Cliff Vuong

855 citations
7 papers · 434 · h-index 6

Impact in

    • Memory and Neural Mechanisms
    • Neural dynamics and brain function
    • Sleep and Wakefulness Research
    • Neuroscience and Neuropharmacology Research
    • Photoreceptor and optogenetics research
    • Neuroscience and Neural Engineering

Papers in

Cliff Vuong

7 papers receiving 428 citations

Peers

Cliff Vuong
Comparison fields: 5 of 61
  • Cognitive Neuroscience 344
  • Cellular and Molecular Neuroscience 254
  • Sensory Systems 62
  • Developmental Neuroscience 17
  • Behavioral Neuroscience 11
Replace Lavanya Acharya with:
Lavanya Acharya United States
Jason J. Moore United States
Ashley L. Kees United States
Adam Ranson United Kingdom
Marius Bauža United Kingdom
Chris C. Rodgers United States
Mark C. Fuhs United States
Nathaniel J. Killian United States
Alexandra T. Keinath United States
Yongdi Zhou China
Cliff Vuong relative to Lavanya Acharya United States Lavanya Acharya's profile →
Citations per field
00.5×1.5×1.8×
Lavanya Acharya · 1×
Citations per year

Countries citing papers authored by Cliff Vuong

Since Specialization
Citations

This map shows the geographic impact of Cliff Vuong'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 Cliff Vuong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cliff Vuong more than expected).

Fields of papers citing papers by Cliff Vuong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cliff Vuong. 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 Cliff Vuong. The network helps show where Cliff Vuong may publish in the future.

Co-authors

The 17 scholars most cited alongside Cliff Vuong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Cliff Vuong Line = papers co-authored together Cliff Vuong links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown

About Cliff Vuong

Cliff Vuong is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems, Dermatology and Molecular Biology, having authored 7 papers that have together received 434 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (4 papers), Memory and Neural Mechanisms (3 papers), Olfactory and Sensory Function Studies (3 papers), Dermatology and Skin Diseases (2 papers), Neuroscience and Neural Engineering (1 paper), Multisensory perception and integration (1 paper), Sphingolipid Metabolism and Signaling (1 paper) and Biochemical Analysis and Sensing Techniques (1 paper). The work is most often cited by research in Cognitive Neuroscience (344 citations), Cellular and Molecular Neuroscience (254 citations), Sensory Systems (62 citations), Developmental Neuroscience (17 citations) and Behavioral Neuroscience (11 citations). Cliff Vuong has collaborated with scholars based in United States. Frequent co-authors include Mayank Mehta, Jason J. Moore, Lavanya Acharya, Zahra M. Aghajan, Jesse D. Cushman, Ashley L. Kees, Pascal Ravassard, David Ho, Diana M. Bautista and K. Arisaka. Their work appears in journals such as Nature, Neuron, Cell, Science and PLoS ONE.

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.

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