Examiner Rehana Perveen has allowed 176 of 192 decided applications (92%) in Computer Architecture, Software, and Information Security.
Examiner Rehana Perveen has a public record spanning six art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Across 192 disposed applications, the allowance rate is 92%. The range of allowance rates among these art units extends from 93% to 100%, reflecting variation in outcomes across the different subject-matter areas within TC 2100. The examiner has allowed 176 applications and seen 16 abandoned. This pooled figure aggregates the examiner's work across all six art units and describes the historical record only.
A pooled examiner record combines statistics from multiple art units into a single aggregate. The overall allowance rate reflects past decisions across all units combined and is not a prediction for any particular application. Because different art units address different technical subject matter, the range between the lowest and highest unit allowance rates illustrates variation in outcomes by field. Pooled figures are historical summaries; they do not forecast the disposition of any specific case.
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.
Primarily examines data-processing methods for specific functions, and processing data by its order or content.
Primarily examines computer-aided design (CAD).
Based on 31 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Primarily examines information retrieval and database structures.
Based on 5 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 2 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 2 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Rehana Perveen 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: 197 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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