Juneseo Chang

I am an undergraduate student majoring Computer Science and Engineering at Seoul National University. I am was an undergraduate research intern at SCALable Computer Architecture Laboratory, Seoul National University, led by Prof. Jung Ho Ahn. I have also been advised by Prof. Daejin Park. My research interests include machine learning for system and memory management.

I am currently serving the mandatory military service (ROK DCC 2024.07 - 2026.01).

news

Mar 26, 2024	IDT: Intelligent Data Placement for Multi-Tiered Main Memory with Reinforcement Learning was accepted at HPDC 2024 (Acceptance Rate: 17%).
Jul 5, 2023	Work-in-Progress: Searching Optimal Compiler Optimization Passes Sequence for Reducing Runtime Memory Profile using Ensemble Reinforcement Learning was accepted at EMSOFT 2023.
Jul 7, 2022	Work-in-Progress: Accuracy-Area Efficient Online Fault Detection for Robust Neural Network Software-Embedded Microcontrollers was accepted to EMSOFT 2022.
Jan 1, 2022	Low-power on-chip implementation of enhanced svm algorithm for sensors fusion-based activity classification in lightweighted edge devices was accepted to Electronics.

selected publications

IDT: Intelligent Data Placement for Multi-Tiered Main Memory with Reinforcement Learning

Juneseo Chang, Wanju Doh, Yaebin Moon, Eojin Lee, and Jung Ho Ahn

In Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing, 2024

Bib PDF Code Slides

@inproceedings{JSChang_HPDC_2024,
  title = {IDT: Intelligent Data Placement for Multi-Tiered Main Memory with Reinforcement Learning},
  author = {Chang, Juneseo and Doh, Wanju and Moon, Yaebin and Lee, Eojin and Ahn, Jung Ho},
  year = {2024},
  isbn = {9798400704130},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3625549.3658659},
  doi = {10.1145/3625549.3658659},
  booktitle = {Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing},
  pages = {69–82},
  numpages = {14},
  location = {Pisa, Italy},
  series = {HPDC '24},
}

Work-in-Progress: Searching Optimal Compiler Optimization Passes Sequence for Reducing Runtime Memory Profile using Ensemble Reinforcement Learning

Juneseo Chang, and Daejin Park

In Proceedings of the International Conference on Embedded Software (EMSOFT), 2023

Bib PDF Code Slides

@inproceedings{JSChang_EMSOFT_2023,
  author = {Chang, Juneseo and Park, Daejin},
  title = {Work-in-Progress: Searching Optimal Compiler Optimization Passes Sequence for Reducing Runtime Memory Profile using Ensemble Reinforcement Learning},
  year = {2023},
  url = {https://doi.org/10.1145/3607890.3608460},
  doi = {10.1145/3607890.3608460},
  booktitle = {Proceedings of the International Conference on Embedded Software (EMSOFT)},
  pages = {3–4},
  numpages = {2},
  keywords = {code optimization, reinforcement learning, embedded system},
  location = {Hamburg, Germany},
  series = {EMSOFT '23},
}

Work-in-Progress: Accuracy-Area Efficient Online Fault Detection for Robust Neural Network Software-Embedded Microcontrollers

Juneseo Chang, Sejong Oh, and Daejin Park

In Proceedings of the International Conference on Embedded Software (EMSOFT), 2022

Bib PDF

@inproceedings{JSChang_EMSOFT_2022,
  author = {Chang, Juneseo and Oh, Sejong and Park, Daejin},
  booktitle = {Proceedings of the International Conference on Embedded Software (EMSOFT)},
  title = {Work-in-Progress: Accuracy-Area Efficient Online Fault Detection for Robust Neural Network Software-Embedded Microcontrollers},
  year = {2022},
  pages = {1-2},
  keywords = {Support vector machines;Fault tolerance;Runtime;Microcontrollers;Fault tolerant systems;Distributed databases;Artificial neural networks;Fault Tolerance;Embedded System;Neural Networks;Reliability},
  doi = {10.1109/EMSOFT55006.2022.00008},
}