Jinzhen Wang 王金震

@misc{deepcq2026,
  title = {{DeepCQ: General-Purpose Deep-Surrogate Framework for Lossy Compression Quality Prediction}},
  author = {Mumenin, Khondoker Mirazul and Underwood, Robert and Dai, Dong and Wang, Jinzhen and Di, Sheng and Lukić, Zarija and Cappello, Franck},
  year = {2025},
  eprint = {2512.21433},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi = {10.48550/arXiv.2512.21433},
  url = {https://arxiv.org/abs/2512.21433},
  note = {Preprint; conference citation metadata not yet verified}
}

@inproceedings{neurlz2025,
  title = {{NeurLZ: An Online Neural Learning-based Method to Enhance Scientific Lossy Compression}},
  author = {Jia, Wenqi and Hu, Zhewen and Liu, Youyuan and Zhang, Boyuan and Wang, Jinzhen and Liu, Jinyang and Niu, Wei and Kalafatis, Stavros and Huang, Junzhou and Jin, Sian and Wang, Daoce and Tian, Jiannan and Yin, Miao},
  booktitle = {Proceedings of the 39th ACM International Conference on Supercomputing},
  year = {2025},
  pages = {26--42},
  publisher = {ACM},
  doi = {10.1145/3721145.3725763},
  url = {https://doi.org/10.1145/3721145.3725763}
}

@inproceedings{qualitynet2024,
  title = {{QualityNet: Error-bounded Lossy Compression Quality Prediction via Deep Surrogate}},
  author = {Mumenin, Khondoker Mirazul and Dai, Dong and Wang, Jinzhen and Di, Sheng},
  booktitle = {2024 IEEE International Conference on Big Data (BigData)},
  year = {2024},
  pages = {252--261},
  publisher = {IEEE},
  doi = {10.1109/bigdata62323.2024.10826140},
  url = {https://doi.org/10.1109/bigdata62323.2024.10826140}
}

@inproceedings{tango2024,
  title = {{Tango: A Cross-layer Approach to Managing I/O Interference over Local Ephemeral Storage}},
  author = {Qiao, Zhenbo and Tian, Qirui and Qin, Zhenlu and Wang, Jinzhen and Liu, Qin g and Podhorszki, Norbert and Klasky, Scott and Zhu, Hongjian},
  booktitle = {SC24: International Conference for High Performance Computing, Networking, Storage and Analysis},
  year = {2024},
  pages = {1--15},
  publisher = {IEEE},
  doi = {10.1109/sc41406.2024.00020},
  url = {https://doi.org/10.1109/sc41406.2024.00020}
}

@inproceedings{progressive2023,
  title = {{Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network}},
  author = {Wang, Jinzhen and Liang, Xin and Whitney, Ben and Chen, Jieyang and Gong, Qian and He, Xubin and Wan, Lipeng and Klasky, Scott and Podhorszki, Norbert and Liu, Qing},
  booktitle = {2023 IEEE 39th International Conference on Data Engineering (ICDE)},
  year = {2023},
  pages = {2727--2739},
  publisher = {IEEE},
  doi = {10.1109/icde55515.2023.00209},
  url = {https://doi.org/10.1109/icde55515.2023.00209}
}

@article{zperf2023,
  title = {{zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression}},
  author = {Wang, Jinzhen and Chen, Qi and Liu, Tong and Liu, Qing and He, Xubin},
  journal = {IEEE Transactions on Computers},
  year = {2023},
  volume = {72},
  number = {9},
  pages = {2641--2655},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tc.2023.3257517},
  url = {https://doi.org/10.1109/tc.2023.3257517}
}

@inproceedings{rendering2022,
  title = {{Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data}},
  author = {Wang, Jinzhen and Grosset, Pascal and Turton, Terece L. and Ahrens, James},
  booktitle = {2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD)},
  year = {2022},
  pages = {11--20},
  publisher = {IEEE},
  doi = {10.1109/drbsd56682.2022.00007},
  url = {https://doi.org/10.1109/drbsd56682.2022.00007}
}

@article{locality2022,
  title = {{Locality-based transfer learning on compression autoencoder for efficient scientific data lossy compression}},
  author = {Wang, Nan and Liu, Tong and Wang, Jinzhen and Liu, Qing and Alibhai, Shakeel and He, Xubin},
  journal = {Journal of Network and Computer Applications},
  year = {2022},
  volume = {205},
  pages = {103452},
  publisher = {Elsevier BV},
  doi = {10.1016/j.jnca.2022.103452},
  url = {https://doi.org/10.1016/j.jnca.2022.103452}
}

