Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19250334 | NEURAL-SYMBOLIC HYBRID SYSTEM FOR DIRECT BINARY DOCUMENT SYNTHESIS WITH INTEGRATED CONSTRAINT SATISFACTION AND HARDWARE ACCELERATION | June 2025 | December 2025 | Allow | 5 | 0 | 1 | No | No |
| 19244450 | SYSTEMS AND METHODS OF SENSOR DATA FUSION | June 2025 | September 2025 | Allow | 3 | 1 | 0 | Yes | No |
| 19196841 | SYSTEMS, METHODS, AND GRAPHICAL USER INTERFACES FOR MITIGATING BIAS IN A MACHINE LEARNING-BASED DECISIONING MODEL | May 2025 | December 2025 | Allow | 8 | 1 | 1 | Yes | No |
| 19026469 | ENSEMBLE MACHINE LEARNING SYSTEMS AND METHODS | January 2025 | March 2026 | Allow | 13 | 2 | 1 | Yes | No |
| 19016241 | SYSTEMS AND METHODS OF SENSOR DATA FUSION | January 2025 | May 2025 | Allow | 4 | 1 | 0 | Yes | No |
| 18853426 | APPARATUS AND METHOD FOR IMPROVED INSPECTION AND/OR MAINTENANCE MANAGEMENT | October 2024 | February 2025 | Allow | 4 | 0 | 0 | No | No |
| 18845907 | Method, System, and Computer Program Product for Ensemble Learning With Rejection | September 2024 | March 2025 | Allow | 6 | 0 | 0 | No | No |
| 18819333 | AUTONOMOUS, WORLD-BUILDING, LIFELONG LEARNING AGENTS AND COMPUTING ENGINES FOR GENERAL-PURPOSE INTELLIGENCE | August 2024 | March 2025 | Allow | 6 | 0 | 0 | No | No |
| 18764967 | SYSTEMS, METHODS, AND GRAPHICAL USER INTERFACES FOR MITIGATING BIAS IN A MACHINE LEARNING-BASED DECISIONING MODEL | July 2024 | April 2025 | Allow | 9 | 1 | 1 | Yes | No |
| 18732399 | METHOD FOR UPDATING A NODE MODEL THAT RESISTS DISCRIMINATION PROPAGATION IN FEDERATED LEARNING | June 2024 | September 2024 | Allow | 3 | 0 | 0 | No | No |
| 18643787 | MULTI-PARTY MACHINE LEARNING USING A DATABASE CLEANROOM | April 2024 | September 2025 | Allow | 17 | 1 | 0 | Yes | No |
| 18637184 | METHODS, SYSTEMS, APPARATUSES, AND DEVICES FOR FACILITATING SIFR OPTIMIZER-BASED EFFICIENT NEURAL NETWORK TRAINING | April 2024 | August 2024 | Allow | 4 | 1 | 0 | No | No |
| 18696993 | DEEP NEURAL NETWORK CHECKPOINT OPTIMIZATION SYSTEM AND METHOD BASED ON NON-VOLATILE MEMORY | March 2024 | October 2025 | Allow | 19 | 0 | 0 | No | No |
| 18611405 | ENSEMBLE MACHINE LEARNING SYSTEMS AND METHODS | March 2024 | July 2024 | Allow | 4 | 1 | 0 | No | No |
| 18429937 | SEMICONDUCTOR DEVICE AND ELECTRONIC DEVICE | February 2024 | April 2025 | Allow | 14 | 0 | 0 | No | No |
| 18424764 | METHOD FOR DISTRIBUTING WORK POINTS TO A PLURALITY OF TASK-PERFORMING ROBOTS | January 2024 | May 2024 | Allow | 3 | 0 | 0 | No | No |
| 18412519 | METHOD FOR CONSTRUCTING TARGET PREDICTION MODEL IN MULTICENTER SMALL SAMPLE SCENARIO AND PREDICTION METHOD | January 2024 | February 2025 | Allow | 13 | 1 | 0 | No | No |
| 18403712 | REASONING ENGINE SERVICES | January 2024 | February 2025 | Allow | 14 | 1 | 1 | Yes | No |
| 18400767 | COMPOUND MODEL SCALING FOR NEURAL NETWORKS | December 2023 | August 2025 | Allow | 20 | 1 | 0 | No | No |
| 18397159 | DISPARITY MITIGATION IN MACHINE LEARNING-BASED PREDICTIONS FOR DISTINCT CLASSES OF DATA USING DERIVED INDISCERNIBILITY CONSTRAINTS DURING NEURAL NETWORK TRAINING | December 2023 | May 2024 | Allow | 5 | 1 | 0 | No | No |
