Cecilia M. Procopiuc
- Artificial Intelligence top 0.5%
- Signal Processing top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 1%
- Computer Networks and Communications top 5%
- Co-authors
- Divesh SrivastavaPhilip S. YuCharų C. AggarwalGraham CormodeJoel L. WolfJong Soo ParkPankaj K. AgarwalXiaokui Xiao
- Topics
- Data Management and Algorithms (13 papers)Privacy-Preserving Technologies in Data (10 papers)Computational Geometry and Mesh Generation (7 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringProceedings of the VLDB EndowmentACM SIGMOD Record
- Partner nations
- United StatesSingaporeUnited Kingdom
In The Last Decade
Cecilia M. Procopiuc
34 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 2.1k
- Signal Processing 701
- Computer Vision and Pattern Recognition 620
- Information Systems 585
- Computer Networks and Communications 356
Countries citing papers authored by Cecilia M. Procopiuc
This map shows the geographic impact of Cecilia M. Procopiuc's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cecilia M. Procopiuc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cecilia M. Procopiuc more than expected).
Fields of papers citing papers by Cecilia M. Procopiuc
This network shows the impact of papers produced by Cecilia M. Procopiuc. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cecilia M. Procopiuc. The network helps show where Cecilia M. Procopiuc may publish in the future.
Co-authorship network of co-authors of Cecilia M. Procopiuc
This figure shows the co-authorship network connecting the top 25 collaborators of Cecilia M. Procopiuc. A scholar is included among the top collaborators of Cecilia M. Procopiuc based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cecilia M. Procopiuc. Cecilia M. Procopiuc is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 212 | |
| 2 | 68 | |
| 3 | 161 | |
| 4 | 23 | |
| 5 | 1 | |
| 6 | 260 | |
| 7 | 63 | |
| 8 | 15 | |
| 9 | 4 | |
| 10 | 12 | |
| 11 | 12 | |
| 12 | Advances in Indexing for Mobile Objects. | 14 |
| 13 | 81 | |
| 14 | 217 | |
| 15 | 4 | |
| 16 | 24 | |
| 17 | Fast algorithms for projected clusteringbreakdown → | 612 |
| 18 | 344 | |
| 19 | 60 | |
| 20 | 4 |
About Cecilia M. Procopiuc
Cecilia M. Procopiuc is a scholar working on Computer Graphics and Computer-Aided Design, Signal Processing and Computer Science Applications, having authored 34 papers that have together received 2.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (13 papers), Privacy-Preserving Technologies in Data (10 papers) and Computational Geometry and Mesh Generation (7 papers). The work is most often cited by research in Artificial Intelligence (2.1k citations), Signal Processing (701 citations) and Computer Science Applications (256 citations). Cecilia M. Procopiuc has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Divesh Srivastava, Philip S. Yu, Charų C. Aggarwal, Graham Cormode, Joel L. Wolf, Jong Soo Park, Pankaj K. Agarwal, Xiaokui Xiao, Jun Zhang and Ting Yu. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment and ACM SIGMOD Record.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.