Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19275890 | EVENT PREDICTION METHOD BASED ON SATELLITE ORBIT THREAT DOMAIN KNOWLEDGE GRAPH | July 2025 | February 2026 | Allow | 6 | 1 | 0 | No | No |
| 19223082 | METHOD FOR EVALUATING DRIVING RISK LEVEL IN TUNNEL BASED ON VEHICLE BUS DATA AND SYSTEM THEREFOR | May 2025 | December 2025 | Allow | 7 | 1 | 0 | No | No |
| 19080814 | ONTOLOGY-DRIVEN METHOD AND SYSTEM FOR CONSTRUCTING FISH KNOWLEDGE GRAPH IN TARGET REGION | March 2025 | September 2025 | Allow | 6 | 1 | 0 | No | No |
| 19018794 | Smart Device System | January 2025 | November 2025 | Abandon | 10 | 1 | 0 | No | No |
| 18898509 | COPILOT IMPLEMENTATION: TRAINING AN EXPANSION MACHINE LEARNING TOOL | September 2024 | March 2026 | Abandon | 18 | 2 | 0 | Yes | Yes |
| 18812897 | ENTROPY-BASED PREEMPTIVE FALSE POSITIVE MITIGATION | August 2024 | April 2025 | Allow | 8 | 1 | 0 | Yes | No |
| 18740464 | SYSTEMS AND METHODS FOR TRAINING MACHINE LEARNING MODELS WITH USER-SPECIFIC KNOWLEDGE GRAPHS TO PREDICT OUTCOMES | June 2024 | September 2025 | Allow | 15 | 3 | 0 | Yes | No |
| 18669203 | SYSTEMS AND METHODS FOR FACILITATING NETWORK CONTENT GENERATION VIA A DYNAMIC MULTI-MODEL APPROACH | May 2024 | December 2025 | Allow | 18 | 3 | 0 | Yes | No |
| 18416549 | SYSTEM AND METHOD FOR MESSAGE REACTION ANALYSIS | January 2024 | July 2025 | Allow | 18 | 3 | 0 | Yes | No |
| 18532795 | INCREMENTAL PRECISION NETWORKS USING RESIDUAL INFERENCE AND FINE-GRAIN QUANTIZATION | December 2023 | September 2024 | Allow | 9 | 1 | 0 | No | No |
| 18497823 | A SYSTEM AND METHOD FOR CREATING A KNOWLEDGE GRAPH | October 2023 | April 2025 | Allow | 18 | 2 | 0 | Yes | No |
| 18375669 | METHOD AND APPARATUS FOR ANALYSIS OF PRESERVATION REQUIREMENTS USING A DUAL PREDICTOR ARCHITECTURE | October 2023 | November 2024 | Allow | 14 | 3 | 0 | Yes | No |
| 18240799 | Systems and Methods for Communication Efficient Distributed Mean Estimation | August 2023 | September 2024 | Allow | 13 | 1 | 0 | No | No |
| 18457255 | SYSTEMS AND METHODS FOR REFINING MACHINE LEARNING MODELS BASED ON USER RESPONSES TO PROMPTS | August 2023 | November 2025 | Allow | 27 | 5 | 0 | Yes | No |
| 18232635 | PROCESSING LOOPS IN COMPUTATIONAL GRAPHS | August 2023 | October 2024 | Allow | 14 | 1 | 0 | No | No |
| 18199865 | METHOD AND SYSTEM FOR GENERATING ONE OR MORE CONDITIONALLY DEPENDENT DATA ENTRIES | May 2023 | May 2025 | Allow | 24 | 3 | 0 | Yes | No |
| 18120434 | METHOD FOR CONSTRUCTING DESIGN CONCEPT GENERATION NETWORK (DCGN) AND METHOD FOR AUTOMATICALLY GENERATING CONCEPTUAL SCHEME | March 2023 | March 2026 | Allow | 36 | 1 | 0 | No | No |
| 18115954 | METHODS AND COMPUTER PROGRAM PRODUCTS FOR CLUSTERING RECORDS USING IMPERFECT RULES | March 2023 | February 2024 | Allow | 11 | 1 | 0 | No | No |
