Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19068261 | METHOD AND SYSTEM FOR PERCEIVING AND ELIMINATING ABNORMAL STATE OF ACTIVE DISTRIBUTION NETWORK BASED ON DATA ENHANCEMENT | March 2025 | October 2025 | Allow | 7 | 1 | 0 | Yes | No |
| 18882311 | APPARATUS AND METHOD FOR DATA GENERATION FOR USER ENGAGEMENT | September 2024 | July 2025 | Allow | 11 | 2 | 0 | Yes | No |
| 18602908 | ARBITRARILY LOW-LATENCY INTERFERENCE WITH COMPUTATIONALLY INTENSIVE MACHING LEARNING VIA PRE-FETCHING | March 2024 | September 2025 | Abandon | 18 | 2 | 0 | Yes | No |
| 18083770 | SPIKING NEURAL NETWORK | December 2022 | March 2026 | Allow | 39 | 1 | 0 | Yes | No |
| 17872950 | APPARATUS AND METHODS FOR ANALYZING DEFICIENCIES | July 2022 | December 2025 | Abandon | 41 | 1 | 0 | No | No |
| 17771474 | METHOD FOR DISTRIBUTING LABELING WORK ACCORDING TO DIFFICULTY THEREOF AND APPARATUS USING SAME | April 2022 | November 2025 | Abandon | 43 | 1 | 0 | No | No |
| 17719349 | Training method and system for machine learning assisted determination of product HS-Codes | April 2022 | October 2025 | Abandon | 42 | 1 | 0 | No | No |
| 17444687 | METHOD AND APPARATUS FOR UPDATING PARAMETER OF MULTI-TASK MODEL, AND STORAGE MEDIUM | August 2021 | August 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17444418 | USING ARTIFICIAL INTELLIGENCE TO OPTIMIZE SEAM PLACEMENT ON 3D MODELS | August 2021 | April 2025 | Abandon | 44 | 1 | 0 | No | No |
| 17443252 | REGION OF INTEREST CONVOLUTIONAL NEURAL NETWORK PROCESSING | July 2021 | October 2025 | Abandon | 51 | 2 | 0 | Yes | No |
| 17372605 | Quantum Entanglement For Distributed Actions | July 2021 | July 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17363141 | DYNAMIC DESIGN METHOD TO IMPROVE THE ADAPTABILITY OF ACCELERATION UNITS TO NEURAL NETWORKS | June 2021 | January 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17358694 | TEMPORALIZING OR SPATIALIZING NETWORKS | June 2021 | November 2024 | Allow | 40 | 2 | 0 | Yes | No |
| 17336250 | PARTIAL-ACTIVATION OF NEURAL NETWORK BASED ON HEAT-MAP OF NEURAL NETWORK ACTIVITY | June 2021 | February 2025 | Allow | 44 | 1 | 0 | No | No |
| 17324303 | SYSTEMS AND METHODS FOR SOCIAL STRUCTURE CONSTRUCTION OF FORUMS USING INTERACTION COHERENCE | May 2021 | December 2025 | Abandon | 55 | 3 | 0 | Yes | No |
| 17324298 | INFORMATION PROCESSING APPARATUS AND NON-TRANSITORY COMPUTER READABLE MEDIUM | May 2021 | February 2025 | Abandon | 45 | 1 | 0 | No | No |
| 17324338 | EFFICIENT EXECUTION OF GROUP-SPARSIFIED NEURAL NETWORKS | May 2021 | September 2025 | Allow | 52 | 3 | 0 | Yes | No |
| 17322828 | SYSTEM AND METHOD FOR UTILIZING GROUPED PARTIAL DEPENDENCE PLOTS AND GAME-THEORETIC CONCEPTS AND THEIR EXTENSIONS IN THE GENERATION OF ADVERSE ACTION REASON CODES | May 2021 | January 2025 | Allow | 44 | 1 | 0 | Yes | No |
| 17319097 | VEHICLE-MOUNTED PROCESSING DEVICE OF LEARNING-USE DATA | May 2021 | January 2025 | Abandon | 45 | 2 | 0 | Yes | No |
| 17231514 | METHODS, DEVICES AND MEDIA FOR RE-WEIGHTING TO IMPROVE KNOWLEDGE DISTILLATION | April 2021 | November 2025 | Allow | 55 | 2 | 0 | No | No |
| 17229147 | MULTIMODAL ANALYSIS COMBINING MONITORING MODALITIES TO ELICIT COGNITIVE STATES AND PERFORM SCREENING FOR MENTAL DISORDERS | April 2021 | December 2024 | Abandon | 44 | 1 | 0 | No | No |
| 17191518 | ALIGNING KNOWLEDGE GRAPHS USING SUBGRAPH TYPING | March 2021 | February 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17248848 | UTILIZING MACHINE LEARNING TO DETECT SINGLE AND CLUSTER-TYPE ANOMALIES IN A DATA SET | February 2021 | February 2026 | Abandon | 60 | 4 | 0 | Yes | No |
| 17265476 | METHOD AND DEVICE FOR TRAINING A MACHINE LEARNING ROUTINE FOR CONTROLLING A TECHNICAL SYSTEM | February 2021 | April 2025 | Allow | 50 | 3 | 0 | No | No |
| 17161152 | HYBRID GRAPH NEURAL NETWORK | January 2021 | January 2025 | Allow | 47 | 2 | 0 | Yes | No |
| 17153852 | ARTIFICIAL INTELLIGENCE OPTIMIZATION PLATFORM | January 2021 | January 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17148707 | VIRTUAL OPERATION ASSISTANT | January 2021 | February 2025 | Abandon | 49 | 2 | 0 | No | No |
| 17122621 | COMPUTER-READABLE RECORDING MEDIUM, INFORMATION PROCESSING APPARATUS, AND DATA GENERATING METHOD | December 2020 | December 2024 | Abandon | 48 | 2 | 0 | No | No |
