Sampson Wong: h-index, Total Citations, and Citation Map
Sampson Wong's h-index is 9 (9 i10-index, 176+ total citations across 34+ publications) according to Google Scholar as of May 2026. Sampson Wong is affiliated with University of Copenhagen.
Sampson Wong is a researcher affiliated with University of Copenhagen, specializing in Computational Geometry. Their work has been cited 176 times. This profile visualizes their global influence, highlighting strong citation networks in Australia.
Sampson Wong's Citation Metrics
Bibliometric impact based on 34 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 176
- Citing Countries
- 9
As of May 2026.
Sampson Wong has an h-index of 9 and 176 total citations across 34 publications, with research cited by institutions in 9 countries.
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Global Impact Map
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Top Cited Works
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(k, l)-Medians clustering of trajectories using continuous dynamic time warping
202025
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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.
111 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed efficient data structures and algorithms for translation-invariant Fréchet distance queries, extending these methods to realistic input graphs and approximate curve matching.
The researcher developed cubic bounds for subtrajectory clustering under continuous Fréchet distance, establishing a foundational framework for efficient trajectory analysis.
The researcher developed a (k, l)-medians clustering framework for trajectories using continuous dynamic time warping, establishing a foundational method for analyzing complex movement data.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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