† Current Ph.D. student advised by Sian Jin.

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SC'26

Youyuan Liu†, Bo Jiang†, Taolue Yang†, Sheng Di, Robert Underwood, and Sian Jin. “TOPIQ: Statistical Error Propagation for Quantity-of-Interest Prediction under Lossy Compression.” The International Conference for High Performance Computing, Networking, Storage, and Analysis, Chicago, Illinois, USA, November 15–20, 2026.

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SC'26

Bo Jiang†, Youyuan Liu†, Taolue Yang†, Sheng Di, and Sian Jin. “3D Gaussian Splatting for Scientific Particle Data Compression and Rendering.” The International Conference for High Performance Computing, Networking, Storage, and Analysis, Chicago, Illinois, USA, November 15–20, 2026.

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VLDB'26

Youyuan Liu†, Longtao Zhang, Ruoyu Li, Bo Jiang†, Taolue Yang†, Kai Zhao, Sheng Di, Eduard Dragut, and Sian Jin. “Error-bounded Point Cloud Compression Using Truncated Octahedron Quantization.” Proceedings of the VLDB Endowment (PVLDB) / The 52nd International Conference on Very Large Data Bases, Boston, Massachusetts, USA, August 31–September 4, 2026.

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ICS'26

Taolue Yang†, Youyuan Liu†, Bo Jiang†, Xinghua Shi, and Sian Jin. “GFAz: State-of-the-Art Graphical Fragment Assembly Compression.” The 40th ACM International Conference on Supercomputing, Belfast, Northern Ireland, United Kingdom, July 6–9, 2026.

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ACM BCB'26

Taolue Yang†, Youyuan Liu†, Bo Jiang†, Chong Li, Xinghua Shi, and Sian Jin. “CuVert-Q: Resolving the Throughput-Ratio Tradeoff in Genomic Sequence Data Compression via GPU Acceleration.” The 17th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Calabria, Italy, June 30–July 3, 2026. [ACM SIGBio Best Paper Award]

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IPDPS'26

Bo Jiang†, Taolue Yang†, Youyuan Liu†, Xubin He, Sheng Di, and Sian Jin. “PackKV: Reducing KV Cache Memory Footprint through LLM-Aware Lossy Compression.” The 40th IEEE International Parallel & Distributed Processing Symposium, New Orleans, Louisiana, USA, May 25–29, 2026.

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HPDC'25

Youyuan Liu†, Wenqi Jia, Taolue Yang†, Bo Jiang†, Miao Yin, and Sian Jin. “Advancing Scientific Data Compression via Cross-Field Prediction.” The 34th ACM International Symposium on High-Performance Parallel and Distributed Computing, Notre Dame, Indiana, USA, July 20–23, 2025.

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ACM BCB'24

Taolue Yang†, Youyuan Liu†, Chong Li, Xinhua Mindy Shi, and Sian Jin. “SeqBench: A Benchmark Suite for Lossless and Lossy Compression of Sequence Data.” The 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Shenzhen, Guangdong, P.R. China, November 22–25, 2024.

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EuroSys'24

Sian Jin, Sheng Di, Frédéric Vivien, Daoce Wang, Yves Robert, Dingwen Tao, and Franck Cappello.``Concealing Compression-accelerated I/O for HPC Applications through In Situ Task Scheduling.'' Proceedings of the Nineteenth European Conference on Computer Systems, Athens, Greece, April 22-25, 2024.

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SIGMOD'24

Jinyang Liu, Sheng Di, Kai Zhao, Xin Liang, Sian Jin, Zizhe Jian, Jiajun Huang, Shixun Wu, Zizhong Chen, and Franck Cappello. ``High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation.'' The ACM Special Interest Group on Management of Data, Santiago, Chile, June 9–-15, 2024.

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SC'23

Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Zarija Lukić, Kai Zhao, Bo Fang, Franck Cappello, James Ahrens, and Dingwen Tao. ``AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications.'' The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver, Colorado, USA, November 12-17, 2023.

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TPDS'23

Haoyu Jin, Donglei Wu, Shuyu Zhang, Xiangyu Zou, Sian Jin, Dingwen Tao, Qing Liao, and Wen Xia
Design of a Quantization-based DNN Delta Compression Framework for Model Snapshots and Federated Learning
IEEE Transactions on Parallel and Distributed Systems, Volume 23

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SC'22

Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, and Franck CappelloAccelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, Nov. 13-18, 2022 [paper]

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VLDB'22

Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, and Dingwen TaoCOMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy CompressionACM International Conference on Very Large Data Bases, Sydney, Australia, Sep. 5–9, 2022 [paper]

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ICDE'22

Sian Jin, Di Sheng, Jiannan Tian, Suren Byna, Dingwen Tao, and Franck CappelloSignificantly Improving Prediction-Based Lossy Compression Via Ratio-Quality ModelingIEEE International Conference on Data Engineering, Worldwide online event, May 9–12, 2022 [paper]

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TPDS'22

Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello
Optimizing Error-Bounded Lossy Compression for Scientific Data with Diverse Constraints
IEEE Transactions on Parallel and Distributed Systems, Volume 22 [paper]

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ICS'22

Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, and Dingwen Tao
CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Designed Adaptive Lossy Compression
ACM International Conference on Supercomputing, Worldwide online event, June 27–30, 2022 [paper]

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HPDC'22

Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, and Dingwen Tao
Optimizing Error-Bounded Lossy Compression for Three Dimensional Adaptive Mesh Refinement Simulations
ACM International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, Minnesota, USA, June 27–July 1, 2022 [paper]

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HPDC'21

Sian Jin, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao, and James AhrensAdaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality ModelingACM International Symposium on High-Performance Parallel and Distributed Computing, Worldwide online event, June 21–25, 2021 [paper]

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PPoPP'21

Sian Jin, Guanpeng Li, Shuaiwen Leon Song, and Dingwen TaoPOSTER: A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy CompressionACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Worldwide online event, Feb. 27–Mar. 3, 2021 [paper]

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ICS'21

Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, and Dingwen Tao
ClickTrain: Efficient and Accurate End-to-End Deep Learning Training via Fine-Grained Architecture-Preserving Pruning
ACM International Conference on Supercomputing, Worldwide online event, June 14–17, 2021 [paper]

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IPDPS'20

Sian Jin, Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, and James AhrensUnderstanding GPU-Based Lossy Compression for Extreme-Scale Cosmological SimulationsIEEE International Parallel & Distributed Processing Symposium, New Orleans, Louisiana, USA, May 18–22, 2020 [paper]

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PACT'20

Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman Fulp, Robert Underwood, Sian Jin, and others
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
ACM International Conference on Parallel Architectures and Compilation Techniques. Virtual, October 2–7, 2020 [paper]

 

PPoPP'20

Jiannan Tian, Sheng Di, Chengming Zhang, Xin Liang, Sian Jin, Dazhao Cheng, Dingwen Tao, and Franck Cappello
WAVESZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. San Diego, California, USA, February 22–26, 2020 [paper]

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HPDC'19

Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, and Franck CappelloDeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy CompressionACM International Symposium on High-Performance Parallel and Distributed Computing, Phoenix, Arizona, USA, June 24–28, 2019 [paper]