| 18529014 | STANDARD ERROR FOR DEEP LEARNING MODEL OUTCOME ESTIMATOR | December 2023 | October 2024 | Allow | 10 | 1 | 0 | No | No |
| 18483998 | METHODS, SYSTEMS, APPARATUSES, AND DEVICES FOR SIFRIAN-BASED NEURAL NETWORK TRAINING | October 2023 | January 2024 | Allow | 3 | 1 | 0 | No | No |
| 18351440 | DATA-EFFICIENT REINFORCEMENT LEARNING FOR CONTINUOUS CONTROL TASKS | July 2023 | March 2025 | Allow | 20 | 2 | 0 | Yes | No |
| 18215784 | NON-INTRUSIVE LOAD MONITORING METHOD AND DEVICE BASED ON TEMPORAL ATTENTION MECHANISM | June 2023 | August 2023 | Allow | 2 | 0 | 0 | Yes | No |
| 18268665 | OPTICAL NEURAL NETWORK, DATA PROCESSING METHOD AND APPARATUS BASED ON SAME, AND STORAGE MEDIUM | June 2023 | February 2024 | Allow | 8 | 1 | 0 | No | No |
| 18338166 | AUTOMATED DETECTION OF CODE REGRESSIONS FROM TIME-SERIES DATA | June 2023 | December 2025 | Abandon | 30 | 1 | 0 | No | No |
| 18141737 | DISPARITY MITIGATION IN MACHINE LEARNING-BASED PREDICTIONS FOR DISTINCT CLASSES OF DATA USING DERIVED INDISCERNIBILITY CONSTRAINTS DURING NEURAL NETWORK TRAINING | May 2023 | September 2023 | Allow | 5 | 1 | 0 | No | No |
| 18308526 | METHODS TO ESTIMATE EFFECTIVENESS OF A MEDICAL TREATMENT | April 2023 | April 2025 | Allow | 24 | 0 | 0 | No | No |
| 18126557 | SPATIO-TEMPORAL CONSISTENCY EMBEDDINGS FROM MULTIPLE OBSERVED MODALITIES | March 2023 | January 2025 | Allow | 22 | 2 | 0 | No | No |
| 18189671 | CUSTOMIZABLE MACHINE LEARNING MODELS | March 2023 | March 2026 | Abandon | 36 | 3 | 0 | Yes | No |
| 18162695 | MULTI-PARTY MACHINE LEARNING USING A DATABASE CLEANROOM | January 2023 | March 2024 | Allow | 13 | 3 | 0 | Yes | No |
| 18067593 | Inference-Based Assignment of Data Type to Data | December 2022 | May 2025 | Abandon | 29 | 2 | 0 | Yes | No |
| 18063232 | Sense Element Engagement Process of Cortical Prosthetic Vision by Neural Networks | December 2022 | June 2023 | Allow | 7 | 0 | 0 | No | No |
| 18075297 | DISPARITY MITIGATION IN MACHINE LEARNING-BASED PREDICTIONS FOR DISTINCT CLASSES OF DATA USING DERIVED INDISCERNIBILITY CONSTRAINTS DURING NEURAL NETWORK TRAINING | December 2022 | March 2023 | Allow | 3 | 0 | 0 | No | No |
| 17989761 | OPTIMIZATION FOR ARTIFICIAL NEURAL NETWORK MODEL AND NEURAL PROCESSING UNIT | November 2022 | May 2023 | Allow | 6 | 1 | 0 | No | No |
| 17967437 | Systems and Methods for Distributed On-Device Learning with Data-Correlated Availability | October 2022 | August 2024 | Allow | 22 | 1 | 0 | No | No |
| 17930046 | SYSTEMS AND METHODS FOR SELECTING MACHINE LEARNING TRAINING DATA | September 2022 | December 2024 | Allow | 27 | 2 | 0 | Yes | No |
| 17893906 | EVOLVED MACHINE LEARNING MODELS | August 2022 | February 2024 | Allow | 18 | 1 | 0 | No | No |
| 17816421 | PRIVACY-PRESERVING MULTI-PARTY MACHINE LEARNING USING A DATABASE CLEANROOM | July 2022 | February 2023 | Allow | 6 | 1 | 0 | No | No |
| 17866576 | INTELLIGENT AMMUNITION CO-EVOLUTION TASK ASSIGNMENT METHOD | July 2022 | February 2026 | Allow | 43 | 1 | 0 | No | No |
| 17856521 | AUTOMATED CLOUD DATA AND TECHNOLOGY SOLUTION DELIVERY USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE MODELING | July 2022 | February 2023 | Allow | 7 | 2 | 0 | No | No |
