Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
16 pending office actions • 15 art units • 16 examiners • 0 of 16 (0%) have an AI response strategy ready • 19 patents granted in the last 365 days
Home Depot Product Authority LLC has 16 pending office actions in Computing & Software. The matters are distributed among 16 distinct examiners and 15 distinct art units. This indicates a separate examiner assignment for each pending matter, with some overlap at the art-unit level.
CHOI, YUK TING is the busiest examiner with 1 pending matter. Because no examiner handles more than one matter in the available data, the principal management challenge is coordination across numerous individual examination relationships. Counsel can use the shared technology area and the limited art-unit overlap to standardize issue tracking while tailoring each response to its assigned examiner.
Based on the USPTO statutory response window for each pending office action. 5 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 5 of the docket's apps have a known mailing date.
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 only | 1 (6%) |
| §101 + other | 4 (25%) |
| §103 only | 4 (25%) |
| §102 only | 2 (12%) |
| Double-patenting only | 1 (6%) |
| Multi-statute (no §101) | 4 (25%) |
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 |
|---|---|---|---|
| CHOI, YUK TING | 1 | 71.5% | +36.4% |
| LEVINE, ADAM L | 1 | 35.9% | +40.0% |
| NGUYEN, TUAN HOANG | 1 | 90.5% | +4.0% |
| DUCKWORTH, BRADLEY | 1 | 72.4% | +20.1% |
| CHEN, HUO LONG | 1 | 53.8% | +30.0% |
| MARI VALCARCEL, FERNANDO MARIANO | 1 | 49.1% | +19.9% |
| SKHOUN, HICHAM | 1 | 77.1% | +5.5% |
| BREENE, PAUL J | 1 | 60.0% | +18.3% |
| SMITH, BRIAN M | 1 | 52.5% | +36.9% |
| GRANO, ERNESTO ARTURIO | 1 | 61.2% | +25.3% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19012537 | DETERMINING VISUALLY SIMILAR IMAGES | NGUYEN, TUAN HOANG | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18097070 | INCREMENTAL MACHINE LEARNING TRAINING | CHEN, KUANG FU | 7d |
| 18103744 | TIGHTENING ROD FOR SLING CHAIR | GABLER, PHILIP F | 69d |
| 18870012 | MODULAR AND POLYVALENT TOP PANEL FOR FURNITURE | DUCKWORTH, BRADLEY | 84d |
| 19080224 | COMPLEMENTARY ITEM RECOMMENDATIONS BASED ON MULTI-MODAL EMBEDDINGS | LEVINE, ADAM L | — |
| 18960394 | ITEM IMAGE LIBRARY MAINTENANCE BASED ON LOW-QUALITY IMAGES | CHEN, HUO LONG | — |
| 18736371 | ENHANCING NEXT ITEM RECOMMENDATION THROUGH CROSS-ATTENTION | BREENE, PAUL J | — |
| 18431370 | USER SELECTION PREDICTION BASED ON GRAPH NEURAL NETWORK AND USER SELECTION SEQUENCE | SMITH, BRIAN M | — |
| 18084324 | MACHINE LEARNING-BASED USER SELECTION PREDICTION BASED ON SEQUENCE OF PRIOR USER SELECTIONS | MENGISTU, TEWODROS E | — |
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 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18932484 | PRESENTATION OF RELATED AND CORRECTED QUERIES FOR A SEARCH ENGINE | MARI VALCARCEL, FERNANDO MARIANO | 22d |
| 18870012 | MODULAR AND POLYVALENT TOP PANEL FOR FURNITURE | DUCKWORTH, BRADLEY | 84d |
| 19197329 | USER CLICK MODELLING IN SEARCH QUERIES | CHOI, YUK TING | — |
| 19080224 | COMPLEMENTARY ITEM RECOMMENDATIONS BASED ON MULTI-MODAL EMBEDDINGS | LEVINE, ADAM L | — |
| 18960394 | ITEM IMAGE LIBRARY MAINTENANCE BASED ON LOW-QUALITY IMAGES | CHEN, HUO LONG | — |
| 18736371 | ENHANCING NEXT ITEM RECOMMENDATION THROUGH CROSS-ATTENTION | BREENE, PAUL J | — |
