Examiner Miranda M Huang has allowed 170 of 278 decided applications (61%) in Computer Architecture, Software, and Information Security.
Miranda M Huang has a public record spanning 3 art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Across 278 disposed applications, she allowed 170, resulting in an overall allowance rate of 61%. The allowance rate ranges from 38% to 66% across her art units, reflecting variation in outcomes within the technology center. This pooled figure represents historical dispositions and does not constitute a prediction for any specific application.
This pooled record aggregates outcomes across multiple art units in TC 2100. The overall allowance rate of 61% describes past dispositions across all art units combined. Because the record spans different art units with different allowance rates (ranging from 38% to 66%), the aggregate figure masks variation among them. Pooled statistics describe historical record only and are not predictions of outcomes in any individual application.
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 information retrieval and database structures.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 120 decided applications with an interview and 66 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 31 decided applications with an interview and 32 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 29 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Miranda M Huang 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: 292 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.
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