Chris Gates

1.2k citations
10 papers · 563 · 1 hit paper · h-index 5

Impact in

Papers in

Chris Gates

9 papers receiving 529 citations

Chris Gates's Hit Papers

Using probabilistic generative models for ranking risks of Android apps 2012 · 261 citations
2610+4+9Years since publication50100150200250

Peers

Chris Gates
Comparison fields: 5 of 54
  • Software 203
  • Signal Processing 477
  • Computer Networks and Communications 333
  • Information Systems 280
  • Artificial Intelligence 81
Replace Birhanu Eshete with:
Birhanu Eshete United States
Shuhao Li China
Thomas Panas United States
Tyler McDonnell United States
Oisín Boydell Ireland
Rui Shu United States
Senthil Mani India
Jonathan Spring United States
Zhengzi Xu Singapore
Chris Gates relative to Birhanu Eshete United States Birhanu Eshete's profile →
Citations per field
00.5×5.1×
Birhanu Eshete · 1×
Citations per year

Countries citing papers authored by Chris Gates

Since Specialization
Citations

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

Fields of papers citing papers by Chris Gates

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chris Gates, 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 Gates Line = papers co-authored together Chris Gates links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Using probabilistic generative models for ranking risks of Android apps
Hit paper breakdown →
2012261
2 2012196
3 201735
4 201831
5 201730
6 20233
7 20203
8 20173
9
Using probabilistic generative models for ranking risks of android apps
20131
10 20250

About Chris Gates

Chris Gates is a scholar working on Information Systems, Signal Processing, Computer Networks and Communications, Information Systems and Management and Cancer Research, having authored 10 papers that have together received 563 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (5 papers), Network Security and Intrusion Detection (3 papers), Spam and Phishing Detection (2 papers), Web Data Mining and Analysis (2 papers), Cancer Genomics and Diagnostics (2 papers), Scientific Computing and Data Management (2 papers), Advanced Proteomics Techniques and Applications (1 paper) and Retinal Diseases and Treatments (1 paper). The work is most often cited by research in Software (203 citations), Signal Processing (477 citations), Computer Networks and Communications (333 citations), Information Systems (280 citations) and Artificial Intelligence (81 citations). Chris Gates has collaborated with scholars based in United States. Frequent co-authors include Cristina Nita-Rotaru, Ian Molloy, Rahul Potharaju, Ninghui Li, Hao Peng, Yuan Qi, Kevin Roundy, Peter Ulintz, Wei-Sheng Wu and Yevgeniy Vorobeychik. Their work appears in journals such as Journal of Emergency Nursing, Journal of Biomolecular Techniques JBT, IEEE Transactions on Visualization and Computer Graphics and Methods in molecular biology.

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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