| 18107577 | SYSTEMS AND METHODS FOR DIVERSITY-ENHANCED ADAPTIVE EXPERIMENTATION IN A MACHINE LEARNING-BASED FORMULATION PLATFORM | February 2023 | May 2024 | Allow | 15 | 2 | 0 | Yes | No |
| 18150701 | MODELING FOR COMPLEX OUTCOMES USING CLUSTERING AND MACHINE LEARNING ALGORITHMS | January 2023 | April 2025 | Abandon | 27 | 1 | 0 | No | No |
| 18091654 | NETWORK OF INTELLIGENT MACHINES | December 2022 | March 2026 | Allow | 38 | 1 | 0 | No | No |
| 18003695 | Semantic-Based Causal Event Probability Analysis Method, Apparatus and System | December 2022 | October 2024 | Abandon | 22 | 3 | 0 | No | No |
| 18060414 | INCREMENTAL PRECISION NETWORKS USING RESIDUAL INFERENCE AND FINE-GRAIN QUANTIZATION | November 2022 | September 2023 | Allow | 9 | 0 | 0 | No | No |
| 17993777 | SYSTEM AND METHOD FOR ONLINE ANALYSIS | November 2022 | July 2023 | Allow | 8 | 1 | 0 | Yes | No |
| 17969816 | Machine Learning For Intent Matching Engine | October 2022 | January 2025 | Allow | 27 | 4 | 0 | Yes | No |
| 17968591 | DATA PATTERN ANALYSIS USING OPTIMIZED DETERMINISTIC FINITE AUTOMATON | October 2022 | June 2025 | Allow | 32 | 3 | 0 | Yes | No |
| 17915660 | LEARNING DEVICE, PERISHABLE PRODUCT CONTAINING DEVICE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM | September 2022 | June 2024 | Abandon | 21 | 4 | 0 | Yes | No |
| 17859654 | INFORMATION PROCESSING DEVICE FOR MACHINE LEARNING PRIORITIZATION | July 2022 | December 2023 | Abandon | 17 | 2 | 0 | Yes | No |
| 17859684 | TIME-BASED ENSEMBLE MACHINE LEARNING MODEL | July 2022 | March 2024 | Allow | 20 | 2 | 0 | Yes | No |
| 17833651 | METHOD OF AND SYSTEM FOR IDENTIFYING AND ENUMERATING CROSS-BODY DEGRADATIONS | June 2022 | May 2024 | Allow | 24 | 2 | 0 | Yes | No |
| 17661316 | DIRECTED TRAJECTORIES THROUGH COMMUNICATION DECISION TREE USING ITERATIVE ARTIFICIAL INTELLIGENCE | April 2022 | May 2023 | Allow | 12 | 1 | 0 | No | No |
| 17706341 | Graph Database Implemented Knowledge Mesh | March 2022 | July 2023 | Allow | 16 | 3 | 0 | Yes | No |
| 17701778 | LEARNING NEURAL NETWORK STRUCTURE | March 2022 | October 2023 | Allow | 18 | 1 | 0 | Yes | No |
| 17687809 | MOLECULAR STRUCTURE ACQUISITION METHOD AND APPARATUS, ELECTRONIC DEVICE AND STORAGE MEDIUM | March 2022 | January 2026 | Allow | 47 | 1 | 0 | No | No |
| 17562001 | METHOD FOR REAL TIME OPTIMIZATION AND PARALLEL COMPUTING OF MODEL PREDICTION CONTROL BASED ON COMPUTING CHART | December 2021 | July 2023 | Allow | 18 | 0 | 0 | No | No |
| 17560000 | SYSTEMS AND METHODS FOR DEEP LEARNING WITH SMALL TRAINING SETS | December 2021 | August 2022 | Allow | 7 | 1 | 0 | Yes | No |
| 17555411 | System and Method for Identifying Substitutable Entities in Procedural Instructions | December 2021 | August 2025 | Allow | 44 | 1 | 0 | No | No |
