Josh Merel
- Biophysics top 1%
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 8
- EEG and Brain-Computer Interfaces 4
- Developmental Biology top 5%
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- Neuroscience and Neural Engineering 4
- Sensory Systems top 10%
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- Reinforcement Learning in Robotics 8
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- Robot Manipulation and Learning 5
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- Advanced Memory and Neural Computing 3
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- Human Pose and Action Recognition 3
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- Robotic Locomotion and Control 3
- Co-authors
- Liam PaninskiEftychios A. PnevmatikakisGreg WayneMatthew BotvinickRandy M. BrunoNicolas HeessWeijian YangMisha B. Ahrens
- Partner nations
- United StatesUnited KingdomRussia
In The Last Decade
Josh Merel
28 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Biophysics 201
- Cognitive Neuroscience 647
- Developmental Biology 60
- Cellular and Molecular Neuroscience 487
- Sensory Systems 54
Countries citing papers authored by Josh Merel
This map shows the geographic impact of Josh Merel'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 Josh Merel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josh Merel more than expected).
Fields of papers citing papers by Josh Merel
This network shows the impact of papers produced by Josh Merel. 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 Josh Merel. The network helps show where Josh Merel may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Josh Merel, 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 | 2025 | 2 | |
| 2 | 2025 | 5 | |
| 3 | 2024 | 20 | |
| 4 | 2021 | 35 | |
| 5 | RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. | 2020 | 2 |
| 6 | 2020 | 89 | |
| 7 | CoMic: Complementary Task Learning & Mimicry for Reusable Skills | 2020 | 5 |
| 8 | Critic Regularized Regression | 2020 | 1 |
| 9 | 2020 | 2 | |
| 10 | 2019 | 140 | |
| 11 | Hierarchical Visuomotor Control of Humanoids. | 2018 | 9 |
| 12 | 2018 | 126 | |
| 13 | Multilayer Recurrent Network Models of Primate Retinal Ganglion Cell Responses | 2017 | 26 |
| 14 | Robust imitation of diverse behaviors | 2017 | 25 |
| 15 | 2016 | 78 | |
| 16 | Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Databreakdown → | 2016 | 608 |
| 17 | 2016 | 11 | |
| 18 | 2014 | 54 | |
| 19 | A multi-agent control framework for co-adaptation in brain-computer interfaces | 2013 | 14 |
| 20 | 2012 | 2 |
About Josh Merel
Josh Merel is a scholar working on Cognitive Neuroscience, Developmental Biology, Control and Systems Engineering, Artificial Intelligence and Cellular and Molecular Neuroscience, having authored 28 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Reinforcement Learning in Robotics (8 papers), Robot Manipulation and Learning (5 papers), Neuroscience and Neural Engineering (4 papers), EEG and Brain-Computer Interfaces (4 papers), Advanced Memory and Neural Computing (3 papers), Human Pose and Action Recognition (3 papers) and Robotic Locomotion and Control (3 papers). The work is most often cited by research in Biophysics (201 citations), Cognitive Neuroscience (647 citations), Developmental Biology (60 citations), Cellular and Molecular Neuroscience (487 citations) and Sensory Systems (54 citations). Josh Merel has collaborated with scholars based in United States, United Kingdom and Russia. Frequent co-authors include Liam Paninski, Eftychios A. Pnevmatikakis, Greg Wayne, Matthew Botvinick, Randy M. Bruno, Nicolas Heess, Weijian Yang, Misha B. Ahrens, Yuanjun Gao and David Pfau. Their work appears in journals such as Nature Communications, Nature, PLoS Computational Biology, Neuron and Physical Review Fluids.
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.