| 17851197 | INTELLIGENT SCALING FACTORS FOR USE WITH EVOLUTIONARY STRATEGIES-BASED ARTIFICIAL INTELLIGENCE (AI) | June 2022 | February 2026 | Allow | 44 | 1 | 0 | No | No |
| 17848579 | MACHINE COMPREHENSION OF UNSTRUCTURED TEXT | June 2022 | October 2024 | Allow | 28 | 2 | 0 | Yes | No |
| 17840559 | APPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATION MANAGEMENT PLATFORM | June 2022 | July 2024 | Allow | 25 | 1 | 0 | No | No |
| 17839214 | SYSTEMS AND METHODS TO MEASURE AND ENHANCE HUMAN ENGAGEMENT AND COGNITION | June 2022 | March 2025 | Abandon | 33 | 2 | 0 | No | No |
| 17806076 | TRANSFORMER-BASED GRAPH NEURAL NETWORK TRAINED WITH THREE-DIMENSIONAL DISTANCE DATA | June 2022 | December 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17831450 | PROCESSING METHOD AND DEVICE FOR DATA OF WELL SITE TEST BASED ON KNOWLEDGE GRAPH | June 2022 | October 2023 | Allow | 16 | 0 | 0 | Yes | No |
| 17824753 | MODEL-PREDICTIVE CONTROL OF PEST PRESENCE IN HOST ENVIRONMENTS | May 2022 | February 2026 | Abandon | 45 | 1 | 0 | No | No |
| 17738053 | OPTIMIZING COGBOT RETRAINING | May 2022 | January 2026 | Allow | 45 | 2 | 0 | Yes | No |
| 17731061 | LEARNING OPERATING METHOD BASED ON FEDERATED DISTILLATION, LEARNING OPERATING SERVER, AND LEARNING OPERATING TERMINAL | April 2022 | November 2025 | Allow | 43 | 1 | 0 | No | No |
| 17771890 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND COMPUTER READABLE RECORDING MEDIUM | April 2022 | February 2026 | Allow | 45 | 1 | 0 | No | No |
| 17769326 | AUTOMATIC RECOMMENDATION OF ANALYSIS FOR DATASET | April 2022 | July 2025 | Allow | 39 | 1 | 0 | No | No |
| 17713157 | LOSSLESS TILING IN CONVOLUTION NETWORKS - RESETTING OVERLAP FACTOR TO ZERO AT SECTION BOUNDARIES | April 2022 | May 2024 | Allow | 26 | 1 | 0 | Yes | No |
| 17657723 | SPATIO-TEMPORAL CONSISTENCY EMBEDDINGS FROM MULTIPLE OBSERVED MODALITIES | April 2022 | December 2022 | Allow | 8 | 1 | 0 | No | No |
| 17700452 | LOSSLESS TILING IN CONVOLUTION NETWORKS - GRAPH METADATA GENERATION | March 2022 | January 2024 | Allow | 22 | 0 | 0 | No | No |
| 17700336 | LOSSLESS TILING IN CONVOLUTION NETWORKS - DATA FLOW LOGIC | March 2022 | November 2024 | Allow | 32 | 2 | 1 | Yes | No |
| 17687516 | LOSSLESS TILING IN CONVOLUTION NETWORKS - SECTION CUTS | March 2022 | September 2024 | Allow | 30 | 2 | 0 | Yes | No |
| 17583889 | MACHINE LEARNING ENGINE FOR DETERMINING DATA SIMILARITY | January 2022 | February 2026 | Allow | 48 | 2 | 0 | Yes | No |
| 17579780 | ASSOCIATIVE RELEVANCY KNOWLEDGE PROFILING ARCHITECTURE, SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT | January 2022 | August 2024 | Allow | 31 | 3 | 0 | Yes | No |
| 17579335 | UNSUPERVISED ANOMALY DETECTION MACHINE LEARNING FRAMEWORKS | January 2022 | November 2025 | Allow | 46 | 2 | 0 | Yes | No |
| 17561480 | SYSTEMS AND METHODS IMPLEMENTING AN INTELLIGENT OPTIMIZATION PLATFORM | December 2021 | July 2024 | Allow | 31 | 2 | 0 | Yes | No |
| 17619304 | WELLBORE TRAJECTORY CONTROL USING RESERVOIR PROPERTY PROJECTION AND OPTIMIZATION | December 2021 | September 2025 | Allow | 45 | 2 | 0 | Yes | No |
