Philipp Moritz
- Artificial Intelligence top 1%
- Reinforcement Learning in Robotics 2
- Automotive Engineering top 5%
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- Cloud Computing and Resource Management 5
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- Surgical Sutures and Adhesives 4
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- Parallel Computing and Optimization Techniques 4
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- Distributed and Parallel Computing Systems 3
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- Advanced Cellulose Research Studies 2
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- Polymer Surface Interaction Studies 2
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- Enzyme-mediated dye degradation 1
- Co-authors
- Michael I. JordanJohn SchulmanPieter AbbeelSergey LevineRobert NishiharaIon StoicaRichard LiawEric Liang
- Partner nations
- GermanyUnited StatesSweden
In The Last Decade
Philipp Moritz
17 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 1.1k
- Control and Systems Engineering 468
- Automotive Engineering 217
- Computer Vision and Pattern Recognition 314
- Management Science and Operations Research 160
Countries citing papers authored by Philipp Moritz
This map shows the geographic impact of Philipp Moritz'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 Philipp Moritz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Moritz more than expected).
Fields of papers citing papers by Philipp Moritz
This network shows the impact of papers produced by Philipp Moritz. 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 Philipp Moritz. The network helps show where Philipp Moritz may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Philipp Moritz, 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 | 2023 | 2 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 5 | |
| 5 | 2022 | 2 | |
| 6 | 2021 | 9 | |
| 7 | 2021 | 20 | |
| 8 | 2021 | 14 | |
| 9 | 2020 | 17 | |
| 10 | 2020 | 9 | |
| 11 | 2020 | 1 | |
| 12 | Ray: A Distributed Execution Engine for the Machine Learning Ecosystem | 2019 | 0 |
| 13 | 2019 | 25 | |
| 14 | RLlib: Abstractions for Distributed Reinforcement Learning | 2018 | 50 |
| 15 | Ray RLLib: A Composable and Scalable Reinforcement Learning Library | 2017 | 49 |
| 16 | 2017 | 35 | |
| 17 | A Linearly-Convergent Stochastic L-BFGS Algorithm | 2016 | 39 |
| 18 | Trust Region Policy Optimizationbreakdown → | 2015 | 1573 |
| 19 | 2014 | 2 |
About Philipp Moritz
Philipp Moritz is a scholar working on Hardware and Architecture, Surfaces, Coatings and Films and Information Systems, having authored 19 papers that have together received 1.9k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (5 papers), Surgical Sutures and Adhesives (4 papers), Parallel Computing and Optimization Techniques (4 papers), Distributed and Parallel Computing Systems (3 papers), Reinforcement Learning in Robotics (2 papers), Advanced Cellulose Research Studies (2 papers), Polymer Surface Interaction Studies (2 papers) and Enzyme-mediated dye degradation (1 paper). The work is most often cited by research in Artificial Intelligence (1.1k citations), Control and Systems Engineering (468 citations) and Automotive Engineering (217 citations). Philipp Moritz has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include Michael I. Jordan, John Schulman, Pieter Abbeel, Sergey Levine, Robert Nishihara, Ion Stoica, Richard Liaw, Eric Liang, Roy Fox and Joseph E. Gonzalez. Their work appears in journals such as Kybernetika, The Journal of Adhesion, ChemPhysChem, The Journal of Physical Chemistry C and International Journal of Adhesion and Adhesives.
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.