Examiner Lut Wong has allowed 556 of 724 decided applications (77%) in Computer Architecture, Software, and Information Security.
Examiner Lut Wong maintains a public record across three art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Over 724 disposed applications, the examiner issued allowances on 556 applications, yielding an allowance rate of 77%. The record spans art units 2121, 2127, and 2129. Across these art units, allowance rates range from 67% to 88%, reflecting variation in outcomes within the examiner's portfolio. A total of 168 applications were abandoned. These figures represent the examiner's pooled historical record and do not constitute predictions about any specific application.
This profile aggregates the examiner's record across multiple art units in TC 2100. The overall allowance rate of 77% describes historical outcomes on decided applications and reflects past performance in aggregate form. Because the record spans different art units, the pooled rate masks individual art-unit variation (reflected in the 67%–88% range). This aggregate figure is historical data only and is not a prediction of any specific application's outcome. Per-art-unit detail appears in a separate section.
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 neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 148 decided applications with an interview and 221 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 101 decided applications with an interview and 132 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 59 decided applications with an interview and 63 without.
Methodology. This page pools every art unit in which Examiner Lut Wong 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: 752 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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