Prosecution Insights
Prosecution Insights
Technology area: Communications
13 pending office actions • 1 client • 13 examiners • 6 art units • 0 of 13 (0%) have an AI response strategy ready • 14 patents granted in the last 365 days
ZILKA-KOTAB, PC- NVID has handled 1296 career applications, focusing on the Communications technology area. The firm maintains a resolved allowance rate pct of 96.48. This figure highlights the success rate for applications that reach a final disposition.
The prosecution process averages 4.23 office actions per allowance, suggesting that the firm frequently engages in extended dialogue with examiners to secure these allowances. Currently, the firm has 9 pending office actions. This indicates that most of the 1296 career applications have been resolved.
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 | 2 (15%) |
| §103 only | 4 (31%) |
| §102 only | 1 (8%) |
| Multi-statute (no §101) | 6 (46%) |
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 |
|---|---|---|---|
| NGUYEN, CHAN T H | 1 | 86.4% | +2.7% |
| SALVUCCI, MATTHEW D | 1 | 72.3% | +27.4% |
| LE, JOHNNY TRAN | 1 | 55.6% | +16.7% |
| CARTER, AARON W | 1 | 84.9% | +8.9% |
| TORRES, JOSE | 1 | 82.0% | +12.2% |
| PHAKOUSONH, DARAVANH | 1 | 25.0% | +100.0% |
| PHAM, NAM D | 1 | 91.0% | +1.7% |
| JONES, RAVEN SIMONE | 1 | 87.5% | +33.3% |
| FLORA, NURUN N | 1 | 86.1% | +1.7% |
| SCHNEE, HAL W | 1 | 84.5% | +22.3% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18395198 | POINT-LEVEL SUPERVISION FOR VIDEO INSTANCE SEGMENTATION | JONES, RAVEN SIMONE | — |
| 18531544 | VOXEL-TO-3D CONTENT GENERATOR | FLORA, NURUN N | — |
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 |
|---|---|---|---|
| 18212629 | SYNTHETIC DATASET GENERATOR | LUDWIG, PETER L | 30d overdue |
| 19084565 | CAMERA WITH COMPRESSIVE SENSING | NGUYEN, CHAN T H | — |
| 18963075 | VIEW SYNTHESIS USING CAMERA POSES LEARNED FROM A VIDEO | LE, JOHNNY TRAN | — |
| 18890544 | NEURAL NETWORK ARCHITECTURE FOR IMPLICIT LEARNING OF A PARAMETRIC DISTRIBUTION OF DATA | CARTER, AARON W | — |
| 18882629 | DUAL FORMULATION FOR A COMPUTER VISION RETENTION MODEL | TORRES, JOSE | — |
| 18602951 | COMPRESSION OF MACHINE LEARNING MODELS VIA SPARSIFICATION AND QUANTIZATION | PHAKOUSONH, DARAVANH | — |
| 18593742 | VARIATIONAL INFERENCING BY A DIFFUSION MODEL | PHAM, NAM D | — |
| 18375377 | DYNAMIC PATH SELECTION FOR PROCESSING THROUGH A MULTI-LAYER NEURAL NETWORK | SCHNEE, HAL W | — |
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 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19043176 | RESERVOIR-BASED SPATIOTEMPORAL IMPORTANCE RESAMPLING UTILIZING A GLOBAL ILLUMINATION DATA STRUCTURE | SALVUCCI, MATTHEW D | — |
| 18963075 | VIEW SYNTHESIS USING CAMERA POSES LEARNED FROM A VIDEO | LE, JOHNNY TRAN | — |
| 18882629 | DUAL FORMULATION FOR A COMPUTER VISION RETENTION MODEL | TORRES, JOSE | — |
