Allen Chang
Impact in
- Cognitive Neuroscience top 10%
- Memory and Neural Mechanisms
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
Papers in
-
- Memory and Neural Mechanisms 3
- Face Recognition and Perception 2
- Neural dynamics and brain function 2
- Functional Brain Connectivity Studies 2
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- AI-based Problem Solving and Planning 2
- Logic, Reasoning, and Knowledge 2
- Co-authors
- Elizabeth Murray (2 shared papers)Michael A. Yassa (2 shared papers)Gizem Keceli (1 shared paper)John P. Toscano (1 shared paper)Maria Ly (1 shared paper)Martin Bellander (2 shared papers)Philippe N. Tobler (2 shared papers)Björn Lindström (2 shared papers)
- Journals
- Nature Communications (2 papers)Behavioral Neuroscience (2 papers)Nature Neuroscience (1 paper)Hippocampus (1 paper)Cerebral Cortex (1 paper)
- Partner nations
- United StatesNetherlandsSwitzerland
In The Last Decade
Allen Chang
10 papers receiving 298 citations
Peers
Comparison fields: 5 of 83
- Cognitive Neuroscience 95
- Biological Psychiatry 10
- Physiology 20
- Pharmacology 52
- Communication 18
Countries citing papers authored by Allen Chang
This map shows the geographic impact of Allen Chang'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 Allen Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Allen Chang more than expected).
Fields of papers citing papers by Allen Chang
This network shows the impact of papers produced by Allen Chang. 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 Allen Chang. The network helps show where Allen Chang may publish in the future.
Co-authors
The 19 scholars most cited alongside Allen Chang, 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 | 2014 | 161 | |
| 2 | 2021 | 90 | |
| 3 | 2018 | 14 | |
| 4 | 2015 | 13 | |
| 5 | Learning partially observable action models: efficient algorithms | 2006 | 10 |
| 6 | 2020 | 8 | |
| 7 | 2021 | 4 | |
| 8 | Goal achievement in partially known, partially observable domains | 2006 | 3 |
| 9 | 2021 | 2 | |
| 10 | Reachability under uncertainty | 2007 | 1 |
About Allen Chang
Allen Chang is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Cellular and Molecular Neuroscience, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 10 papers that have together received 306 indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (3 papers), AI-based Problem Solving and Planning (2 papers), Face Recognition and Perception (2 papers), Neural dynamics and brain function (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Logic, Reasoning, and Knowledge (2 papers), Functional Brain Connectivity Studies (2 papers) and Experimental Behavioral Economics Studies (1 paper). The work is most often cited by research in Cognitive Neuroscience (95 citations), Biological Psychiatry (10 citations), Physiology (20 citations), Pharmacology (52 citations) and Communication (18 citations). Allen Chang has collaborated with scholars based in United States, Netherlands and Switzerland. Frequent co-authors include Elizabeth Murray, Michael A. Yassa, Gizem Keceli, John P. Toscano, Maria Ly, Martin Bellander, Philippe N. Tobler, Björn Lindström, David M. Amodio and David Schultner. Their work appears in journals such as Nature Communications, Behavioral Neuroscience, Nature Neuroscience, Hippocampus and Cerebral Cortex.
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.