| 17544213 | METHOD FOR PREDICTING DIOXIN EMISSION CONCENTRATION | December 2021 | December 2025 | Abandon | 48 | 2 | 0 | No | No |
| 17540369 | SYSTEMS AND METHODS FOR CLASSIFYING MEDIA ACCORDING TO USER NEGATIVE PROPENSITIES | December 2021 | May 2023 | Allow | 18 | 1 | 0 | Yes | No |
| 17540800 | METHOD AND SYSTEM FOR IMPLEMENTING MACHINE LEARNING CLASSIFICATIONS | December 2021 | December 2023 | Allow | 25 | 1 | 0 | Yes | No |
| 17532478 | OPTIMIZATION OF INVESTIGATOR AND SITE LOCATION IDENTIFICATION | November 2021 | June 2024 | Allow | 30 | 2 | 0 | Yes | No |
| 17454976 | COGNITIVE DISAMBIGUATION FOR PROBLEM-SOLVING TASKS INVOLVING A POWER GRID USING RELEVANCE FEEDBACK | November 2021 | March 2025 | Allow | 40 | 4 | 0 | No | No |
| 17517374 | Detecting Human Input Activity in a Cognitive Environment Using Wearable Inertia and Audio Sensors | November 2021 | March 2026 | Allow | 52 | 2 | 0 | Yes | No |
| 17514063 | AGENT ASSISTED MODEL DEVELOPMENT | October 2021 | January 2025 | Allow | 38 | 0 | 0 | No | No |
| 17607385 | COMPUTATIONALLY EFFICIENT IMPLEMENTATION OF ANALOG NEURON | October 2021 | January 2026 | Abandon | 50 | 2 | 0 | No | No |
| 17502794 | Systems and Methods for Communication Efficient Distributed Mean Estimation | October 2021 | May 2023 | Allow | 19 | 1 | 0 | No | No |
| 17501330 | SYSTEM AND METHOD FOR PREDICTIVE MODELING FOR ENTITLEMENT DIFFUSION AND ROLE EVOLUTION IN IDENTITY MANAGEMENT ARTIFICIAL INTELLIGENCE SYSTEMS USING NETWORK IDENTITY GRAPHS | October 2021 | June 2023 | Allow | 20 | 1 | 0 | No | No |
| 17498248 | QUANTUM ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN A NEXT GENERATION MOBILE NETWORK | October 2021 | March 2026 | Allow | 53 | 3 | 0 | Yes | No |
| 17493492 | CIRCUIT FOR HANDLING PROCESSING WITH OUTLIERS | October 2021 | October 2025 | Allow | 49 | 1 | 0 | Yes | No |
| 17492643 | SYSTEM AND METHOD FOR CONVERTING MACHINE LEARNING ALGORITHM, AND ELECTRONIC DEVICE | October 2021 | November 2024 | Abandon | 38 | 2 | 0 | No | No |
| 17483093 | METHOD TO INCREASE DISCOVERY PIPELINE HIT RATES AND LAB TO FIELD TRANSLATION | September 2021 | April 2022 | Allow | 7 | 2 | 0 | Yes | No |
| 17477514 | Method and Apparatus for Cross Correlation | September 2021 | May 2025 | Abandon | 44 | 1 | 0 | No | No |
| 17462186 | RELIABILITY EVALUATION DEVICE AND RELIABILITY EVALUATION METHOD | August 2021 | August 2025 | Abandon | 48 | 2 | 0 | No | No |
| 17461979 | FEDERATED LEARNING FOR IMPROVING MATCHING EFFICIENCY | August 2021 | August 2025 | Allow | 48 | 1 | 0 | No | No |
| 17412630 | RETRAINING DOCUMENT-TAGGING MACHINE-LEARNED MODEL BASED ON ANONYMIZED DATA | August 2021 | October 2025 | Allow | 50 | 2 | 0 | Yes | No |
