Damien Ernst: h-index, Total Citations, and Citation Map
Damien Ernst's h-index is 52 (189 i10-index, 25,958+ total citations across 588+ publications) according to Google Scholar as of June 2026. Damien Ernst is affiliated with Professor of Electrical Engineering and Computer Science, ULiège.
Damien Ernst is a researcher affiliated with Professor of Electrical Engineering and Computer Science, ULiège, specializing in Power Systems, Smart Grids, Reinforcement Learning. Their work has been cited 25,958 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Damien Ernst's Citation Metrics
Bibliometric impact based on 588 indexed publications.
- H-Index
- 52
- i10-Index
- 189
- Total Citations
- 25,958
- Citing Countries
- 74
As of June 2026.
Damien Ernst has an h-index of 52 and 25,958 total citations across 588 publications, with research cited by institutions in 74 countries.
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We've mapped 5,000 of 25,958 citations for Damien Ernst
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Global Impact Map
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Top Cited Works
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Extremely randomized trees
200611,842
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.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
734 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered extremely randomized trees and advanced reinforcement learning applications, establishing foundational methods widely adopted by independent researchers across diverse scientific domains.
The researcher developed a unified framework for transient stability contingency filtering, ranking, and assessment, establishing a foundational methodology for power system security analysis.
The researcher established a foundational reinforcement learning framework for power systems stability control, a seminal contribution that has been widely adopted by the independent academic community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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