Jared Roesch
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
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- Parallel Computing and Optimization Techniques
Papers in
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- Logic, programming, and type systems 4
- Security and Verification in Computing 3
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- Parallel Computing and Optimization Techniques 5
- Physical Unclonable Functions (PUFs) and Hardware Security 2
- Co-authors
- Ben Hardekopf (7 shared papers)Kyle Dewey (2 shared papers)Dan Suciu (1 shared paper)Shumo Chu (1 shared paper)Alvin Cheung (1 shared paper)Leonardo de Moura (1 shared paper)Sebastian Ullrich (1 shared paper)Jeremy Avigad (1 shared paper)
- Journals
- IEEE Micro (2 papers)ACM SIGPLAN Notices (1 paper)Proceedings of the ACM on Programming Languages (1 paper)Proceedings of the VLDB Endowment (1 paper)ACM SIGARCH Computer Architecture News (1 paper)
- Partner nations
- United StatesChinaAustria
In The Last Decade
Jared Roesch
11 papers receiving 170 citations
Peers
Comparison fields: 5 of 25
- Software 87
- Hardware and Architecture 25
- Signal Processing 38
- Information Systems 62
- Artificial Intelligence 77
Countries citing papers authored by Jared Roesch
This map shows the geographic impact of Jared Roesch'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 Jared Roesch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jared Roesch more than expected).
Fields of papers citing papers by Jared Roesch
This network shows the impact of papers produced by Jared Roesch. 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 Jared Roesch. The network helps show where Jared Roesch may publish in the future.
Co-authors
The 22 scholars most cited alongside Jared Roesch, 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 | 2015 | 51 | |
| 2 | 2014 | 33 | |
| 3 | 2018 | 32 | |
| 4 | 2017 | 27 | |
| 5 | 2013 | 14 | |
| 6 | 2019 | 5 | |
| 7 | 2017 | 5 | |
| 8 | Relay: A High-Level IR for Deep Learning. | 2019 | 4 |
| 9 | 2020 | 2 | |
| 10 | 2025 | 1 | |
| 11 | 2018 | 1 | |
| 12 | 2013 | 0 | |
| 13 | 2017 | 0 |
About Jared Roesch
Jared Roesch is a scholar working on Artificial Intelligence, Hardware and Architecture, Information Systems, Electrical and Electronic Engineering and Software, having authored 13 papers that have together received 175 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (5 papers), Software Engineering Research (5 papers), Logic, programming, and type systems (4 papers), Software Testing and Debugging Techniques (3 papers), Radiation Effects in Electronics (3 papers), Security and Verification in Computing (3 papers), Physical Unclonable Functions (PUFs) and Hardware Security (2 papers) and Formal Methods in Verification (2 papers). The work is most often cited by research in Software (87 citations), Hardware and Architecture (25 citations), Signal Processing (38 citations), Information Systems (62 citations) and Artificial Intelligence (77 citations). Jared Roesch has collaborated with scholars based in United States, China and Austria. Frequent co-authors include Ben Hardekopf, Kyle Dewey, Dan Suciu, Shumo Chu, Alvin Cheung, Leonardo de Moura, Sebastian Ullrich, Jeremy Avigad, Behnam Robatmili and Mehrdad Reshadi. Their work appears in journals such as IEEE Micro, ACM SIGPLAN Notices, Proceedings of the ACM on Programming Languages, Proceedings of the VLDB Endowment and ACM SIGARCH Computer Architecture News.
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.