Prosecution Insights
Prosecution Insights
Technology areas: Networking & Security • Communications
8 pending office actions • 2 art units • 8 examiners • 0 of 8 (0%) have an AI response strategy ready • 14 patents granted in the last 365 days
The Indian Institute Of Technology Madras (Iit Madras) has 6 pending office actions within the Communications technology area. Despite the volume of actions, all 6 pending office actions are concentrated within 1 distinct art unit. This suggests that while the institute has multiple active matters, they are all related to a specific technical niche within the broader communications field.
The prosecution workload is spread across a number of distinct examiners, which means that each pending action is being reviewed by a different individual. This distribution provides a variety of examiner perspectives even though the work is confined to a single art unit. NGUYEN, THIEN DANG is the busiest examiner for the portfolio, currently managing 1 busiest examiner pending action.
Because the busiest examiner pending count is limited, the workload is distributed among the distinct examiners. This lack of concentration with any single examiner may lead to varied prosecution experiences for the institute. Practitioners should note that the distinct art unit serves as the primary administrative hub for all pending office actions in the Communications sector.
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 (25%) |
| §103 only | 2 (25%) |
| Multi-statute (no §101) | 4 (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 |
|---|---|---|---|
| NGUYEN, THIEN DANG | 1 | 87.4% | +11.7% |
| CHEN, PETER | 1 | 87.8% | +21.2% |
| HENSON, JAMAAL R | 1 | 84.4% | +4.3% |
| MASUR, PAUL H | 1 | 87.2% | +13.4% |
| SCHEIBEL, ROBERT C | 1 | 80.7% | +15.0% |
| HSU, BAILOR CHIA-JONG | 1 | 90.0% | +4.1% |
| BERA, HENA RAKESHKUMAR | 1 | — | — |
| SHEDRICK, CHARLES TERRELL | 1 | 77.7% | +9.5% |
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 |
|---|---|---|---|
| 18844702 | TRANSMISSION OF SOUNDING REFERENCE SIGNALS USING A PLURALITY OF PORTS OF A USER EQUIPMENT | CHEN, PETER | — |
| 18709408 | TRANSFORM-PRECODING OF A SELECTIVE SET OF DATA FOR TRANSMISSION OVER A WIRELESS COMMUNICATION NETWORK | HSU, BAILOR CHIA-JONG | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19073480 | Neural network-based decoder architecture for 5G | NGUYEN, THIEN DANG | — |
| 18839113 | METHODS OF WAVEFORM SWITCHING IN A CELLULAR NETWORK | HENSON, JAMAAL R | — |
| 18799434 | PHYSICAL LAYER SIGNALING PROCEDURES FOR AI/ML BASED CHANNEL FEEDBACK | MASUR, PAUL H | — |
| 18836162 | MANAGING CROSS-LINK INTERFERENCE IN A WIRELESS COMMUNICATION NETWORK | SCHEIBEL, ROBERT C | — |
| 18631994 | METHODS AND KITS FOR DETECTING CANNABINOIDS | BERA, HENA RAKESHKUMAR | — |
| 18697509 | METHOD OF IMPROVING ACCURACY OF POSITIONING A NODE IN A CELLULAR NETWORK | SHEDRICK, CHARLES TERRELL | — |
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 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19073480 | Neural network-based decoder architecture for 5G | NGUYEN, THIEN DANG | — |
| 18844702 | TRANSMISSION OF SOUNDING REFERENCE SIGNALS USING A PLURALITY OF PORTS OF A USER EQUIPMENT | CHEN, PETER | — |
| 18799434 | PHYSICAL LAYER SIGNALING PROCEDURES FOR AI/ML BASED CHANNEL FEEDBACK | MASUR, PAUL H | — |
| 18836162 | MANAGING CROSS-LINK INTERFERENCE IN A WIRELESS COMMUNICATION NETWORK | SCHEIBEL, ROBERT C | — |
| Art Unit | Apps |
|---|---|
| 2461 | 1 |
| 2646 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19073480 | Neural network-based decoder architecture for 5G | NGUYEN, THIEN DANG | — | §101§102§103§112 | Non-Final OA | — | Pending | Mar 07, 2025 |
| 18844702 | TRANSMISSION OF SOUNDING REFERENCE SIGNALS USING A PLURALITY OF PORTS OF A USER EQUIPMENT | CHEN, PETER | — | §103 | Non-Final OA | — | Pending | Sep 06, 2024 |
| 18839113 | METHODS OF WAVEFORM SWITCHING IN A CELLULAR NETWORK | HENSON, JAMAAL R | — | §102§103§112 | Non-Final OA | — | Pending | Aug 16, 2024 |
| 18799434 | PHYSICAL LAYER SIGNALING PROCEDURES FOR AI/ML BASED CHANNEL FEEDBACK | MASUR, PAUL H | — | §103§112 | Non-Final OA | — | Pending | Aug 09, 2024 |
| 18836162 | MANAGING CROSS-LINK INTERFERENCE IN A WIRELESS COMMUNICATION NETWORK | SCHEIBEL, ROBERT C | — | §102§103§112 | Non-Final OA | — | Pending | Aug 06, 2024 |
| 18709408 | TRANSFORM-PRECODING OF A SELECTIVE SET OF DATA FOR TRANSMISSION OVER A WIRELESS COMMUNICATION NETWORK | HSU, BAILOR CHIA-JONG | 2461 | §103 | Final Rejection | — | Pending | May 10, 2024 |
| 18631994 | METHODS AND KITS FOR DETECTING CANNABINOIDS | BERA, HENA RAKESHKUMAR | — | §101§103§112 | Non-Final OA | — | Pending | Apr 10, 2024 |
| 18697509 | METHOD OF IMPROVING ACCURACY OF POSITIONING A NODE IN A CELLULAR NETWORK | SHEDRICK, CHARLES TERRELL | 2646 | §102§103 | Non-Final OA | — | Pending | Apr 01, 2024 |
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