Kai Zhao

Assistant Professor
Department of Computer Science
The University of Alabama at Birmingham

Office: University Hall 4153
Email: kzhao@uab.edu
Tel: 205-975-3087


Biography

I am a tenure-track assistant professor in the Department of Computer Science at University of Alabama at Birmingham. I received Ph.D. in computer science from University of California, Riverside in 2022, advised by Dr. Zizhong Chen. Prior to that, I received B.S. in Computer Science from Peking University in 2014. During my Ph.D. studies, I worked as a student intern at Argonne National Laboratory, advised by Dr. Sheng Di and Dr. Franck Cappello. My research interests lie broadly in the area of high-performance computing and autonomous driving, with a special focus on reliability, efficiency, and data management. More details can be found in my CV.
I am married with Qian Wang. We have a Sheprador dog Sha Sha.

I am hiring Ph.D. students for 2023 Fall admission. If interested, please send me your CV and transcript.


Research Interests


Awards


Publications

VLDB'23

Pu Jiao, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello
Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data.
Proceedings of the 49th International Conference on Very Large Data Bases, Vancour, Canada, Aug 28 - Sep 1, 2023.

ICDE'23

Md Hasanur Rahman, Sheng Di, Kai Zhao, Robert Underwood, Guanpeng Li, and Franck Cappello
A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets
Proceedings of the 39th IEEE International Conference on Data Engineering, Anaheim, CA, USA, April 3 – 7, 2023.

PPoPP'23

Jieyang Chen, Xin Liang, Kai Zhao, Hadi Zamani Sabzi, Laxmi Bhuyan, and Zizhong Chen
Improving Energy Saving of One-sided Matrix Decompositions on CPU-GPU Heterogeneous Systems
Proceeding of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, Montreal, Canada. Feb 25 - Mar 1, 2023.

SC'22

Jinyang Liu, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello
Dynamic Quality Metric Oriented Error Bounded Lossy Compression for Scientific Datasets
Proceedings of the 34rd ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, TX, USA, Nov 13 - 18, 2022. [Link]

TPDS'22

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

TBD'22

Xin Liang*, Kai Zhao*, Sheng Di, Sihuan Li, Robert Underwood, Ali M Gok, Jiannan Tian, Junjing Deng, Jon C Calhoun, Dingwen Tao, Zizhong Chen, Franck Cappello
SZ3: A modular framework for composing prediction-based error-bounded lossy compressors
IEEE Transactions on Big Data.
*Authors contributed equally. [Link]

HPDC'22

Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello
Ultrafast Error-bounded Lossy Compression for Scientific Datasets
Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, United States, June 27 - July 1, 2022. [Link]

ICDE'22

Kai Zhao, Sheng Di, Danny Perez, Zizhong Chen, and Franck Cappello
MDZ: An Efficient Error-bounded Lossy Compressor for Molecular Dynamics Simulations
Proceedings of the 38th IEEE International Conference on Data Engineering, Kuala Lumpur, Malaysia, May 9 - 12, 2022. [Link]

SC'21

Sihuan Li, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello
Resilient Error-bounded Lossy Compressor for Data Transfer
Proceedings of the 33rd ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, St. Louis, MO, USA, Nov 14 - 19, 2021. [Link]

DRBSD-7

Yuanjian Liu, Sheng Di, Kai Zhao, Kyle Chard, Dingwen Tao, Sian Jin, Cheng Wang, Ian Foster, and Frank Cappello,
Understanding Effectiveness of Multi-error-bounded Lossy Compression for Preserving Ranges of Interest in Scientific Analysis
Proceedings of the 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, St. Louis, MO, USA, Nov 14th, 2021. [Link]

Cluster'21

Jinyang Liu, Sheng Di, Kai Zhao, Sian Jin, Dingwen Tao, Xin Liang, Zizhong Chen, Franck Cappello
Exploring Autoencoder-Based Error-Bounded Compression for Scientific Data
Proceedings of the 23nd IEEE International Conference on Cluster Computing, Online, Sep 7 - 10, 2021. [Link]

