Paul Prasse

27 papers receiving 257 citations

Peers

Paul Prasse
Comparison fields: 5 of 67
  • Human-Computer Interaction 70
  • Analytical Chemistry 41
  • Signal Processing 43
  • Cognitive Neuroscience 50
  • Artificial Intelligence 73
Replace Pinki Kumari with:
Pinki Kumari India
Guanghua Gu China
Sohail Masood Bhatti Pakistan
Noura A. Semary Egypt
M. Mohamed Sathik India
S. S. Shylaja India
Nidhal K. El Abbadi Iraq
Xinyu Zhu China
Abu Sayeed Bangladesh
Fei Long China
Paul Prasse relative to Pinki Kumari India Pinki Kumari's profile →
Citations per field
00.5×6.5×
Pinki Kumari · 1×
Citations per year

Countries citing papers authored by Paul Prasse

Since Specialization
Citations

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

Fields of papers citing papers by Paul Prasse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202049
2 202136
3 201733
4 202020
5 202217
6 202313
7 202011
8 202310
9
Learning to identify concise regular expressions that describe email campaigns
20159
10 20249
11 20226
12 20226
13 20236
14 20215
15
Learning to Identify Regular Expressions that Describe Email Campaigns
20125
16 20234
17 20244
18 20243
19 20243
20 20223

About Paul Prasse

Paul Prasse is a scholar working on Artificial Intelligence, Human-Computer Interaction, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Ophthalmology, having authored 29 papers that have together received 264 indexed citations. Recurring topics across this work include Gaze Tracking and Assistive Technology (9 papers), Glaucoma and retinal disorders (4 papers), Topic Modeling (4 papers), EEG and Brain-Computer Interfaces (4 papers), Computational Drug Discovery Methods (3 papers), Network Security and Intrusion Detection (3 papers), Neurobiology of Language and Bilingualism (3 papers) and Internet Traffic Analysis and Secure E-voting (3 papers). The work is most often cited by research in Human-Computer Interaction (70 citations), Analytical Chemistry (41 citations), Signal Processing (43 citations), Cognitive Neuroscience (50 citations) and Artificial Intelligence (73 citations). Paul Prasse has collaborated with scholars based in Germany, Switzerland and Czechia. Frequent co-authors include Tobias Scheffer, Lena A. Jäger, Tomáš Pevný, Patrick Haller, Sven Connemann, Ludovic Duponchel, Jakub Vrábel, Erik Képeš, Manoj Kumar Gundawar and Xiaofeng Tan. Their work appears in journals such as NAR Genomics and Bioinformatics, Proceedings of the ACM on Human-Computer Interaction, Computers & Graphics, PLoS ONE and Spectrochimica Acta Part B Atomic Spectroscopy.

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