| 18602951 | COMPRESSION OF MACHINE LEARNING MODELS VIA SPARSIFICATION AND QUANTIZATION | PHAKOUSONH, DARAVANH | — |
| 18395198 | POINT-LEVEL SUPERVISION FOR VIDEO INSTANCE SEGMENTATION | JONES, RAVEN SIMONE | — |
| 18375377 | DYNAMIC PATH SELECTION FOR PROCESSING THROUGH A MULTI-LAYER NEURAL NETWORK | SCHNEE, HAL W | — |
| Client (Assignee) | Pending OAs |
|---|---|
| NVIDIA | 13 |
| Art Unit | Apps |
|---|---|
| 2665 | 1 |
| 2619 | 1 |
| 2129 | 1 |
| 2400 | 1 |
| 3627 | 1 |
| 2667 | 1 |
| App # | Title | Client | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|---|
| 19084565 | CAMERA WITH COMPRESSIVE SENSING | Nvidia Corporation | NGUYEN, CHAN T H | §102§103 | Non-Final OA | — | Pending | Mar 19, 2025 | |
| 19043176 | RESERVOIR-BASED SPATIOTEMPORAL IMPORTANCE RESAMPLING UTILIZING A GLOBAL ILLUMINATION DATA STRUCTURE | Nvidia Corporation | SALVUCCI, MATTHEW D | §103 | Non-Final OA | — | Pending | Jan 31, 2025 | |
| 18963075 | VIEW SYNTHESIS USING CAMERA POSES LEARNED FROM A VIDEO | Nvidia Corporation | LE, JOHNNY TRAN | §103§112 | Non-Final OA | — | Pending | Nov 27, 2024 | |
| 18890544 | NEURAL NETWORK ARCHITECTURE FOR IMPLICIT LEARNING OF A PARAMETRIC DISTRIBUTION OF DATA | Nvidia Corporation | CARTER, AARON W | §102§103 | Non-Final OA | — | Pending | Sep 19, 2024 | |
| 18882629 | DUAL FORMULATION FOR A COMPUTER VISION RETENTION MODEL | Nvidia Corporation | TORRES, JOSE | §103§112 | Non-Final OA | — | Pending | Sep 11, 2024 | |
| 18602951 | COMPRESSION OF MACHINE LEARNING MODELS VIA SPARSIFICATION AND QUANTIZATION | Nvidia Corporation | PHAKOUSONH, DARAVANH | §101§112 | Non-Final OA | — | Pending | Mar 12, 2024 | |
| 18593742 | VARIATIONAL INFERENCING BY A DIFFUSION MODEL | Nvidia Corporation | PHAM, NAM D | §102§103 | Non-Final OA | — | Pending | Mar 01, 2024 | |
| 18395198 | POINT-LEVEL SUPERVISION FOR VIDEO INSTANCE SEGMENTATION | Nvidia Corporation | JONES, RAVEN SIMONE | 2665 | §103 | Non-Final OA | — | Pending | Dec 22, 2023 |
| 18531544 | VOXEL-TO-3D CONTENT GENERATOR | Nvidia Corporation | FLORA, NURUN N | 2619 | §103 | Non-Final OA | — | Pending | Dec 06, 2023 |
| 18375377 | DYNAMIC PATH SELECTION FOR PROCESSING THROUGH A MULTI-LAYER NEURAL NETWORK | Nvidia Corporation | SCHNEE, HAL W | 2129 | §102§103§112 | Final Rejection | — | Pending | Sep 29, 2023 |
| 18243555 | LANDMARK DETECTION WITH AN ITERATIVE NEURAL NETWORK | Nvidia Corporation | CZEKAJ, DAVID J | 2400 | §103 | Non-Final OA | — | Pending | Sep 07, 2023 |
| 18212629 | SYNTHETIC DATASET GENERATOR | Nvidia Corporation | LUDWIG, PETER L | 3627 | §101§103 | Final Rejection | 30d overdue | Pending | Jun 21, 2023 |
| 17893038 | PERFORMING VISUAL RELATIONAL REASONING | Nvidia Corporation | DUONG, JOHNNYKHOI BAO | 2667 | §102 | Non-Final OA | 4d overdue | Pending | Aug 22, 2022 |
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