| 17550285 | DATA-CREATION ASSISTANCE APPARATUS AND DATA-CREATION ASSISTANCE METHOD | December 2021 | July 2025 | Allow | 43 | 1 | 0 | No | No |
| 17545384 | Incognito Mode for Personalized Machine-Learned Models | December 2021 | January 2024 | Allow | 25 | 1 | 0 | No | No |
| 17522921 | CUSTOMIZED PRODUCT PERFORMANCE PREDICTION METHOD BASED ON HETEROGENEOUS DATA DIFFERENCE COMPENSATION FUSION | November 2021 | January 2025 | Allow | 38 | 0 | 0 | No | No |
| 17509322 | DECISION-MAKING AGENT HAVING HIERARCHICAL STRUCTURE | October 2021 | October 2025 | Abandon | 47 | 1 | 0 | No | No |
| 17508911 | Fault monitoring method for sewage treatment process based on fuzzy width adaptive learning model | October 2021 | May 2022 | Allow | 7 | 1 | 0 | No | No |
| 17506536 | AUTOMATED CLOUD DATA AND TECHNOLOGY SOLUTION DELIVERY USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE MODELING | October 2021 | April 2022 | Allow | 6 | 1 | 0 | Yes | No |
| 17502343 | COOPERATIVELY TRAINING AND/OR USING SEPARATE INPUT AND SUBSEQUENT CONTENT NEURAL NETWORKS FOR INFORMATION RETRIEVAL | October 2021 | May 2024 | Allow | 31 | 2 | 0 | Yes | No |
| 17368493 | METHODS AND APPARATUSES FOR HIGH PERFORMANCE AND ACCURACY FIXED-POINT BATCHNORM IMPLEMENTATION | July 2021 | August 2025 | Allow | 49 | 2 | 0 | No | No |
| 17364129 | Lossless Tiling in Convolution Networks - Tiling Configuration Between Two Sections | June 2021 | April 2024 | Abandon | 33 | 1 | 0 | No | No |
| 17364110 | Lossless Tiling in Convolution Networks - Tiling Configuration for a Sequence of Sections of a Graph | June 2021 | October 2023 | Allow | 28 | 1 | 0 | No | No |
| 17419228 | USING BAYESIAN INFERENCE TO PREDICT REVIEW DECISIONS IN A MATCH GRAPH | June 2021 | September 2025 | Allow | 50 | 2 | 0 | Yes | No |
| 17345405 | SYSTEMS AND METHODS FOR MACHINE LEARNING MODEL INTERPRETATION | June 2021 | July 2022 | Allow | 13 | 2 | 0 | Yes | No |
| 17335135 | METHODS AND SYSTEMS FOR CLASSIFYING RESOURCES TO NICHE MODELS | June 2021 | August 2022 | Allow | 14 | 3 | 0 | Yes | No |
| 17322738 | MACHINE LEARNING BASED MODEL FOR DETERMINING EFFECTIVE COMMUNICATION MECHANISM WITH USERS | May 2021 | December 2025 | Allow | 55 | 3 | 0 | No | No |
| 17322674 | METHODS AND SYSTEMS FOR COMPRESSING A TRAINED NEURAL NETWORK AND FOR IMPROVING EFFICIENTLY PERFORMING COMPUTATIONS OF A COMPRESSED NEURAL NETWORK | May 2021 | October 2024 | Allow | 41 | 1 | 0 | No | No |
| 17293428 | PROCESSING DEVICE, PROCESSING METHOD, AND PROCESSING PROGRAM | May 2021 | July 2025 | Abandon | 51 | 1 | 0 | No | No |
| 17292661 | NEURAL NETWORK PROCESSING APPARATUS, NEURAL NETWORK PROCESSING METHOD, AND NEURAL NETWORK PROCESSING PROGRAM | May 2021 | December 2024 | Allow | 43 | 1 | 0 | No | No |
| 17314199 | Pill Shape Classification using Imbalanced Data with Human-Machine Hybrid Explainable Model | May 2021 | June 2025 | Allow | 50 | 2 | 0 | Yes | No |
| 17246801 | INFRASTRUCTURE REFACTORING VIA FUZZY UPSIDE DOWN REINFORCEMENT LEARNING | May 2021 | December 2024 | Allow | 43 | 1 | 0 | No | No |