| 17251508 | NEURAL NETWORKS HAVING REDUCED NUMBER OF PARAMETERS | December 2020 | December 2024 | Allow | 48 | 2 | 0 | Yes | No |
| 17116138 | THREE-DIMENSIONAL INTERSECTION STRUCTURE PREDICTION FOR AUTONOMOUS DRIVING APPLICATIONS | December 2020 | January 2025 | Allow | 49 | 2 | 0 | Yes | No |
| 17116698 | METHODS AND APPARATUS FOR AUTOMATIC ATTRIBUTE EXTRACTION FOR TRAINING MACHINE LEARNING MODELS | December 2020 | January 2025 | Allow | 49 | 2 | 0 | Yes | No |
| 16952523 | APPARATUS AND METHOD FOR DISTINGUISHING NEURAL WAVEFORMS | November 2020 | November 2024 | Allow | 48 | 2 | 0 | No | No |
| 16951768 | ARTIFICIAL NEURAL NETWORK BYPASS | November 2020 | November 2024 | Allow | 48 | 2 | 0 | Yes | No |
| 17082867 | METHOD, ELECTRONIC DEVICE, AND COMPUTER PROGRAM PRODUCT FOR PROCESSING MACHINE LEARNING MODEL | October 2020 | October 2025 | Abandon | 60 | 4 | 0 | Yes | No |
| 17061499 | DECIMATING HIDDEN LAYERS FOR TRAINING TRANSFORMER MODELS | October 2020 | January 2025 | Abandon | 52 | 3 | 0 | Yes | No |
| 17039294 | FEDERATED INFERENCE | September 2020 | January 2025 | Abandon | 51 | 2 | 0 | No | No |
| 17023679 | SHIFTLEFT TOPOLOGY CONSTRUCTION AND INFORMATION AUGMENTATION USING MACHINE LEARNING | September 2020 | October 2024 | Allow | 49 | 3 | 0 | Yes | No |
| 17018923 | SYSTEM AND METHOD FOR DETECTING AND RECTIFYING CONCEPT DRIFT IN FEDERATED LEARNING | September 2020 | November 2025 | Abandon | 60 | 4 | 0 | No | No |
No appeal data available for this record. This may indicate that no appeals have been filed or decided for applications in this dataset.
Examiner WU, NICHOLAS S works in Art Unit 2148 and has examined 31 patent applications in our dataset. With an allowance rate of 58.1%, this examiner allows applications at a lower rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 48 months.
Examiner WU, NICHOLAS S's allowance rate of 58.1% places them in the 18% percentile among all USPTO examiners. This examiner is less likely to allow applications than most examiners at the USPTO.
On average, applications examined by WU, NICHOLAS S receive 2.16 office actions before reaching final disposition. This places the examiner in the 59% percentile for office actions issued. This examiner issues a slightly above-average number of office actions.
The median time to disposition (half-life) for applications examined by WU, NICHOLAS S is 48 months. This places the examiner in the 8% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +33.6% benefit to allowance rate for applications examined by WU, NICHOLAS S. This interview benefit is in the 82% percentile among all examiners. Recommendation: Interviews are highly effective with this examiner and should be strongly considered as a prosecution strategy. Per MPEP § 713.10, interviews are available at any time before the Notice of Allowance is mailed or jurisdiction transfers to the PTAB.
When applicants file an RCE with this examiner, 33.3% of applications are subsequently allowed. This success rate is in the 72% percentile among all examiners. Strategic Insight: RCEs show above-average effectiveness with this examiner. Consider whether your amendments or new arguments are strong enough to warrant an RCE versus filing a continuation.
This examiner enters after-final amendments leading to allowance in 26.7% of cases where such amendments are filed. This entry rate is in the 37% percentile among all examiners. Strategic Recommendation: This examiner shows below-average receptiveness to after-final amendments. You may need to file an RCE or appeal rather than relying on after-final amendment entry.
When applicants file petitions regarding this examiner's actions, 200.0% are granted (fully or in part). This grant rate is in the 98% percentile among all examiners. Strategic Note: Petitions are frequently granted regarding this examiner's actions compared to other examiners. Per MPEP § 1002.02(c), various examiner actions are petitionable to the Technology Center Director, including prematureness of final rejection, refusal to enter amendments, and requirement for information. If you believe an examiner action is improper, consider filing a petition.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 11% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 11% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.