ICT Convergence (ICTC 2021). (Oct. 20-22, 2021).

[C5] J-G. Park, N. Dutt, and S-S. Lim, "ML-Gov: A Machine Learning Enhanced Integrated CPU-GPU  DVFS Governor for Mobile Gaming", proceedings of the 15th International Symposium on Embedded Systems for Real Time Multimedia  (ESTIMEDIA 2017), Seoul, Korea, October 2017. 

[C4] J-G. Park, N. Dutt, H. Kim,S-S. Lim: “HiCAP: Hierarchical FSM-based Dynamic Integrated CPU-GPU Frequency Capping Governor for Energy-Efficient Mobile Gaming.”, International Symposium on Low Power Electronics and Design (ISLPED 2016), San Francisco, USA, Aug. 2016

[C3] J-G. Park, C-Y. Hsieh, N. Dutt, S-S. Lim: “Co-Cap: energy-efficient cooperative CPU-GPU frequency capping for mobile games.” Proceedings of the 31st Annual ACM Symposium on Applied Computing (SAC 2016), Pisa, Italy, April 2016.

[C2] C. Hsieh, J-G. Park, N. Dutt, and S-S. Lim, "Memory-aware Cooperative CPU-GPU DVFS Governor for Mobile Games", proceedings of the 13th International Symposium on Embedded Systems for Real Time Multimedia (ESTIMEDIA 2015)

[C1] J-G. Park, C-Y. Hsieh, N. Dutt, and S-S. Lim, "Quality-aware Mobile Graphics Workload Characterization for Energy-efficient DVFS Design", Symposium on Embedded Systems for Real Time Multimedia  (ESTIMEDIA 2014), October 2014.

Preprint (informal, not peer-reviewed) papers  

[i2] Nursultan Amanzhol, Jurn-Gyu Park. Energy-Efficient Vision Transformer Inference for Edge-AI Deployment. CoRR abs/2511.23166 (2025)

[i1] Merey Orazaly, Fariza Temirkhanova, Jurn-Gyu Park. Efficient-Husformer: Efficient Multimodal Transformer Hyperparameter Optimization for Stress and Cognitive Loads. CoRR abs/2511.22362 (2025)