| 17412970 | SYSTEM AND METHOD FOR APPROXIMATING NUMERICAL FEATURES VIA CUBIC SPLINES AND APPLICATIONS THEREOF | August 2021 | December 2025 | Allow | 52 | 3 | 0 | No | No |
| 17423075 | AGENT JOINING DEVICE, METHOD, AND PROGRAM | July 2021 | November 2025 | Abandon | 52 | 2 | 0 | No | No |
| 17305125 | SYSTEM METHOD AND APPARATUS FOR AI-BASED ADAPTIVE CONTROL OF HYDROLOGY MANAGEMENT FOR BASIN RIVERS | June 2021 | January 2022 | Allow | 7 | 1 | 1 | Yes | No |
| 17364135 | METHOD AND SYSTEM USING MACHINE LEARNING FOR WELL OPERATIONS AND LOGISTICS | June 2021 | September 2025 | Allow | 50 | 3 | 0 | Yes | No |
| 17362607 | VISUAL QUESTION ANSWERING WITH KNOWLEDGE GRAPHS | June 2021 | February 2026 | Allow | 55 | 3 | 0 | Yes | No |
| 17361316 | SYSTEM AND METHOD FOR COMPACT TREE REPRESENTATION FOR MACHINE LEARNING | June 2021 | March 2025 | Allow | 45 | 2 | 0 | Yes | No |
| 17337053 | SYSTEM AND METHOD FOR EFFICIENT GENERATION OF MACHINE-LEARNING MODELS | June 2021 | February 2025 | Allow | 45 | 4 | 0 | Yes | No |
| 17333251 | SYSTEM AND METHODS FOR MULTI-LANGUAGE ABSTRACT MODEL CREATION FOR DIGITAL ENVIRONMENT SIMULATIONS | May 2021 | January 2023 | Allow | 20 | 1 | 0 | No | No |
| 17319210 | SYSTEM, METHOD, AND RECORDING MEDIUM FOR DISTRIBUTED PROBABILISTIC EIDETIC QUERYING, ROLLBACK, AND REPLAY | May 2021 | January 2024 | Allow | 32 | 8 | 0 | No | No |
| 17308267 | DIGITAL TRANSACTION LEDGER WITH DNA-RELATED LEDGER PARAMETER | May 2021 | October 2024 | Allow | 41 | 3 | 0 | Yes | No |
| 17246201 | METHODS, APPARATUSES, AND COMPUTING DEVICES FOR TRAININGS OF LEARNING MODELS | April 2021 | July 2022 | Allow | 15 | 3 | 0 | Yes | No |
| 17244006 | METHOD AND APPARATUS WITH NEURAL NETWORK INFERENCE OPTIMIZATION IMPLEMENTATION | April 2021 | November 2025 | Allow | 54 | 2 | 0 | Yes | No |
| 17227010 | SYSTEM AND METHOD FOR ADDRESSING OVERFITTING IN A NEURAL NETWORK | April 2021 | July 2023 | Allow | 27 | 1 | 0 | No | No |
| 17208436 | SYSTEMS AND METHODS FOR NETWORKS OF TIME SERIES | March 2021 | April 2022 | Allow | 13 | 3 | 0 | Yes | No |
| 17208316 | SYSTEMS AND METHODS FOR NETWORKS OF TIME SERIES | March 2021 | June 2025 | Abandon | 51 | 2 | 0 | Yes | No |
| 17276094 | METHOD AND SYSTEM FOR MULTIRAIL ENCODING OF QUANTUM BITS | March 2021 | February 2025 | Allow | 47 | 1 | 0 | Yes | No |
| 17198259 | REINFORCEMENT LEARNING SYSTEM AND TRAINING METHOD | March 2021 | April 2025 | Abandon | 49 | 4 | 0 | Yes | No |
| 17192756 | ELECTRONIC DEVICE AND METHOD FOR TURNOVER RATE PREDICTION | March 2021 | February 2026 | Abandon | 59 | 2 | 0 | No | No |
| 17188112 | PROCESSING SEQUENTIAL INTERACTION DATA | March 2021 | December 2022 | Allow | 21 | 1 | 0 | No | No |
| 17164491 | METHODS AND SYSTEMS FOR CONFIRMING AN ADVISORY INTERACTION WITH AN ARTIFICIAL INTELLIGENCE PLATFORM | February 2021 | May 2025 | Allow | 51 | 2 | 0 | Yes | No |
