Chris Gates

1.2k citations
12 papers · 653 · 1 hit paper · h-index 6

Impact in

Papers in

Chris Gates

11 papers receiving 615 citations

Chris Gates's Hit Papers

Using probabilistic generative models for ranking risks of Android apps 2012 · 299 citations
2990+4+9Years since publication50100150200250

Peers

Chris Gates
Comparison fields: 5 of 54
  • Software 246
  • Signal Processing 560
  • Computer Networks and Communications 399
  • Information Systems 321
  • Artificial Intelligence 93
Replace Xiaoqi Jia with:
Xiaoqi Jia China
Birhanu Eshete United States
Peter Teufl Austria
Shuhao Li China
Tyler McDonnell United States
Dean Frederick Jerding United States
Oisín Boydell Ireland
Benjamin Bichsel Switzerland
Rui Shu United States
Chris Gates relative to Xiaoqi Jia China Xiaoqi Jia's profile →
Citations per field
00.5×2×3.2×
Xiaoqi Jia · 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

12 of 12 papers shown
#Work
1
Using probabilistic generative models for ranking risks of Android apps
Hit paper breakdown →
2012299
2 2012228
3 201739
4 201831
5 201731
6 20159
7 20234
8 20233
9
Using probabilistic generative models for ranking risks of android apps
20133
10 20203
11 20173
12 20250

About Chris Gates

Chris Gates is a scholar working on Signal Processing, Information Systems, Computer Networks and Communications, Information Systems and Management and Artificial Intelligence, having authored 12 papers that have together received 653 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (7 papers), Network Security and Intrusion Detection (5 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 (246 citations), Signal Processing (560 citations), Computer Networks and Communications (399 citations), Information Systems (321 citations) and Artificial Intelligence (93 citations). Chris Gates has collaborated with scholars based in United States and Spain. Frequent co-authors include Ian Molloy, Rahul Potharaju, Ninghui Li, Cristina Nita-Rotaru, Yuan Qi, Hao Peng, Kevin Roundy, Peter Ulintz, Yevgeniy Vorobeychik and Wei-Sheng Wu. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Journal of Biomolecular Techniques JBT, Journal of Emergency Nursing, Lecture notes in computer science 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.

Explore authors with similar magnitude of impact