Pieter Abbeel: h-index, Total Citations, and Citation Map
Pieter Abbeel's h-index is 114 (346 i10-index, 278,724+ total citations across 701+ publications) according to Google Scholar as of September 2026. Pieter Abbeel is affiliated with UC Berkeley | Amazon FAR.
Pieter Abbeel is a researcher affiliated with UC Berkeley | Amazon FAR, specializing in AI & Machine Learning. Their work has been cited 278,724 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Pieter Abbeel's Citation Metrics
Bibliometric impact based on 701 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 114
- i10-Index
- 346
- Total Citations
- 278,724
- Citing Countries
- 89
As of September 2026.
Pieter Abbeel has an h-index of 114 and 278,724 total citations across 701 publications, with research cited by institutions in 89 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Denoising diffusion probabilistic models
202038,060
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Pieter Abbeel's research
Pieter Abbeel is a researcher in AI & Machine Learning at UC Berkeley | Amazon FAR. Their work has been cited 278,724 times across 701 publications (h-index 114), according to Google Scholar.
Their most-cited work, “Denoising diffusion probabilistic models” (2020), has accumulated 38,060 citations. Other influential works include “Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks” (2017) with 5,758 citations and “Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor” (2018) with 3,481 citations.
Citations of Pieter Abbeel's research come primarily from United States, China and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
