Chris Giannella

2.4k citations
35 papers · 1.2k · h-index 14

Impact in

Papers in

Chris Giannella

32 papers receiving 1.1k citations

Peers

Chris Giannella
Comparison fields: 5 of 84
  • Signal Processing 352
  • Computer Networks and Communications 571
  • Artificial Intelligence 786
  • Information Systems 439
  • Statistical and Nonlinear Physics 97
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Stephen D. Bay United States
Benjamin Moseley United States
Sharma Chakravarthy United States
Byron Choi Hong Kong
Panagiotis Karras Denmark
Ran Wolff Israel
Arijit Khan Singapore
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Citations per field
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Citations per year

Countries citing papers authored by Chris Giannella

Since Specialization
Citations

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

Fields of papers citing papers by Chris Giannella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chris Giannella, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chris Giannella Line = papers co-authored together Chris Giannella links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mining Frequent Patterns in Data Streams at Multiple Time Granularities
2002300
2 2006142
3 2006130
4 2005113
5 200897
6 200693
7 201161
8 200560
9 200749
10 200344
11 200831
12 200521
13 202114
14 201214
15 20098
16 20157
17 20056
18
On the Privacy of Euclidean Distance Preserving Data Perturbation
20095
19 20175
20 20095

About Chris Giannella

Chris Giannella is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Management and Algorithms (8 papers), Data Stream Mining Techniques (8 papers), Data Mining Algorithms and Applications (8 papers), Natural Language Processing Techniques (6 papers), Advanced Database Systems and Queries (5 papers), Topic Modeling (5 papers), Privacy-Preserving Technologies in Data (4 papers) and Anomaly Detection Techniques and Applications (4 papers). The work is most often cited by research in Signal Processing (352 citations), Computer Networks and Communications (571 citations), Artificial Intelligence (786 citations), Information Systems (439 citations) and Statistical and Nonlinear Physics (97 citations). Chris Giannella has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include H. Kargupta, Souptik Datta, Xifeng Yan, Jiawei Han, Philip S. Yu, Hillol Kargupta, Ran Wolff, Kanishka Bhaduri, Joel W. Branch and Bolesław K. Szymański. Their work appears in journals such as Natural Language Engineering, Statistical Analysis and Data Mining The ASA Data Science Journal, IEEE Internet Computing, Information Systems and Information Sciences.

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.

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