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◈ USPTO PATENT EXAMINER STATISTICS

Examiner Suzanne Lo

TECH CENTER 2100 · 3 ART UNITS · 366 DECIDED APPLICATIONS · LAST ACTION NOV 2020
ALLOWANCE RATE = SHARE OF DECIDED APPLICATIONS (ALLOWED + ABANDONED); PENDING EXCLUDED
OVERALL ALLOWANCE RATE · POOLED ACROSS 3 ART UNITS

Examiner Suzanne Lo has allowed 230 of 366 decided applications (63%) in Computer Architecture, Software, and Information Security.

63% pooled allowance · benchmarked per art unit below
DATA UPDATED JUNE 25, 2026
AU 2128 · 56%AU 2127 · 82%AU 2123 · 0%
// READING THIS EXAMINER

What the data says.

Examiner Suzanne Lo maintains a public record across 3 art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Over 366 disposed applications, her overall allowance rate is 63%, based on 230 allowed and 136 abandoned applications. Allowance rates across her art units range from 56% to 82%. This pooled figure reflects her record across multiple areas of TC 2100 and does not represent a prediction for any individual application.

// HOW TO READ THESE NUMBERS

How to read these numbers.

A pooled record aggregates the examiner's history across all art units in which they have examined applications. The overall allowance rate describes what occurred in the past across decided applications and is a statistical summary, not a forecast. Individual art units may show different rates. A pooled figure provides broad context for an examiner's overall record but does not predict the outcome of any specific application.

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 →

// BY ART UNIT

The record, art unit by art unit.

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.

◈ PRIMARY · ART UNIT 2128
260 APPS · 56% ALLOWANCE

Primarily examines machine learning, and neural-network / biological-model computing.

56% allowance (of decided)▏ art-unit average 53%
DISPOSITION146 / 114 / 0allowed / abandoned / pending
FIRST ACTION29.9 moart unit avg 30 mo
TOTAL PENDENCY56 moart unit avg 46.5 mo
// REJECTION PROFILE
§101 — Subject-matter eligibility70% · art unit 65%
§102 — Anticipation (novelty)61%
§103 — Obviousness83% · art unit 84%
§112 — Written description & definiteness70%
// INTERVIEW SPLIT

Allowance rate for applications with an examiner interview versus without one.

WITH INTERVIEW77%allowance share
WITHOUT INTERVIEW48%+29 pt difference

A correlation, not proof that interviews cause allowances. Based on 71 decided applications with an interview and 189 without.

ART UNIT 2127
102 APPS · 82% ALLOWANCE

Primarily examines neural-network / biological-model computing, and machine learning.

82% allowance (of decided)▏ art-unit average 67%
DISPOSITION84 / 18 / 0allowed / abandoned / pending
FIRST ACTION25.4 moart unit avg 28.5 mo
TOTAL PENDENCY39.3 moart unit avg 41.8 mo
// REJECTION PROFILE
§101 — Subject-matter eligibility59% · art unit 51%
§102 — Anticipation (novelty)82%
§103 — Obviousness64% · art unit 77%
§112 — Written description & definiteness87%
// INTERVIEW SPLIT

Allowance rate for applications with an examiner interview versus without one.

WITH INTERVIEW92%allowance share
WITHOUT INTERVIEW71%+21 pt difference

A correlation, not proof that interviews cause allowances. Based on 53 decided applications with an interview and 49 without.

ART UNIT 2123
4 APPS · 0% ALLOWANCE · LIMITED DATA

Primarily examines neural-network / biological-model computing, and machine learning.

0% allowance (of decided)▏ art-unit average 51%
DISPOSITION0 / 4 / 0allowed / abandoned / pending
FIRST ACTION32 moart unit avg 29.3 mo
TOTAL PENDENCY54 moart unit avg 43.8 mo
// REJECTION PROFILE
§101 — Subject-matter eligibility75% · art unit 61%
§102 — Anticipation (novelty)75%
§103 — Obviousness25% · art unit 85%
§112 — Written description & definiteness75%

Based on 4 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.

// FAQ

Questions about Examiner Suzanne Lo

  • What is Examiner Suzanne Lo's overall allowance rate?
    Her overall allowance rate is 63%, based on 366 disposed applications (230 allowed, 136 abandoned).
  • How many art units does this record cover?
    The record spans 3 art units: 2123, 2127, and 2128, all within TC 2100.
  • What is the range of allowance rates across her art units?
    Allowance rates range from 56% to 82% across the art units in which she maintains a substantial record.
  • Does this pooled rate predict the outcome of my application?
    No. The pooled allowance rate is a historical summary of decided applications and is not a prediction of any specific application's outcome.
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METHODOLOGY & DISCLOSURES

Methodology. This page pools every art unit in which Examiner Suzanne Lo 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: 366 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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