Examiner Benjamin J Buss has allowed 340 of 468 decided applications (73%) in Computer Architecture, Software, and Information Security.
Benjamin J Buss has a public record of 468 disposed applications across 4 art units in Technology Center 2100 (Computer Architecture, Software, and Information Security). Of these decided applications, 340 were allowed and 128 were abandoned, yielding an overall allowance rate of 73%. The allowance rate varies across the examiner's art units, ranging from 68% to 91%. This pooled figure aggregates outcomes from art units 2121, 2125, 2127, and 2129 and reflects the examiner's historical record in this technology center.
A pooled record aggregates data from multiple art units, masking variation in outcomes within each unit. The overall allowance rate of 73% describes what occurred historically across all the examiner's assigned art units combined. This aggregate percentage is a description of past decisions, not a prediction of the outcome of any specific application. For detail on allowance rates within individual art units, refer to the per-art-unit 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 156 decided applications with an interview and 168 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 68 decided applications with an interview and 23 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 44 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 9 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Benjamin J Buss 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: 468 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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