| 17155665 | PREDICTION CIRCUITRY CONFIGURED TO PREDICT SPECULATIVE ACTION BASED ON HIT-TO-TRAIN RATIO OR BASED ON TRAIN COUNTER AND HIT COUNTER | January 2021 | June 2025 | Allow | 52 | 1 | 0 | No | No |
| 17152262 | FIELD DATA MONITORING DEVICE, FIELD DATA MONITORING METHOD, AND FIELD DATA DISPLAY DEVICE | January 2021 | September 2025 | Abandon | 56 | 2 | 0 | No | No |
| 17143029 | SCALABLE NEUTRAL ATOM BASED QUANTUM COMPUTING | January 2021 | May 2025 | Allow | 52 | 1 | 0 | Yes | No |
| 17135396 | METHOD AND DEVICE FOR PERFORMING BEHAVIOR PREDICTION BY USING EXPLAINABLE SELF-FOCUSED ATTENTION | December 2020 | May 2023 | Abandon | 29 | 6 | 0 | Yes | No |
| 17126818 | GENERATION OF A BAYESIAN NETWORK | December 2020 | August 2023 | Allow | 32 | 2 | 0 | No | No |
| 17117925 | METHOD AND SYSTEM FOR DISTRIBUTED TRAINING USING SYNTHETIC GRADIENTS | December 2020 | March 2025 | Abandon | 51 | 1 | 0 | No | No |
| 17118139 | ALTERNATIVE SOFT LABEL GENERATION | December 2020 | January 2025 | Allow | 50 | 3 | 0 | Yes | No |
| 17116811 | Probabilistic Accumulation Approach to Assess Primary Uncertainty In Catastrophe Models | December 2020 | October 2024 | Allow | 47 | 1 | 0 | Yes | No |
| 17113814 | SYSTEMS AND METHODS FOR SOLVING UNRESTRICTED INCREMENTAL CONSTRAINT PROBLEMS | December 2020 | October 2023 | Allow | 34 | 2 | 0 | Yes | No |
| 17101406 | SYSTEM AND METHOD FOR PREDICTIVE MODELING FOR ENTITLEMENT DIFFUSION AND ROLE EVOLUTION IN IDENTITY MANAGEMENT ARTIFICIAL INTELLIGENCE SYSTEMS USING NETWORK IDENTITY GRAPHS | November 2020 | August 2021 | Allow | 9 | 1 | 0 | Yes | No |
| 17080596 | APPARATUS, SYSTEMS, AND METHODS FOR CROWDSOURCING DOMAIN SPECIFIC INTELLIGENCE | October 2020 | January 2026 | Allow | 60 | 5 | 0 | Yes | No |
| 17049651 | SYSTEM AND METHOD FOR EMULATING QUANTIZATION NOISE FOR A NEURAL NETWORK | October 2020 | February 2024 | Allow | 40 | 1 | 0 | No | No |
| 17049642 | VISUAL QUESTION ANSWERING USING ON-IMAGE ANNOTATIONS | October 2020 | April 2024 | Abandon | 42 | 1 | 0 | No | No |
| 17032050 | METHODS AND SYSTEMS FOR CONFIRMING AN ADVISORY INTERACTION WITH AN ARTIFICIAL INTELLIGENCE PLATFORM | September 2020 | May 2024 | Allow | 43 | 1 | 0 | Yes | No |
| 17030359 | USER-TAILORED RECOMMENDATIONS | September 2020 | May 2023 | Abandon | 31 | 1 | 0 | No | No |
| 17022771 | METHODS AND SYSTEMS FOR OBSERVATION PREDICTION IN AUTONOMOUS VEHICLES | September 2020 | December 2024 | Allow | 51 | 1 | 0 | No | No |
| 17011151 | DYNAMIC ONTOLOGY CLASSIFICATION SYSTEM | September 2020 | October 2024 | Allow | 49 | 2 | 0 | Yes | Yes |
| 17006002 | SEPARATION DISTANCE BETWEEN FEATURE VECTORS FOR SEMI-SUPERVISED HOTSPOT DETECTION AND CLASSIFICATION | August 2020 | April 2025 | Abandon | 55 | 2 | 0 | Yes | No |
