Pli

Pengyuan Li, Ph.D. Student

I received my B.Sc in 2013 from Chongqing University. I received my M.S. degree in Computer Science in 2016 from Illinois Institute of Technology. I started my Ph.D. at the IIT DBGroup in 2018.

Awards

EDBT 2026 Best Paper Award (2026)

Teaching

I have been TA for the following courses:

2018 Fall: -
2018 Fall: -

Research Projects

I am involved in the following research projects:

GProM - A database-independent middleware for computing the provenance of queries, updates, and transactions
Relevance-based Data Management - We use provenance to determine what data is relevant for which task and then exploit this information to improve a wide range of data management tasks.

Collaborators

I am collaborating with:

Dieter Gawlick - Oracle
Danica Porobic - Oracle
Oliver Kennedy - SUNY Buffalo
Vasudha Krishnaswamy - Oracle
Venkatesh Radhakrishnan
Zhen Hua Liu - Oracle

Publications

In-memory Incremental Maintenance of Provenance Sketches
Pengyuan Li, Boris Glavic, Dieter Gawlick, Vasudha Krishnaswamy, Zhen Hua Liu, Danica Porobic and Xing Niu
Proceedings 29th International Conference on Extending Database Technology, EDBT 2026, Tampere, Finland, March 24-27, 2026 (2026), pp. 56–68.

@inproceedings{LG26,
  author = {Li, Pengyuan and Glavic, Boris and Gawlick, Dieter and Krishnaswamy, Vasudha and Liu, Zhen Hua and Porobic, Danica and Niu, Xing},
  editor = {Lehner, Wolfgang and Braganholo, Vanessa and Stefanidis, Kostas and Zhang, Zheying and Krause, Alexander and Pimentel, Jo{\~{a}}o Felipe Nicolaci},
  title = {In-memory Incremental Maintenance of Provenance Sketches},
  booktitle = {Proceedings 29th International Conference on Extending Database Technology, {EDBT} 2026, Tampere, Finland, March 24-27, 2026},
  pages = {56--68},
  publisher = {OpenProceedings.org},
  year = {2026},
  award = {best paper},
  url = {https://doi.org/10.48786/edbt.2026.05},
  doi = {10.48786/EDBT.2026.05},
  keywords = {Provenance; Data Skipping; Relevance-based Data Management; Incremental Maintenance},
  projects = {Relevance-based Data Management},
  pdfurl = {http://www.cs.uic.edu/%7ebglavic/dbgroup/assets/pdfpubls/LG26.pdf},
  longversionurl = {https://arxiv.org/pdf/2505.20683},
  venueshort = {EDBT}
}

details

Towards an Objective Metric for Data Value Through Relevance
Boris Glavic, Pengyuan Li, Ziyu Liu, Dieter Gawlick, Vasudha Krishnaswamy, Danica Porobic and Zhen Hua Liu
Proceedings of the 14th Conference on Innovative Data Systems (2024).

pdf
details

@inproceedings{GL24,
  author = {Glavic, Boris and Li, Pengyuan and Liu, Ziyu and Gawlick, Dieter and Krishnaswamy, Vasudha and Porobic, Danica and Liu, Zhen Hua},
  title = {Towards an Objective Metric for Data Value Through Relevance},
  booktitle = {Proceedings of the 14th Conference on Innovative Data Systems},
  year = {2024},
  projects = {Provenance; Relevance-based Data Management},
  pdfurl = {http://www.cs.uic.edu/%7ebglavic/dbgroup/assets/pdfpubls/GL24.pdf},
  venueshort = {CIDR}
}

details

Self-tuning Database Operations by Assessing the Importance of Data
Boris Glavic, Pengyuan Li and Ziyu Liu
Technical Report #UIC/CS-DB-2023-01
Illinois Institute of Technology.

pdf
details

@techreport{GL23,
  author = {Glavic, Boris and Li, Pengyuan and Liu, Ziyu},
  title = {Self-tuning Database Operations by Assessing the Importance of Data},
  institution = {Illinois Institute of Technology},
  year = {2023},
  number = {UIC/CS-DB-2023-01},
  pdfurl = {http://www.cs.uic.edu/%7ebglavic/dbgroup/assets/pdfpubls/GL23.pdf},
  projects = {Relevance-based Data Management},
  keywords = {Provenance, Relevance-based Data Management},
  venueshort = {Techreport}
}

details

Oracle PBDS Experiments
Boris Glavic, Xing Niu, Pengyuan Li and Ziyu Liu
Technical Report #UIC/Cs-db-2022-01
Illinois Institute of Technology.

pdf
details

@techreport{GN22,
  author = {Glavic, Boris and Niu, Xing and Li, Pengyuan and Liu, Ziyu},
  title = {Oracle PBDS Experiments},
  institution = {Illinois Institute of Technology},
  year = {2022},
  number = {UIC/Cs-db-2022-01},
  pdfurl = {http://www.cs.uic.edu/%7ebglavic/dbgroup/assets/pdfpubls/GN22.pdf},
  projects = {Relevance-based Data Management},
  keywords = {Provenance, Relevance-based Data Management},
  venueshort = {Techreport}
}

details

Provenance-based Data Skipping
Xing Niu, Ziyu Liu, Pengyuan Li, Boris Glavic, Dieter Gawlick, Vasudha Krishnaswamy, Zhen Hua Liu and Danica Porobic
Proceedings of the VLDB Endowment. 15, 3 (2021) , 451–464.
- doi
- pdf
- extended version
- details
- reproducibility
```
@article{NL21,
  author = {Niu, Xing and Liu, Ziyu and Li, Pengyuan and Glavic, Boris and Gawlick, Dieter and Krishnaswamy, Vasudha and Liu, Zhen Hua and Porobic, Danica},
  keywords = {Provenance, Data Skipping, Relevance-based Data Management},
  title = {Provenance-based Data Skipping},
  journal = {Proceedings of the VLDB Endowment},
  projects = {Relevance-based Data Management},
  pages = {451 - 464},
  volume = {15},
  issue = {3},
  year = {2021},
  doi = {10.14778/3494124.3494130},
  reproducibility = {https://github.com/IITDBGroup/2021_pbds_reproducibility},
  reproducibilitybatch = {available},
  venueshort = {{PVLDB}},
  pdfurl = {https://vldb.org/pvldb/vol15/p451-niu.pdf},
  longversionurl = {https://arxiv.org/pdf/2104.12815}
}
```
Database systems use static analysis to determine upfront which data is needed for answering a query and use indexes and other physical design techniques to speed-up access to that data. However, for important classes of queries, e.g., HAVING and top-k queries, it is impossible to determine up-front what data is relevant. To overcome this limitation, we develop provenance-based data skipping (PBDS), a novel approach that generates provenance sketches to concisely encode what data is relevant for a query. Once a provenance sketch has been captured it is used to speed up subsequent queries. PBDS can exploit physical design artifacts such as indexes and zone maps.
details