Examiner Kandasamy Thangavelu has allowed 863 of 1,029 decided applications (84%) in Computer Architecture, Software, and Information Security.
Examiner Kandasamy Thangavelu maintains a public record across 3 art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Over 1,029 disposed applications, the examiner allowed 863, yielding an 84% allowance rate. The allowance rate ranges from 80% to 96% across the examiner's art units. This pooled figure reflects decisions across multiple areas of TC 2100 and does not represent performance in any single art unit or predict outcomes in individual applications.
A pooled record aggregates data from multiple art units, smoothing variation within each area. The overall allowance rate (84% across 1,029 decided applications) describes the examiner's past record in aggregate and is not a prediction of any specific application's outcome. The stated range (80% to 96%) shows variation among the individual art units but does not identify which art unit achieved which rate. Pooled figures are historical summaries only.
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 34 decided applications with an interview and 622 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 96 decided applications with an interview and 118 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 40 decided applications with an interview and 119 without.
Methodology. This page pools every art unit in which Examiner Kandasamy Thangavelu 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: 1,029 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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