Tim Mullen
- Cognitive Neuroscience top 0.5%
- EEG and Brain-Computer Interfaces 32
- Neural dynamics and brain function 23
- Functional Brain Connectivity Studies 10
- Neural and Behavioral Psychology Studies 4
- Signal Processing top 2%
- Blind Source Separation Techniques 10
- Human-Computer Interaction top 2%
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- Neuroscience and Neural Engineering 4
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- Advanced Memory and Neural Computing 3
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- IoT and Edge/Fog Computing 2
- Co-authors
- Christian KotheNima Bigdely-ShamloScott MakeigKay A. RobbinsTzyy‐Ping JungGert CauwenberghsAlejandro OjedaYu Mike
- Journals
- NeuroImage (4 papers)Frontiers in Neuroscience (2 papers)Computational Intelligence and Neuroscience (2 papers)
- Partner nations
- United StatesFranceTaiwan
In The Last Decade
Tim Mullen
38 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Cognitive Neuroscience 2.5k
- Signal Processing 327
- Human-Computer Interaction 161
- Experimental and Cognitive Psychology 315
- Cellular and Molecular Neuroscience 424
Countries citing papers authored by Tim Mullen
This map shows the geographic impact of Tim Mullen'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 Tim Mullen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Mullen more than expected).
Fields of papers citing papers by Tim Mullen
This network shows the impact of papers produced by Tim Mullen. 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 Tim Mullen. The network helps show where Tim Mullen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tim Mullen, 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 | 4 | |
| 2 | 2024 | 5 | |
| 3 | 2024 | 3 | |
| 4 | 2022 | 14 | |
| 5 | 2021 | 32 | |
| 6 | 2019 | 22 | |
| 7 | 2019 | 19 | |
| 8 | 2018 | 38 | |
| 9 | 2017 | 20 | |
| 10 | 2016 | 45 | |
| 11 | 2016 | 1 | |
| 12 | The PREP pipeline: standardized preprocessing for large-scale EEG analysisbreakdown → | 2015 | 782 |
| 13 | Real-time neuroimaging and cognitive monitoring using wearable dry EEGbreakdown → | 2015 | 518 |
| 14 | 2014 | 93 | |
| 15 | 2014 | 42 | |
| 16 | 2014 | 22 | |
| 17 | 2014 | 23 | |
| 18 | 2013 | 1 | |
| 19 | 2012 | 10 | |
| 20 | 2011 | 25 |
About Tim Mullen
Tim Mullen is a scholar working on Cognitive Neuroscience, Signal Processing and Human-Computer Interaction, having authored 39 papers that have together received 3.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (32 papers), Neural dynamics and brain function (23 papers), Functional Brain Connectivity Studies (10 papers), Blind Source Separation Techniques (10 papers), Neuroscience and Neural Engineering (4 papers), Neural and Behavioral Psychology Studies (4 papers), Advanced Memory and Neural Computing (3 papers) and IoT and Edge/Fog Computing (2 papers). The work is most often cited by research in Cognitive Neuroscience (2.5k citations), Signal Processing (327 citations) and Human-Computer Interaction (161 citations). Tim Mullen has collaborated with scholars based in United States, France and Taiwan. Frequent co-authors include Christian Kothe, Nima Bigdely-Shamlo, Scott Makeig, Kay A. Robbins, Tzyy‐Ping Jung, Gert Cauwenberghs, Alejandro Ojeda, Yu Mike, Zeynep Akalin Acar and Arnaud Delorme. Their work appears in journals such as NeuroImage, Frontiers in Neuroscience, Computational Intelligence and Neuroscience, IEEE Transactions on Neural Systems and Rehabilitation Engineering and Scientific Reports.
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.