James Koppel
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Information Systems top 5%
- Software Engineering Research
- Blockchain Technology Applications and Security
Papers in
-
- Logic, programming, and type systems 4
- Adversarial Robustness in Machine Learning 1
-
- Software Engineering Research 5
- Spam and Phishing Detection 1
- Co-authors
- Armando Solar-Lezama (7 shared papers)Angela T. Chen (1 shared paper)Daniel J. Weitzner (1 shared paper)Michael A. Specter (1 shared paper)Nadia Polikarpova (1 shared paper)Daniel Jackson (1 shared paper)Maxwell Nye (1 shared paper)Leslie Pack Kaelbling (1 shared paper)
- Journals
- Proceedings of the ACM on Programming Languages (2 papers)DSpace@MIT (Massachusetts Institute of Technology) (3 papers)Chalmers Research (Chalmers University of Technology) (1 paper)
- Partner nations
- United StatesChinaFrance
In The Last Decade
James Koppel
9 papers receiving 229 citations
Peers
Comparison fields: 5 of 30
- Software 154
- Information Systems 160
- Signal Processing 28
- Artificial Intelligence 66
- Hardware and Architecture 12
Countries citing papers authored by James Koppel
This map shows the geographic impact of James Koppel'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 James Koppel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Koppel more than expected).
Fields of papers citing papers by James Koppel
This network shows the impact of papers produced by James Koppel. 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 James Koppel. The network helps show where James Koppel may publish in the future.
Co-authors
The 12 scholars most cited alongside James Koppel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 154 | |
| 2 | The Ballot is Busted Before the Blockchain: A Security Analysis of Voatz, the First Internet Voting Application Used in U.S. Federal Elections. | 2020 | 36 |
| 3 | 2020 | 27 | |
| 4 | 2022 | 12 | |
| 5 | 2017 | 2 | |
| 6 | 2023 | 2 | |
| 7 | 2018 | 1 | |
| 8 | 2020 | 1 | |
| 9 | A large-scale benchmark for few-shot program induction and synthesis | 2021 | 1 |
| 10 | A Language for Counterfactual Generative Models | 2021 | 1 |
About James Koppel
James Koppel is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Software and Hardware and Architecture, having authored 10 papers that have together received 237 indexed citations. Recurring topics across this work include Software Engineering Research (5 papers), Software Testing and Debugging Techniques (4 papers), Logic, programming, and type systems (4 papers), Parallel Computing and Optimization Techniques (3 papers), Software Reliability and Analysis Research (2 papers), Spam and Phishing Detection (1 paper), Software System Performance and Reliability (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Software (154 citations), Information Systems (160 citations), Signal Processing (28 citations), Artificial Intelligence (66 citations) and Hardware and Architecture (12 citations). James Koppel has collaborated with scholars based in United States, China and France. Frequent co-authors include Armando Solar-Lezama, Angela T. Chen, Daniel J. Weitzner, Michael A. Specter, Nadia Polikarpova, Daniel Jackson, Maxwell Nye, Leslie Pack Kaelbling, Josh Tenenbaum and Ferran Alet. Their work appears in journals such as Proceedings of the ACM on Programming Languages, DSpace@MIT (Massachusetts Institute of Technology) and Chalmers Research (Chalmers University of Technology).
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.