Stephen McAleer
- Mechanical Engineering top 5%
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- Scheduling and Optimization Algorithms 1
- Mechanics of Materials top 5%
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics 3
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- Neutrino Physics Research 2
- Astrophysics and Cosmic Phenomena 2
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- Economic theories and models 1
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- Radio Astronomy Observations and Technology 1
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- Cell Image Analysis Techniques 1
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- Photoacoustic and Ultrasonic Imaging 1
- Co-authors
- Ruqiang YanPierre BaldiSiyu ShaoForest AgostinelliAlexander ShmakovChristian GläserYaodong YangS. W. Barwick
- Cited by
- Control and Systems EngineeringMechanical EngineeringIndustrial and Manufacturing Engineering
- Journals
- Translational Vision Science & Technology (1 paper)Astroparticle Physics (1 paper)Nature Machine Intelligence (1 paper)
- Partner nations
- United StatesChinaSweden
In The Last Decade
Stephen McAleer
10 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Control and Systems Engineering 949
- Mechanical Engineering 531
- Industrial and Manufacturing Engineering 125
- Mechanics of Materials 292
- Artificial Intelligence 298
Countries citing papers authored by Stephen McAleer
This map shows the geographic impact of Stephen McAleer'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 Stephen McAleer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen McAleer more than expected).
Fields of papers citing papers by Stephen McAleer
This network shows the impact of papers produced by Stephen McAleer. 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 Stephen McAleer. The network helps show where Stephen McAleer may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Stephen McAleer, 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 | 1 | |
| 2 | 2024 | 8 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 9 | |
| 5 | Neural Auto-Curricula in Two-Player Zero-Sum Games | 2021 | 2 |
| 6 | 2021 | 2 | |
| 7 | 2021 | 11 | |
| 8 | 2019 | 77 | |
| 9 | Solving the Rubik's Cube with Approximate Policy Iteration | 2018 | 7 |
| 10 | Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learningbreakdown → | 2018 | 1180 |
About Stephen McAleer
Stephen McAleer is a scholar working on Biophysics, Artificial Intelligence, Nuclear and High Energy Physics, Industrial and Manufacturing Engineering and Management Science and Operations Research, having authored 10 papers that have together received 1.3k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Neutrino Physics Research (2 papers), Astrophysics and Cosmic Phenomena (2 papers), Economic theories and models (1 paper), Radio Astronomy Observations and Technology (1 paper), Cell Image Analysis Techniques (1 paper), Photoacoustic and Ultrasonic Imaging (1 paper) and Scheduling and Optimization Algorithms (1 paper). The work is most often cited by research in Control and Systems Engineering (949 citations), Mechanical Engineering (531 citations), Industrial and Manufacturing Engineering (125 citations), Mechanics of Materials (292 citations) and Artificial Intelligence (298 citations). Stephen McAleer has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Ruqiang Yan, Pierre Baldi, Siyu Shao, Pierre Baldi, Forest Agostinelli, Alexander Shmakov, Christian Gläser, Yaodong Yang, S. W. Barwick and Andrew Browne. Their work appears in journals such as Translational Vision Science & Technology, Astroparticle Physics, Nature Machine Intelligence, IEEE Transactions on Industrial Informatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.