Christine Piatko

8.9k total citations · 2 hit papers
57 papers, 5.8k citations indexed

About

Christine Piatko is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Christine Piatko has authored 57 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 10 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Christine Piatko's work include Topic Modeling (16 papers), Natural Language Processing Techniques (16 papers) and Data Management and Algorithms (9 papers). Christine Piatko is often cited by papers focused on Topic Modeling (16 papers), Natural Language Processing Techniques (16 papers) and Data Management and Algorithms (9 papers). Christine Piatko collaborates with scholars based in United States and Israel. Christine Piatko's co-authors include Ruth Silverman, Angela Y. Wu, Nathan S. Netanyahu, David M. Mount, Tapas Kanungo, Holly Rushmeier, Gregory Ward Larson, James Mayfield, Paul McNamee and Jason Eisner and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and IEEE Transactions on Image Processing.

In The Last Decade

Christine Piatko

55 papers receiving 5.3k citations

Hit Papers

An efficient k-means clustering algorithm: analysis and i... 1997 2026 2006 2016 2002 1997 1000 2.0k 3.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Christine Piatko United States 19 2.1k 2.1k 683 602 531 57 5.8k
Sherjil Ozair United States 6 3.5k 1.6× 2.7k 1.3× 628 0.9× 294 0.5× 361 0.7× 7 8.5k
Mehdi Mirza Canada 5 3.9k 1.9× 3.1k 1.5× 719 1.1× 290 0.5× 365 0.7× 5 9.2k
Jean Pouget-Abadie United States 6 3.3k 1.6× 2.5k 1.2× 574 0.8× 271 0.5× 345 0.6× 11 8.2k
Ruth Silverman United States 14 2.6k 1.2× 2.0k 1.0× 1.0k 1.5× 542 0.9× 586 1.1× 27 6.5k
Tapas Kanungo United States 22 2.3k 1.1× 2.2k 1.1× 727 1.1× 902 1.5× 603 1.1× 75 5.9k
Angela Y. Wu United States 17 2.8k 1.3× 2.0k 1.0× 1.0k 1.5× 542 0.9× 719 1.4× 53 6.9k
Li Zhang China 44 3.3k 1.6× 3.3k 1.6× 599 0.9× 1.4k 2.3× 604 1.1× 485 9.2k
Mark E. Shields United States 3 3.1k 1.5× 4.3k 2.1× 814 1.2× 494 0.8× 416 0.8× 6 10.7k
Nathan S. Netanyahu United States 23 3.1k 1.5× 2.2k 1.1× 1.2k 1.8× 600 1.0× 735 1.4× 90 7.5k

Countries citing papers authored by Christine Piatko

Since Specialization
Citations

This map shows the geographic impact of Christine Piatko'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 Christine Piatko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christine Piatko more than expected).

Fields of papers citing papers by Christine Piatko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christine Piatko. 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 Christine Piatko. The network helps show where Christine Piatko may publish in the future.

Co-authorship network of co-authors of Christine Piatko

This figure shows the co-authorship network connecting the top 25 collaborators of Christine Piatko. A scholar is included among the top collaborators of Christine Piatko 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 Christine Piatko. Christine Piatko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
McElroy, K., Nam Q. Le, Ian McCue, et al.. (2023). Closed-loop superconducting materials discovery. npj Computational Materials. 9(1). 11 indexed citations
2.
Burkom, Howard, Yevgeniy Elbert, Christine Piatko, & Clay Fink. (2015). A Term-based Approach to Asyndromic Determination of Significant Case Clusters. Online Journal of Public Health Informatics. 7(1). 6 indexed citations
3.
McNamee, Paul, James Mayfield, & Christine Piatko. (2011). Processing Named Entities in Text. 2 indexed citations
4.
Sayeed, Asad, Tamer Elsayed, Nikesh Garera, et al.. (2009). Arabic Cross-Document Coreference Resolution. Meeting of the Association for Computational Linguistics. 357–360.
5.
McNamee, Paul, Mark Dredze, Adam Gerber, et al.. (2009). HLTCOE Approaches to Knowledge Base Population at TAC 2009. Maryland Shared Open Access Repository (USMAI Consortium). 25 indexed citations
6.
Mayfield, James, Bonnie J. Dorr, Jason Eisner, et al.. (2009). Cross-Document Coreference Resolution: A Key Technology for Learning by Reading. Maryland Shared Open Access Repository (USMAI Consortium). 65–70. 25 indexed citations
7.
Finin, Tim, Zareen Syed, James Mayfield, Paul McNamee, & Christine Piatko. (2009). Using Wikitology for Cross-Document Entity Coreference Resolution. Maryland Shared Open Access Repository (USMAI Consortium). 29–35. 16 indexed citations
8.
Cancro, George, Russell Turner, L. Nguyen, et al.. (2007). An Interactive Visualization System for Analyzing Spacecraft Telemetry. 1–9. 2 indexed citations
9.
Mayfield, James, et al.. (2003). Lattice-based tagging using support vector machines. 303–308. 9 indexed citations
10.
McNamee, Paul, James Mayfield, & Christine Piatko. (2002). Haircut: a system for multilingual text retrieval in java. Journal of computing sciences in colleges. 17(3). 8–22. 3 indexed citations
11.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2002). An efficient k-means clustering algorithm: analysis and implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 24(7). 881–892. 3878 indexed citations breakdown →
12.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2002). A local search approximation algorithm for k-means clustering. 10–18. 261 indexed citations
13.
Mayfield, James, Paul McNamee, Cash Costello, Christine Piatko, & Amit Banerjee. (2001). JHU/APL at TREC 2001: Experiments in Filtering and in Arabic, Video, and Web Retrieval. Text REtrieval Conference. 27 indexed citations
14.
Piatko, Christine, et al.. (2001). Path planning for mine countermeasures command and control. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4394. 836–836. 8 indexed citations
15.
McNamee, Paul, James Mayfield, & Christine Piatko. (2000). The HAIRCUT System at TREC-9.. Text REtrieval Conference. 7 indexed citations
16.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2000). The analysis of a simple k -means clustering algorithm. 100–109. 67 indexed citations
17.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (1999). Computing nearest neighbors for moving points and applications to clustering. Symposium on Discrete Algorithms. 931–932. 16 indexed citations
18.
Mayfield, James, Paul McNamee, & Christine Piatko. (1999). The JHU/APL HAIRCUT System at TREC-8.. Text REtrieval Conference. 19 indexed citations
19.
Larson, Gregory Ward, Holly Rushmeier, & Christine Piatko. (1997). A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics. 3(4). 291–306. 535 indexed citations breakdown →
20.
Khuller, Samir, et al.. (1995). <title>Localizing an object with finger probes</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2356. 272–283. 2 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026