Prosecution Insights
Prosecution Insights
Technology areas: Communications • Transportation, E-Commerce & Mechanical Systems
21 pending office actions • 13 art units • 20 examiners • 0 of 21 (0%) have an AI response strategy ready • 27 patents granted in the last 365 days
Autobrains Technologies Ltd. manages 21 pending office actions in the Communications technology area. These matters are spread across 19 distinct examiners and 12 distinct art units. This high volume of activity suggests a broad and active prosecution strategy within the communications sector. The 21 pending office actions represent a significant workload that is distributed widely across the USPTO's technical divisions, indicating a diverse range of technologies being developed by the company.
HO, MATTHEW is the busiest examiner for the portfolio. This examiner is currently handling 3 pending office actions. With 19 distinct examiners managing the portfolio, the majority of the workload is distributed individually, though some examiners like the busiest one handle multiple cases. This wide distribution across 12 art units requires a complex management strategy to ensure consistency in prosecution. The fact that HO, MATTHEW manages 3 actions makes his individual examination style a notable factor in the portfolio's overall progress.
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 + other | 5 (24%) |
| §103 only | 8 (38%) |
| §112 only | 3 (14%) |
| Double-patenting + other | 1 (5%) |
| Multi-statute (no §101) | 4 (19%) |
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 |
|---|---|---|---|
| HO, MATTHEW | 2 | 73.9% | +12.6% |
| REFAI, RAMSEY | 1 | 50.7% | +12.3% |
| SITTNER, MATTHEW T | 1 | 57.9% | +56.1% |
| COUSO, JOSE L | 1 | 90.1% | +8.4% |
| MCCLEARY, CAITLIN RENEE | 1 | 59.8% | +25.3% |
| SCHOECH, ASHLEY TIFFANY | 1 | 68.8% | +28.1% |
| PARK, EDWARD | 1 | 82.3% | +17.9% |
| SHIMELES, BEZAWIT NOLAWI | 1 | 88.9% | +0.0% |
| SMITH, JORDAN T | 1 | 66.3% | +10.2% |
| DANG, RACHEL YEN VI | 1 | 100.0% | +0.0% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18800477 | LEARNING BY PREDICTION THROUGH IMAGE LEVEL REPRESENTATION | COUSO, JOSE L | — |
| 18651522 | DYNAMIC CLASSIFICATION FOR AUTONOMOUS DRIVING | SHIMELES, BEZAWIT NOLAWI | — |
| 18624057 | TRACKING ROAD ELEMENTS IN AN ENVIRONMENT OF A VEHICLE | DANG, RACHEL YEN VI | — |
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 |
|---|---|---|---|
| 18595381 | TRAVEL LANE ELEMENT CLASSIFICATION | KUDO, KEN | 23d |
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | — |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | — |
| 18746213 | CUSTOMIZED PROTOTYPE BASED TRAINING FOR EMBEDDING CLASSIFICATIONS | PARK, EDWARD | — |
| 18627440 | USING SENSED INFORMATION FROM DIFFERENT TYPES OF SENSORS | SMITH, JORDAN T | — |
| 18610222 | SELF-LEARNING OF RELEVANCY METRICS FOR PERCEPTION RELATED APPLICATIONS | HAN, BYUNGKWON | — |
| 18522910 | SYSTEM AND METHOD OF CREATING INTERPRETABLE LATENT REPRESENTATIONS OF AN ARTIFICIAL INTELLIGENCE MODEL | DUONG, HIEN LUONGVAN | — |
| 18466793 | Accuracy of Object Detection | HO, MATTHEW | — |
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 |
|---|---|---|---|
| 18773590 | DIRECTING TRAFFIC ASSISTANCE SKILL | SCHOECH, ASHLEY TIFFANY | 17d overdue |
| 18914860 | ENHANCEMENT OF AI MODELS FOR AUTONOMOUS DRIVING PER LOCALIZATION | HO, MATTHEW | 4d overdue |
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | — |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | — |
| 18800751 | SELECTIVE LEARNING BY PREDICTION FOR DRIVING | MCCLEARY, CAITLIN RENEE | — |
