Examiner Tri T Nguyen has allowed 132 of 194 decided applications (68%) in Computer Architecture, Software, and Information Security.
Examiner Tri T Nguyen holds a public record of 228 total applications across four art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Of 194 disposed applications, 132 were allowed, for an overall allowance rate of 68%. The examiner's record spans art units 2115, 2123, 2126, and 2128. Allowance rates across these art units range from 43% to 89%, reflecting variation in outcomes within the technology center.
This record aggregates decisions across four separate art units. The 68% allowance rate represents the pooled outcome of 194 decided applications and describes the examiner's historical pattern, not a forecast of any specific case. Cross-art-unit records provide a broad snapshot; individual art units and application facts may differ materially from the aggregate. Pooled figures mask variation—as shown by the 43% to 89% range—so context matters.
These are aggregate statistics from this examiner's past public record — not predictions about any specific application. The per-art-unit figures below show how the record varies across art units. Our approach to patent prosecution →
Each section benchmarks this examiner against that art unit's average. Figures are this examiner's own public record within the art unit; the overall rate above pools them.
Primarily examines machine learning, and neural-network / biological-model computing.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 52 decided applications with an interview and 40 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 37 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Primarily examines control or regulating systems, and electric power networks.
Based on 35 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 30 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Tri T Nguyen has a public record within Technology Center 2100. Statistics are computed from publicly available USPTO records, refreshed on a recurring schedule. This page's data was last updated June 25, 2026. The overall allowance rate is total allowed divided by total decided applications (allowed plus abandoned) across all art units — not an average of the per-art-unit rates; pending applications are excluded. Figures are rounded for display. Pooled sample: 228 applications.
Lynch LLP is not affiliated with, endorsed by, or sponsored by the United States Patent and Trademark Office. Examiner statistics are derived from publicly available USPTO data.
These statistics describe past examiner behavior and do not predict the outcome of any particular application. Past results do not guarantee future outcomes. Where this page compares an examiner's allowance rate to an art-unit average, that comparison is a factual description of the public record, not a characterization of any individual examiner's conduct or competence.
This page is for general informational purposes and is not legal advice. No attorney-client relationship is formed by viewing it. Full disclaimers →
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