| 18431370 | USER SELECTION PREDICTION BASED ON GRAPH NEURAL NETWORK AND USER SELECTION SEQUENCE | SMITH, BRIAN M | — |
| 18569526 | ACCESSORY ATTACHMENT ASSEMBLY FOR CONTAINER | GRANO, ERNESTO ARTURIO | — |
| Art Unit | Apps |
|---|---|
| 2164 | 2 |
| 3689 | 1 |
| 2649 | 1 |
| 3632 | 1 |
| 2682 | 1 |
| 2159 | 1 |
| 2129 | 1 |
| 2122 | 1 |
| 3735 | 1 |
| 3636 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19197329 | USER CLICK MODELLING IN SEARCH QUERIES | CHOI, YUK TING | 2164 | §103 | Final Rejection | — | Pending | May 02, 2025 |
| 19080224 | COMPLEMENTARY ITEM RECOMMENDATIONS BASED ON MULTI-MODAL EMBEDDINGS | LEVINE, ADAM L | 3689 | §101§103Other | Non-Final OA | — | Pending | Mar 14, 2025 |
| 19012537 | DETERMINING VISUALLY SIMILAR IMAGES | NGUYEN, TUAN HOANG | 2649 | DP | Non-Final OA | — | Pending | Jan 07, 2025 |
| 18870012 | MODULAR AND POLYVALENT TOP PANEL FOR FURNITURE | DUCKWORTH, BRADLEY | 3632 | §102§112 | Non-Final OA | 84d | Pending | Nov 27, 2024 |
| 18960394 | ITEM IMAGE LIBRARY MAINTENANCE BASED ON LOW-QUALITY IMAGES | CHEN, HUO LONG | 2682 | §101§102§103 | Non-Final OA | — | Pending | Nov 26, 2024 |
| 18932484 | PRESENTATION OF RELATED AND CORRECTED QUERIES FOR A SEARCH ENGINE | MARI VALCARCEL, FERNANDO MARIANO | 2159 | §103 | Final Rejection | 22d | Pending | Oct 30, 2024 |
| 18901739 | GENERATION OF A SEQUENCE OF RELATED TEXT-BASED SEARCH QUERIES | SKHOUN, HICHAM | 2164 | §102 | Final Rejection | 9d | Pending | Sep 30, 2024 |
| 18736371 | ENHANCING NEXT ITEM RECOMMENDATION THROUGH CROSS-ATTENTION | BREENE, PAUL J | 2129 | §101§103§112 | Non-Final OA | — | Pending | Jun 06, 2024 |
| 18431370 | USER SELECTION PREDICTION BASED ON GRAPH NEURAL NETWORK AND USER SELECTION SEQUENCE | SMITH, BRIAN M | 2122 | §101§102§103§112 | Non-Final OA | — | Pending | Feb 02, 2024 |
| 18569526 | ACCESSORY ATTACHMENT ASSEMBLY FOR CONTAINER | GRANO, ERNESTO ARTURIO | 3735 | §102 | Non-Final OA | — | Pending | Dec 12, 2023 |
| 18103744 | TIGHTENING ROD FOR SLING CHAIR | GABLER, PHILIP F | 3636 | §102§103 | Final Rejection | 69d | Pending | Jan 31, 2023 |
| 18097070 | INCREMENTAL MACHINE LEARNING TRAINING | CHEN, KUANG FU | 2143 | §103§112 | Non-Final OA | 7d | Pending | Jan 13, 2023 |
| 18084324 | MACHINE LEARNING-BASED USER SELECTION PREDICTION BASED ON SEQUENCE OF PRIOR USER SELECTIONS | MENGISTU, TEWODROS E | 2127 | §103§112 | Non-Final OA | — | Pending | Dec 19, 2022 |
| 17947117 | MACHINE LEARNING-BASED USER SELECTION PREDICTION BASED ON SEQUENCE OF PRIOR USER SELECTIONS | KOWALIK, SKIELER ALEXANDER | 2142 | §103 | Non-Final OA | — | Pending | Sep 17, 2022 |
| 17891304 | WEAKLY-SUPERVISED COMPATIBLE PRODUCTS RECOMMENDATION | MEYER, JACQUELINE CHRISTINE | 2144 | §103 | Final Rejection | — | Pending | Aug 19, 2022 |
| 17887195 | INFORMATION-GREEDY MULTI-ARM BANDITS FOR ELECTRONIC USER INTERFACE EXPERIENCE TESTING | WEBB III, JAMES L | 3624 | §101 | Non-Final OA | — | Pending | Aug 12, 2022 |
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Start Free TrialHome Depot Product Authority LLC has 16 pending office actions as of October 2026, spread across 15 art units and 16 examiners.
Yuk Ting Choi has the most, with 1 of Home Depot Product Authority LLC's pending office actions.
Mostly Computing & Software (USPTO Tech Center 2100), based on where its pending office actions are examined.
