Pengzhan Zhao

Orcid: 0000-0003-1415-8020

According to our database1, Pengzhan Zhao authored at least 13 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
On Repairing Quantum Programs Using ChatGPT.
CoRR, 2024

2023
Bugs4Q: A benchmark of existing bugs to enable controlled testing and debugging studies for quantum programs.
J. Syst. Softw., November, 2023

VQPy: An Object-Oriented Approach to Modern Video Analytics.
CoRR, 2023

An Empirical Study of Bugs in Quantum Machine Learning Frameworks.
Proceedings of the IEEE International Conference on Quantum Software, 2023

Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs.
Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

QChecker: Detecting Bugs in Quantum Programs via Static Analysis.
Proceedings of the 4th IEEE/ACM International Workshop on Quantum Software Engineering, 2023

2022
A Comprehensive Study of Bug Fixes in Quantum Programs.
Proceedings of the IEEE International Conference on Software Analysis, 2022

AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures.
Proceedings of the ASPLOS '22: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, 28 February 2022, 2022

2021
Bugs4Q: A Benchmark of Real Bugs for Quantum Programs.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

Identifying Bug Patterns in Quantum Programs.
Proceedings of the 2nd IEEE/ACM International Workshop on Quantum Software Engineering, 2021

DISC: A Dynamic Shape Compiler for Machine Learning Workloads.
Proceedings of the EuroMLSys@EuroSys 2021, 2021

2020
FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads.
CoRR, 2020

Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics.
Proceedings of the SIGCOMM '20: Proceedings of the 2020 Annual conference of the ACM Special Interest Group on Data Communication on the applications, 2020


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