Ming Lin: h-index, Total Citations, and Citation Map
Ming Lin's h-index is 106 (335 i10-index, 46,034+ total citations across 696+ publications) according to Google Scholar as of July 2026. Ming Lin is affiliated with Distinguished University Professor of University of Maryland at College Park & Amazon.
Ming Lin is a researcher affiliated with Distinguished University Professor of University of Maryland at College Park & Amazon, specializing in various fields. Their work has been cited 46,034 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Ming Lin's Citation Metrics
Bibliometric impact based on 696 indexed publications. Of these, 18 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 106
- i10-Index
- 335
- Total Citations
- 46,034
- Citing Countries
- 38
As of July 2026.
Ming Lin has an h-index of 106 and 46,034 total citations across 696 publications, with research cited by institutions in 38 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Ming Lin's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
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.
OBBTree: A hierarchical structure for rapid interference detection
19963,723
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.
9 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered accelerated collision detection algorithms for virtual environments, establishing foundational methods that significantly influenced subsequent computational geometry and simulation research.
The researcher developed OBBTree, a hierarchical structure for rapid interference detection, establishing a foundational algorithm for efficient collision checking in computational geometry.
The researcher established foundational methods for efficient collision and proximity queries, a seminal contribution that has become a standard reference in computational geometry and spatial data processing.
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 Ming Lin's research
Ming Lin is a researcher at Distinguished University Professor of University of Maryland at College Park & Amazon. Their work has been cited 46,034 times across 696 publications (h-index 106), according to Google Scholar.
Their most-cited work, “OBBTree: A hierarchical structure for rapid interference detection” (1996), has accumulated 3,723 citations. Other influential works include “Reciprocal n-Body Collision Avoidance” (2011) with 2,777 citations and “Reciprocal velocity obstacles for real-time multi-agent navigation” (2008) with 2,508 citations.
Citations of Ming Lin's research come primarily from United States, China and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
