Ethan Fast

1.8k citations
17 papers · 872 · 1 hit paper · h-index 10

Impact in

Papers in

Ethan Fast

17 papers receiving 834 citations

Ethan Fast's Hit Papers

Long-Term Trends in the Public Perception of Artificial Intelligence 2017 · 305 citations
3050+3+6Years since publication100200300

Peers

Ethan Fast
Comparison fields: 5 of 88
  • Health Informatics 47
  • Software 108
  • Computer Science Applications 97
  • Safety Research 106
  • Artificial Intelligence 261
Replace Alireza Ahadi with:
Alireza Ahadi Australia
Erik T. Mueller United States
Katharina A. Zweig Germany
Marc–André Kaufhold Germany
Kevin C. Haudek United States
Andrew Smart United States
Mark Simkin United States
Amy X. Zhang United States
Frances S. Grodzinsky United States
Roman Lukyanenko Canada
Ethan Fast relative to Alireza Ahadi Australia Alireza Ahadi's profile →
Citations per field
00.5×6.7×
Alireza Ahadi · 1×
Citations per year

Countries citing papers authored by Ethan Fast

Since Specialization
Citations

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

Fields of papers citing papers by Ethan Fast

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1
Long-Term Trends in the Public Perception of Artificial Intelligence
Hit paper breakdown →
2017305
2 2019223
3 201888
4 201367
5 201051
6 202041
7 201426
8 201314
9 201612
10 201611
11 20179
12 20217
13 20167
14 20184
15 20173
16
Software Mutational Robustness: Bridging The Gap Between Mutation Testing and Evolutionary Biology
20122
17 20152

About Ethan Fast

Ethan Fast is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Software and Molecular Biology, having authored 17 papers that have together received 872 indexed citations. Recurring topics across this work include Software Engineering Research (6 papers), Intelligent Tutoring Systems and Adaptive Learning (3 papers), Topic Modeling (3 papers), Software Testing and Debugging Techniques (3 papers), Online Learning and Analytics (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Immunotherapy and Immune Responses (2 papers) and Psychology of Moral and Emotional Judgment (2 papers). The work is most often cited by research in Health Informatics (47 citations), Software (108 citations), Computer Science Applications (97 citations), Safety Research (106 citations) and Artificial Intelligence (261 citations). Ethan Fast has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Eric Horvitz, Michael S. Bernstein, Binbin Chen, Westley Weimer, Stephanie Forrest, Joshua E. Elias, Lisa E. Wagar, Brian J. Sworder, Ronald Levy and Russ B. Altman. Their work appears in journals such as Genetic Programming and Evolvable Machines, Nature Biotechnology, Blood, Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the International AAAI Conference on Web and Social Media.

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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