| 18746213 | CUSTOMIZED PROTOTYPE BASED TRAINING FOR EMBEDDING CLASSIFICATIONS | PARK, EDWARD | — |
| 18627440 | USING SENSED INFORMATION FROM DIFFERENT TYPES OF SENSORS | SMITH, JORDAN T | — |
| 18466793 | Accuracy of Object Detection | HO, MATTHEW | — |
| Art Unit | Apps |
|---|---|
| 3669 | 3 |
| 2672 | 2 |
| 3664 | 1 |
| 3629 | 1 |
| 2667 | 1 |
| 2675 | 1 |
| 2673 | 1 |
| 2661 | 1 |
| 2671 | 1 |
| 2857 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18914860 | ENHANCEMENT OF AI MODELS FOR AUTONOMOUS DRIVING PER LOCALIZATION | HO, MATTHEW | 3669 | §103 | Non-Final OA | 4d overdue | Pending | Oct 14, 2024 |
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | 3664 | §102§103§112 | Final Rejection | — | Pending | Sep 26, 2024 |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | 3629 | §101§103§112 | Non-Final OA | — | Pending | Sep 02, 2024 |
| 18800477 | LEARNING BY PREDICTION THROUGH IMAGE LEVEL REPRESENTATION | COUSO, JOSE L | 2667 | §102DP | Final Rejection | — | Pending | Aug 12, 2024 |
| 18800751 | SELECTIVE LEARNING BY PREDICTION FOR DRIVING | MCCLEARY, CAITLIN RENEE | 3669 | §103 | Non-Final OA | — | Pending | Aug 12, 2024 |
| 18773590 | DIRECTING TRAFFIC ASSISTANCE SKILL | SCHOECH, ASHLEY TIFFANY | 3669 | §103 | Final Rejection | 17d overdue | Pending | Jul 16, 2024 |
| 18746213 | CUSTOMIZED PROTOTYPE BASED TRAINING FOR EMBEDDING CLASSIFICATIONS | PARK, EDWARD | 2675 | §102§103 | Non-Final OA | — | Pending | Jun 18, 2024 |
| 18651522 | DYNAMIC CLASSIFICATION FOR AUTONOMOUS DRIVING | SHIMELES, BEZAWIT NOLAWI | 2673 | §103 | Final Rejection | — | Pending | Apr 30, 2024 |
| 18627440 | USING SENSED INFORMATION FROM DIFFERENT TYPES OF SENSORS | SMITH, JORDAN T | — | §101§103 | Non-Final OA | — | Pending | Apr 04, 2024 |
| 18624057 | TRACKING ROAD ELEMENTS IN AN ENVIRONMENT OF A VEHICLE | DANG, RACHEL YEN VI | 2661 | §112 | Final Rejection | — | Pending | Apr 01, 2024 |
| 18610222 | SELF-LEARNING OF RELEVANCY METRICS FOR PERCEPTION RELATED APPLICATIONS | HAN, BYUNGKWON | — | §101§102§103§112 | Non-Final OA | — | Pending | Mar 19, 2024 |
| 18606772 | ADAPTABLE IMAGE SIGNAL PROCESSING FOR A VEHICLE | SHARIFF, MICHAEL ADAM | 2672 | §103 | Non-Final OA | — | Pending | Mar 15, 2024 |
| 18595381 | TRAVEL LANE ELEMENT CLASSIFICATION | KUDO, KEN | 2671 | §103§112 | Final Rejection | 23d | Pending | Mar 04, 2024 |
| 18405500 | OVERCOMING TECHNICAL CHALLANGES OF WORKING IN A VERY HIGH DIMENSIONAL SPACE | SHALU, ZELALEM W | — | §103 | Non-Final OA | — | Pending | Jan 05, 2024 |
| 18522910 | SYSTEM AND METHOD OF CREATING INTERPRETABLE LATENT REPRESENTATIONS OF AN ARTIFICIAL INTELLIGENCE MODEL | DUONG, HIEN LUONGVAN | — | §101§103 | Non-Final OA | — | Pending | Nov 29, 2023 |
| 18504834 | VISUALIZING NEURONS IN AN ARTIFICIAL INTELLIGENCE MODEL | KIM, JONATHAN J | — | §103 | Non-Final OA | — | Pending | Nov 08, 2023 |
| 18493274 | Tracking Objects in Image Frames | CHAN, CAROL WANG | 2672 | §112 | Non-Final OA | 31d overdue | Pending | Oct 24, 2023 |
| 18466793 | Accuracy of Object Detection | HO, MATTHEW | 2857 | §101§102§103§112 | Non-Final OA | — | Pending | Sep 13, 2023 |
| 18355324 | DRIVING RELATED AUGMENTED VIRTUAL FIELDS | ARTIMEZ, DANA FERREN | 3667 | §112 | Non-Final OA | — | Pending | Jul 19, 2023 |
| 18355370 | ACCURATE BOUNDING BOX LOCALIZATION FOR AUTOMATIC TAGGING SYSTEM USING PHYSICAL GROUND TRUTH | ORANGE, DAVID BENJAMIN | 2663 | §103 | Non-Final OA | 33d | Pending | Jul 19, 2023 |
| 18327865 | PASSIVE READOUT | KIM, DAVID | 2141 | §103§112 | Final Rejection | — | Pending | Jun 01, 2023 |
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