Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
2 pending office actions • 2 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready
Dongguan University Of Technology currently manages 2 pending office actions in the Transportation, E-Commerce & Mechanical Systems technology area. These actions are assigned to 2 distinct examiners across 2 distinct art units. OLSON, LARS A is the busiest examiner, holding 1 pending office action. This busiest examiner pending count of 1 indicates that each of the 2 pending office actions is handled by a different examiner in a different art unit. This lack of examiner concentration means that each pending matter is being handled by a different individual, requiring separate tactical approaches for each case.
The presence of 2 distinct art units indicates that the 2 pending office actions are located in different administrative divisions of the patent office. With 2 distinct examiners and 2 distinct art units, the company must manage two independent prosecution paths. The busiest examiner pending count of 1 confirms that no single examiner has oversight of both pending actions. This distribution requires the legal team to adapt to the preferences of OLSON, LARS A and the other distinct examiner. The 2 pending office actions represent the current total workload for Dongguan University Of Technology in the Transportation, E-Commerce & Mechanical Systems field.
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 (50%) |
| Multi-statute (no §101) | 1 (50%) |
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 |
|---|---|---|---|
| OLSON, LARS A | 1 | 82.0% | +14.0% |
| HONORE, EVEL NMN | 1 | 50.0% | +28.6% |
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 |
|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | — |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | — |
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 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | — |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | — |
| Art Unit | Apps |
|---|---|
| 3615 | 1 |
| 2142 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | 3615 | §103§112 | Non-Final OA | — | Pending | Sep 24, 2024 |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | 2142 | §101 | Non-Final OA | — | Pending | Mar 22, 2024 |
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Start Free TrialDongguan University Of Technology has 2 pending office actions as of October 2026, spread across 2 art units and 2 examiners.
Lars A Olson has the most, with 1 of Dongguan University Of Technology's pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.