@inproceedings{unbalanced2021,
  title = {{Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression}},
  author = {Wang, Xinying and Wan, Lipeng and Chen, Jieyang and Gong, Qian and Whitney, Ben and Wang, Jinzhen and Gainaru, Ana and Liu, Qing and Podhorszki, Norbert and Zhao, Dongfang and Yan, Feng and Klasky, Scott},
  booktitle = {2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7)},
  year = {2021},
  pages = {26--32},
  publisher = {IEEE},
  doi = {10.1109/drbsd754563.2021.00008},
  url = {https://doi.org/10.1109/drbsd754563.2021.00008}
}

@inproceedings{proportioning2021,
  title = {{Reducing the Training Overhead of the HPC Compression Autoencoder via Dataset Proportioning}},
  author = {Liu, Tong and Alibhai, Shakeel and Wang, Jinzhen and Liu, Qing and He, Xubin},
  booktitle = {2021 IEEE International Conference on Networking, Architecture and Storage (NAS)},
  year = {2021},
  pages = {1--7},
  publisher = {IEEE},
  doi = {10.1109/nas51552.2021.9605407},
  url = {https://doi.org/10.1109/nas51552.2021.9605407}
}

@article{autoencoder2021,
  title = {{High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data}},
  author = {Liu, Tong and Wang, Jinzhen and Liu, Qing and Alibhai, Shakeel and Lu, Tao and He, Xubin},
  journal = {IEEE Transactions on Big Data},
  year = {2023},
  volume = {9},
  number = {1},
  pages = {22--36},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tbdata.2021.3066151},
  url = {https://doi.org/10.1109/tbdata.2021.3066151}
}

@article{compressibility2020,
  title = {{Estimating Lossy Compressibility of Scientific Data Using Deep Neural Networks}},
  author = {Qin, Zhenlu and Wang, Jinzhen and Liu, Qing and Chen, Jieyang and Pugmire, Dave and Podhorszki, Norbert and Klasky, Scott},
  journal = {IEEE Letters of the Computer Society},
  year = {2020},
  volume = {3},
  number = {1},
  pages = {5--8},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/locs.2020.2971940},
  url = {https://doi.org/10.1109/locs.2020.2971940}
}

@article{ratio2019,
  title = {{Compression Ratio Modeling and Estimation across Error Bounds for Lossy Compression}},
  author = {Wang, Jinzhen and Liu, Tong and Liu, Qing and He, Xubin and Luo, Huizhang and He, Weiming},
  journal = {IEEE Transactions on Parallel and Distributed Systems},
  year = {2020},
  volume = {31},
  number = {7},
  pages = {1621--1635},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tpds.2019.2938503},
  url = {https://doi.org/10.1109/tpds.2019.2938503}
}

@inproceedings{transfer2019,
  title = {{Exploring Transfer Learning to Reduce Training Overhead of HPC Data in Machine Learning}},
  author = {Liu, Tong and Alibhai, Shakeel and Wang, Jinzhen and Liu, Qing and He, Xubin and Wu, Chentao},
  booktitle = {2019 IEEE International Conference on Networking, Architecture and Storage (NAS)},
  year = {2019},
  pages = {1--7},
  publisher = {IEEE},
  doi = {10.1109/nas.2019.8834723},
  url = {https://doi.org/10.1109/nas.2019.8834723}
}

@inproceedings{latent2019,
  title = {{Identifying Latent Reduced Models to Precondition Lossy Compression}},
  author = {Luo, Huizhang and Huang, Dan and Liu, Qing and Qiao, Zhenbo and Jiang, Hong and Bi, Jing and Yuan, Haitao and Zhou, Mengchu and Wang, Jinzhen and Qin, Zhenlu},
  booktitle = {2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
  year = {2019},
  pages = {293--302},
  publisher = {IEEE},
  doi = {10.1109/ipdps.2019.00039},
  url = {https://doi.org/10.1109/ipdps.2019.00039}
}

@article{sirius2018,
  title = {{SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data}},
  author = {Qiao, Zhenbo and Lu, Tao and Luo, Huizhang and Liu, Qing and Klasky, Scott and Podhorszki, Norbert and Wang, Jinzhen},
  journal = {IEEE Transactions on Multi-Scale Computing Systems},
  year = {2018},
  volume = {4},
  number = {4},
  pages = {900--913},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tmscs.2018.2886851},
  url = {https://doi.org/10.1109/tmscs.2018.2886851}
}

@article{duomodel2018,
  title = {{DuoModel: Leveraging Reduced Model for Data Reduction and Re-Computation on HPC Storage}},
  author = {Luo, Huizhang and Liu, Qing and Qiao, Zhenbo and Wang, Jinzhen and Wang, Mengxiao and Jiang, Hong},
  journal = {IEEE Letters of the Computer Society},
  year = {2018},
  volume = {1},
  number = {1},
  pages = {5--8},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/lcos.2018.2855118},
  url = {https://doi.org/10.1109/lcos.2018.2855118}
}