| 17289947 | AN EXPLAINABLE ARTIFICIAL INTELLIGENCE MECHANISM | April 2021 | November 2024 | Allow | 43 | 2 | 0 | No | No |
| 17242392 | MEMORY MAPPING OF ACTIVATIONS FOR CONVOLUTIONAL NEURAL NETWORK EXECUTIONS | April 2021 | January 2025 | Allow | 45 | 1 | 0 | No | No |
| 17230115 | INDUSTRIAL INTERNET OF THINGS AIOPS WORKFLOWS | April 2021 | February 2025 | Allow | 46 | 2 | 0 | Yes | No |
| 17227785 | NEURAL NETWORK CIRCUIT, EDGE DEVICE AND NEURAL NETWORK OPERATION PROCESS | April 2021 | October 2024 | Allow | 42 | 1 | 0 | No | No |
| 17283502 | NEURAL-SYMBOLIC COMPUTING | April 2021 | February 2023 | Allow | 22 | 0 | 0 | No | No |
| 17219973 | METHODS AND SYSTEMS FOR PROBABILISTIC FILTERING OF CANDIDATE INTERVENTION REPRESENTATIONS | April 2021 | December 2022 | Allow | 20 | 3 | 0 | Yes | No |
| 17216680 | APPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATION MANAGEMENT PLATFORM | March 2021 | March 2022 | Allow | 11 | 2 | 0 | No | No |
| 17216651 | Lossless Tiling in Convolution Networks - Tiling Configuration | March 2021 | August 2021 | Allow | 4 | 1 | 1 | Yes | No |
| 17213952 | METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM FOR EXPANDING DATA | March 2021 | July 2024 | Allow | 40 | 1 | 0 | No | No |
| 17209576 | METHOD AND APPARATUS FOR GENERATING SHARED ENCODER | March 2021 | October 2024 | Allow | 43 | 1 | 0 | No | No |
| 17210216 | JOINT TRAINING METHOD AND APPARATUS FOR MODELS, DEVICE AND STORAGE MEDIUM | March 2021 | September 2024 | Allow | 41 | 1 | 0 | No | No |
| 17209051 | METHOD, APPARATUS, ELECTRONIC DEVICE AND STORAGE MEDIUM FOR TRAINING SEMANTIC SIMILARITY MODEL | March 2021 | August 2024 | Allow | 41 | 1 | 0 | No | No |
| 17205894 | METHOD AND APPARATUS FOR GENERATING SEMANTIC REPRESENTATION MODEL, AND STORAGE MEDIUM | March 2021 | July 2024 | Allow | 40 | 1 | 0 | No | No |
| 17204223 | METHOD, APPARATUS, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM FOR CONSTRUCTING KEY-POINT LEARNING MODEL | March 2021 | November 2024 | Abandon | 44 | 1 | 0 | No | No |
| 17200722 | SYSTEMS AND METHODS TO MEASURE AND ENHANCE HUMAN ENGAGEMENT AND COGNITION | March 2021 | May 2022 | Allow | 15 | 2 | 0 | Yes | No |
| 17186924 | LEARNING APPARATUS, METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM | February 2021 | August 2024 | Allow | 42 | 1 | 0 | No | No |
| 17180972 | Federated Learning with Dataset Sketch Commitment Based Malicious Participant Identification | February 2021 | September 2024 | Allow | 43 | 1 | 0 | Yes | No |
| 17177909 | DATA PROCESSING METHOD AND APPARATUS USING NEURAL NETWORK AND ELECTRONIC DEVICE INCLUDING THE SAME | February 2021 | May 2024 | Allow | 39 | 1 | 0 | No | No |
| 17172259 | SEMICONDUCTOR DEVICE AND ELECTRONIC DEVICE | February 2021 | September 2023 | Allow | 31 | 1 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner WONG, LUT.
