Michael Carbin
Impact in
- Hardware and Architecture top 0.5%
- Parallel Computing and Optimization Techniques
- Software top 1%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
Papers in
-
- Parallel Computing and Optimization Techniques 26
- Software 5
- Co-authors
- Martin RinardSaša MisailovícJonathan FrankleStelios SidiroglouHenry HoffmannAnant AgarwalSara AchourSaman Amarasinghe
- Journals
- Proceedings of the ACM on Programming Languages (11 papers)ACM SIGPLAN Notices (7 papers)Communications of the ACM (1 paper)ACM Computing Surveys (1 paper)ACM SIGOPS Operating Systems Review (1 paper)
- Partner nations
- United StatesUnited KingdomSingapore
In The Last Decade
Michael Carbin
58 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 79
- Hardware and Architecture 825
- Software 394
- Computational Mathematics 18
- Computer Networks and Communications 611
- Artificial Intelligence 796
Countries citing papers authored by Michael Carbin
This map shows the geographic impact of Michael Carbin'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 Michael Carbin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Carbin more than expected).
Fields of papers citing papers by Michael Carbin
This network shows the impact of papers produced by Michael Carbin. 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 Michael Carbin. The network helps show where Michael Carbin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Carbin, 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 | 2024 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 0 | |
| 5 | 2021 | 25 | |
| 6 | 2020 | 32 | |
| 7 | Compiler Auto-Vectorization with Imitation Learning | 2019 | 13 |
| 8 | The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. | 2019 | 237 |
| 9 | Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks | 2019 | 13 |
| 10 | 2019 | 1 | |
| 11 | 2019 | 14 | |
| 12 | The Lottery Ticket Hypothesis: Training Pruned Neural Networks. | 2018 | 46 |
| 13 | 2017 | 2 | |
| 14 | 2017 | 11 | |
| 15 | 2014 | 43 | |
| 16 | 2012 | 18 | |
| 17 | 2011 | 43 | |
| 18 | 2011 | 236 | |
| 19 | 2010 | 54 | |
| 20 | Self-defending software: Automatically patching security vulnerabilities | 2009 | 1 |
About Michael Carbin
Michael Carbin is a scholar working on Hardware and Architecture, Software, Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications, having authored 61 papers that have together received 2.0k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (26 papers), Distributed systems and fault tolerance (9 papers), Advanced Neural Network Applications (9 papers), Logic, programming, and type systems (8 papers), Cloud Computing and Resource Management (7 papers), Radiation Effects in Electronics (7 papers), Formal Methods in Verification (7 papers) and Machine Learning and Algorithms (6 papers). The work is most often cited by research in Hardware and Architecture (825 citations), Software (394 citations), Computational Mathematics (18 citations), Computer Networks and Communications (611 citations) and Artificial Intelligence (796 citations). Michael Carbin has collaborated with scholars based in United States, United Kingdom and Singapore. Frequent co-authors include Martin Rinard, Saša Misailovíc, Jonathan Frankle, Stelios Sidiroglou, Henry Hoffmann, Anant Agarwal, Sara Achour, Saman Amarasinghe, Deokhwan Kim and Frank P. Sherwood. Their work appears in journals such as Proceedings of the ACM on Programming Languages, ACM SIGPLAN Notices, Communications of the ACM, ACM Computing Surveys and ACM SIGOPS Operating Systems Review.
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.