Cluster'21

Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello
Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Proceedings of the 23nd IEEE International Conference on Cluster Computing, Online, Sep 7 - 10, 2021. [Link]

ICS'21

Yujia Zhai, Elisabeth Giem, Quan Fan, Kai Zhao, Jinyang Liu, and Zizhong Chen
FT-BLAS: A High Performance BLAS Implementation With Online Fault Tolerance
Proceeding of the 35th ACM International Conference on Supercomputing, Online, June 14 - 17, 2021.
Acceptance Rate: 24.2% (38/157) [Link]

ICDE'21

Kai Zhao, Sheng Di, Maxim Dmitriev, Thierry-Laurent D. Tonellot, Zizhong Chen, and Franck Cappello
Optimizing Error-Bounded Lossy Compression for Scientific Data by Dynamic Spline Interpolation
Proceeding of the 37th IEEE International Conference on Data Engineering, Chania, Crete, Greece, Apr 19 - 22, 2021.
Acceptance Rate: 27.5% (151/549) [Link]

IWBDR-1

Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, and Franck Cappello
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
Proceedings of the 1st International Workshop on Big Data Reduction @BigData'20, Online, Dec 10 - 13, 2020.

TPDS

Kai Zhao, Sheng Di, Sihuan Li, Xin Liang, Yujia Zhai, Jieyang Chen, Kaiming Ouyang, Franck Cappello, and Zizhong Chen
FT-CNN: Algorithm-Based Fault Tolerance for Convolutional Neural Networks
IEEE Transactions on Parallel and Distributed Systems. [Link]

PACT'20

Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, and Franck Cappello.
cuSZ: An Efficient GPU Based Error-Bounded Lossy Compression Framework for Scientific Data.
Proceedings of the 29th International Conference on Parallel Architectures and Compilation Techniques, Atlanta, GA, USA, Oct 3 - 7, 2020. Acceptance Rate: 25% (35/137) [Link]

Cluster'20

Sihuan Li, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello.
Towards End-to-end SDC Detection for HPC Applications Equipped with Lossy Compression.
Proceedings of the 22nd IEEE International Conference on Cluster Computing, Kobe, Japan, Sep 14 - 17, 2020. Acceptance Rate: 24.2% (32/132) [Link]

HPDC'20

Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Zizhong Chen, and Franck Cappello.
Significantly Improving Lossy Compression for HPC Datasets with Second-Order Prediction and Parameter Optimization.
Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing, Stockholm, Sweden, June 23 - 26, 2020. Acceptance Rate: 22.5% (16/71) [Link]

SC'19

Sihuan Li, Hongbo Li, Xin Liang, Jieyang Chen, Elisabeth Giem, Kaiming Ouyang, Kai Zhao, Sheng Di, Franck Cappello, and Zizhong Chen.
FT-iSort: Efficient Fault Tolerance for Introsort.
Proceedings of the 31st ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, Colorado, USA, Nov 17 - 22, 2019. Acceptance Rate: 20.9% (72/344) [Link]

ICS'19

Jieyang Chen, Nan Xiong, Xin Liang, Dingwen Tao, Sihuan Li, Kaiming Ouyang, Kai Zhao, Nathan DeBardeleben, Qiang Guan, and Zizhong Chen.
TSM2: Optimizing Tall-and-Skinny Matrix-Matrix Multiplication on GPUs.
Proceedings of the 33rd ACM International Conference on Supercomputing, Phoenix, AZ, USA, June 26 - 28, 2019. Acceptance Rate: 23.3% (45/193) [Link]

SC'18

Jieyang Chen, Hongbo Li, Sihuan Li, Xin Liang, Panruo Wu, Dingwen Tao, Kaiming Ouyang, Yuanlai Liu, Kai Zhao, Qiang Guan, and Zizhong Chen
Fault Tolerant One-sided Matrix Decompositions on Heterogeneous Systems with GPUs.
Proceedings of the 30th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, Texas, USA, Nov 11 - 16, 2018. Acceptance Rate: 19.1% (55/288). [Link]