With a 40.0% reversal rate, the PTAB reverses the examiner's rejections in a meaningful percentage of cases. This reversal rate is above the USPTO average, indicating that appeals have better success here than typical.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 33.3% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is above the USPTO average, suggesting that filing an appeal can be an effective strategy for prompting reconsideration.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner WONG, LUT works in Art Unit 2127 and has examined 166 patent applications in our dataset. With an allowance rate of 88.0%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 43 months.
Examiner WONG, LUT's allowance rate of 88.0% places them in the 68% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by WONG, LUT receive 1.86 office actions before reaching final disposition. This places the examiner in the 44% percentile for office actions issued. This examiner issues fewer office actions than average, which may indicate efficient prosecution or a more lenient examination style.
The median time to disposition (half-life) for applications examined by WONG, LUT is 43 months. This places the examiner in the 16% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +4.7% benefit to allowance rate for applications examined by WONG, LUT. This interview benefit is in the 29% percentile among all examiners. Recommendation: Interviews provide a below-average benefit with this examiner.
When applicants file an RCE with this examiner, 31.7% of applications are subsequently allowed. This success rate is in the 66% 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 15.9% of cases where such amendments are filed. This entry rate is in the 17% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 28.6% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 30% percentile among all examiners. Note: Pre-appeal conferences show below-average success with this examiner. Consider whether your arguments are strong enough to warrant a PAC request.
This examiner withdraws rejections or reopens prosecution in 64.3% of appeals filed. This is in the 44% percentile among all examiners. Of these withdrawals, 33.3% occur early in the appeal process (after Notice of Appeal but before Appeal Brief). Strategic Insight: This examiner shows below-average willingness to reconsider rejections during appeals. Be prepared to fully prosecute appeals if filed.
When applicants file petitions regarding this examiner's actions, 37.5% are granted (fully or in part). This grant rate is in the 26% percentile among all examiners. Strategic Note: Petitions show below-average success regarding this examiner's actions. Ensure you have a strong procedural basis before filing.
Examiner's Amendments: This examiner makes examiner's amendments in 7.8% of allowed cases (in the 91% percentile). Per MPEP § 1302.04, examiner's amendments are used to place applications in condition for allowance when only minor changes are needed. This examiner frequently uses this tool compared to other examiners, indicating a cooperative approach to getting applications allowed. Strategic Insight: If you are close to allowance but minor claim amendments are needed, this examiner may be willing to make an examiner's amendment rather than requiring another round of prosecution.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 10% 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.