Technology areas: Computing & Software • Communications
3 pending office actions • 3 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 1 patents granted in the last 365 days
Aondevices Inc. has 3 pending office actions in Computing & Software. The matters are distributed across 3 distinct examiners and 3 distinct art units, creating three separate examination contexts. HWANG, MEGAN ELIZABETH is the busiest examiner, with 1 pending matter.
The profile requires active coordination across the pending software matters while preserving response specificity for each art unit. Counsel should maintain consistent definitions and claim positions where the applications share technical concepts, but should not assume identical examiner treatment. The identified examiner handles 1 pending matter, with the remaining actions assigned to other examination settings.
Based on the USPTO statutory response window for each pending office action. 2 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 + other | 1 (33%) |
| §103 only | 1 (33%) |
| Multi-statute (no §101) | 1 (33%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| HWANG, MEGAN ELIZABETH | 1 | 55.9% | +58.6% |
| ZEVITZ, DANIELLE ELIZABETH | 1 | 34.3% | +60.0% |
| NGUYEN, MAIKHANH | 1 | 87.1% | +29.7% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17450398 | ADAPTIVE TUNING PARAMETERS FOR A CLASSIFICATION NEURAL NETWORK | NGUYEN, MAIKHANH | 62d |
| 17703969 | END-TO-END ADAPTIVE DEEP LEARNING TRAINING AND INFERENCE METHOD AND TOOL CHAIN TO IMPROVE PERFORMANCE AND SHORTEN DEVELOPMENT CYCLES | HWANG, MEGAN ELIZABETH | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17675947 | ALWAYS-ON WAKE ON MULTI-DIMENSIONAL PATTERN DETECTION (WOMPD) FROM A SENSOR FUSION CIRCUITRY | ZEVITZ, DANIELLE ELIZABETH | 25d overdue |
| 17450398 | ADAPTIVE TUNING PARAMETERS FOR A CLASSIFICATION NEURAL NETWORK | NGUYEN, MAIKHANH | 62d |
| 17703969 | END-TO-END ADAPTIVE DEEP LEARNING TRAINING AND INFERENCE METHOD AND TOOL CHAIN TO IMPROVE PERFORMANCE AND SHORTEN DEVELOPMENT CYCLES | HWANG, MEGAN ELIZABETH | — |
| Art Unit | Apps |
|---|---|
| 2143 | 1 |
| 2655 | 1 |
| 2144 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 17703969 | END-TO-END ADAPTIVE DEEP LEARNING TRAINING AND INFERENCE METHOD AND TOOL CHAIN TO IMPROVE PERFORMANCE AND SHORTEN DEVELOPMENT CYCLES | HWANG, MEGAN ELIZABETH | 2143 | §103§112 | Non-Final OA | — | Pending | Mar 24, 2022 |
| 17675947 | ALWAYS-ON WAKE ON MULTI-DIMENSIONAL PATTERN DETECTION (WOMPD) FROM A SENSOR FUSION CIRCUITRY | ZEVITZ, DANIELLE ELIZABETH | 2655 | §103 | Non-Final OA | 25d overdue | Pending | Feb 18, 2022 |
| 17450398 | ADAPTIVE TUNING PARAMETERS FOR A CLASSIFICATION NEURAL NETWORK | NGUYEN, MAIKHANH | 2144 | §101§102§103 | Final Rejection | 62d | Pending | Oct 08, 2021 |
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Start Free TrialAondevices Inc. has 3 pending office actions as of October 2026, spread across 3 art units and 3 examiners.
Megan Elizabeth Hwang has the most, with 1 of Aondevices Inc.'s pending office actions.
Mostly Computing & Software (USPTO Tech Center 2100), based on where its pending office actions are examined.
