Examiner Iftekhar A Khan has allowed 484 of 620 decided applications in Computer Architecture, Software, and Information Security.
Examiner Iftekhar A Khan maintains a pooled allowance rate of 78% across hundreds of decided applications in Technology Center 2100 (Computer Architecture, Software, and Information Security). This record spans five art units: 2123, 2127, 2128, 2146, and 2187. The allowance rate varies across these art units, ranging from 65% to 86%. This range reflects differences in application outcomes among the distinct art units within the technology center, though the examiner's overall pooled rate of 78% represents the aggregate of all decided applications across all five units.
This page presents a pooled record aggregating all of the examiner's decided applications across five art units. The 78% allowance rate is a historical figure describing past outcomes and is not a prediction of any specific application's prosecution or allowance. Pooled figures mask variation among individual art units; separate detailed records for each art unit are available elsewhere. Pooled data is useful for understanding an examiner's broad record but does not predict outcomes in any particular 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 machine learning, and neural-network / biological-model computing.
Grounds can co-occur, so the four don't sum to 100%. The art-unit figure is the unweighted mean across examiners in the art unit; §102 and §112 carry no art-unit benchmark.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 61 decided applications with an interview and 113 without.
Primarily examines artificial-intelligence and machine-learning methods.
Grounds can co-occur, so the four don't sum to 100%. The art-unit figure is the unweighted mean across examiners in the art unit; §102 and §112 carry no art-unit benchmark.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 75 decided applications with an interview and 97 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Grounds can co-occur, so the four don't sum to 100%. The art-unit figure is the unweighted mean across examiners in the art unit; §102 and §112 carry no art-unit benchmark.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 84 decided applications with an interview and 71 without.
Primarily examines computer-aided design (CAD).
Grounds can co-occur, so the four don't sum to 100%. The art-unit figure is the unweighted mean across examiners in the art unit; §102 and §112 carry no art-unit benchmark.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 54 decided applications with an interview and 56 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Grounds can co-occur, so the four don't sum to 100%. The art-unit figure is the unweighted mean across examiners in the art unit; §102 and §112 carry no art-unit benchmark.
Based on 9 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
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Methodology. This page pools every art unit in which Examiner Iftekhar A Khan 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 July 14, 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: 654 applications.
Rejection rates. Each §-rate is the share of this examiner's applications that drew at least one office-action rejection in which that statutory ground appears; applications with no rejection on record are excluded, and because grounds can co-occur the four do not sum to 100%. The art-unit figure beside each is the unweighted mean of the per-examiner rates across the art unit, published for §101 and §103 only. Beside the overall allowance rate we show a benchmark: for a single-art-unit examiner it is exactly that art unit's average, labeled “art-unit average”; for an examiner spanning several art units it is the “weighted peer average” — the per-art-unit averages, weighted by this examiner's application count in each — labeled distinctly because it is a blended figure, not any single art unit's average. Both are built from the same per-art-unit averages the panels show.
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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