Department of Computer Science
Building & Room:
851 S. Morgan St, Chicago, IL 60607
Stavros Sintos is an Assistant Professor in the Department of Computer Science at the University of Illinois Chicago. Before joining UIC, he was a Postdoctoral Scholar on Data Management at the University of Chicago working with Asst. Prof. Sanjay Krishnan and Prof. Michael Franklin. He obtained his Ph.D. in Computer Science at Duke University under the supervision of Prof. Pankaj K. Agarwal. He also obtained his B.S. in the Department of Computer Science at the University of Ioannina in Greece. He is a recipient of the James B. Duke Fellowship, and he was nominated for the 2019-2020 outstanding Ph.D. dissertation award for his thesis titled “Efficient Algorithms for Querying Large and Uncertain Data”. His main research interest is in the design of efficient algorithms for problems in databases, data mining, and data management. In particular, he works on designing practical geometric indexes with theoretical guarantees focusing on approximate query processing, top-k queries, summarization queries, and join queries. His work has been published in top-tier conferences and journals such as VLDB, SIGMOD, ICDE, PODS, ICALP, JCSS. For more details, please visit stavrossintos.info
- Bruno Barbarioli, Gabriel Mersy, Stavros Sintos, and Sanjay Krishnan. Hierarchical Residual Encoding for Multiresolution Time Series Compression. ACM SIGMOD International Conference on Management of Data (SIGMOD), 2023.
- Xi Liang, Stavros Sintos, and Sanjay Krishnan. JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. IEEE International Conference on Data Engineering (ICDE), 2023.
- Xiao Hu, Stavros Sintos, Junyang Gao, Pankaj K. Agarwal, and Jun Yang. Computing Complex Temporal Join Queries Efficiently. ACM SIGMOD International Conference on Management of Data (SIGMOD), 2022.
- Pankaj K. Agarwal, Xiao Hu, Stavros Sintos, and Jun Yang. Dynamic Enumeration of Similarity Joins. International Colloquium on Automata, Languages and Programming (ICALP), 2021
- Xi Liang, Stavros Sintos, Zechao Shang, and Sanjay Krishnan. Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
- Pankaj K. Agarwal, Stavros Sintos, and Alex Steiger. Efficient Indexes for Diverse Top-k Range Queries. ACM Symposium on Principles of Database Systems (PODS), 2020.
- Brett Walenz, Stavros Sintos, Sudeepa Roy, and Jun Yang. Learning to Sample: Counting with Complex Queries. International Conference on Very Large Data Bases (PVLDB), 2019.
- Stavros Sintos, Pankaj K. Agarwal, and Jun Yang. Selecting Data to Clean for Fact Checking: Minimizing Uncertainty vs. Maximizing Surprise. International Conference on Very Large Data Bases (PVLDB), 2019.
- Pankaj K. Agarwal, Nirman Kumar, Stavros Sintos, and Subhash Suri. Range-Max Queries on Uncertain Data. Invited paper in special issue of Journal of Computer and System Sciences, Vol. 94, 2018.
- Pankaj K. Agarwal, Nirman Kumar, Stavros Sintos, and Subhash Suri. Efficient Algorithms for k-Regret Minimizing Sets. International Symposium on Experimental Algorithms (SEA), 2017.
- Stavros Sintos, and Panayiotis Tsaparas. Using Strong Triadic Closure to Characterize Ties in Social Networks. ACM International Conference on Knowledge Discovery and Data Mining (KDD), 2014.