Examiner Mohammad A Rahman has allowed 139 of 186 decided applications (75%) in Computer Architecture, Software, and Information Security.
Mohammad A Rahman has a public record spanning 4 art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Across 186 disposed applications, 139 were allowed, yielding an allowance rate of 75%. The allowance rate across the examiner's art units ranges from 71% to 79%. This pooled figure aggregates the examiner's record across all four art units and describes outcomes on applications already decided; it is not a prediction of the outcome on any pending or future application.
A pooled record combines data from multiple art units into a single aggregate allowance rate. This rate reflects past outcomes across different subject areas and examiner assignments. The range (lowest to highest allowance rate among the art units) indicates variation in the examiner's record by art unit. Pooled figures describe historical dispositions and are not predictions of outcomes on any specific application or art unit.
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 control or regulating systems, and electric power networks.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 35 decided applications with an interview and 62 without.
Primarily examines control or regulating systems.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 43 decided applications with an interview and 24 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 19 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 3 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Mohammad A Rahman 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: 186 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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