| 16976063 | Mission-Critical AI Processor with Multi-Layer Fault Tolerance Support | August 2020 | October 2024 | Abandon | 50 | 1 | 0 | No | No |
| 17000973 | METHOD OF AND SYSTEM FOR IDENTIFYING AND ENUMERATING CROSS-BODY DEGRADATIONS | August 2020 | April 2022 | Allow | 19 | 4 | 0 | Yes | No |
| 16986974 | PROCESSING LOOPS IN COMPUTATIONAL GRAPHS | August 2020 | May 2023 | Allow | 33 | 1 | 0 | No | No |
| 16983775 | APPARATUSES, SYSTEMS AND METHODS FOR GENERATING A BASE-LINE PROBABLE ROOF LOSS CONFIDENCE SCORE | August 2020 | September 2025 | Allow | 60 | 4 | 0 | Yes | No |
| 16941615 | TECHNOLOGY FOR OPTIMIZING ARTIFICIAL INTELLIGENCE PIPELINES | July 2020 | August 2024 | Abandon | 48 | 1 | 0 | No | No |
| 16938416 | CATEGORICAL INPUT MACHINE LEARNING MODELS | July 2020 | June 2025 | Allow | 58 | 3 | 0 | Yes | No |
| 16936328 | MACHINE LEARNING BASED HEALTH OUTCOME RECOMMENDATION ENGINE | July 2020 | March 2024 | Abandon | 43 | 1 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner FIGUEROA, KEVIN W.
With a 21.1% reversal rate, the PTAB affirms the examiner's rejections in the vast majority of cases. This reversal rate is below the USPTO average, indicating that appeals face more challenges 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, 28.9% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is below the USPTO average, suggesting that filing an appeal has limited effectiveness in prompting favorable reconsideration.
⚠ Appeals to PTAB face challenges. Ensure your case has strong merit before committing to full Board review.
⚠ Filing a Notice of Appeal shows limited benefit. Consider other strategies like interviews or amendments before appealing.
Examiner FIGUEROA, KEVIN W works in Art Unit 2124 and has examined 301 patent applications in our dataset. With an allowance rate of 71.1%, this examiner has a below-average tendency to allow applications. Applications typically reach final disposition in approximately 50 months.
Examiner FIGUEROA, KEVIN W's allowance rate of 71.1% places them in the 34% percentile among all USPTO examiners. This examiner has a below-average tendency to allow applications.
On average, applications examined by FIGUEROA, KEVIN W receive 2.99 office actions before reaching final disposition. This places the examiner in the 86% percentile for office actions issued. This examiner issues more office actions than most examiners, which may indicate thorough examination or difficulty in reaching agreement with applicants.
The median time to disposition (half-life) for applications examined by FIGUEROA, KEVIN W is 50 months. This places the examiner in the 5% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +26.4% benefit to allowance rate for applications examined by FIGUEROA, KEVIN W. This interview benefit is in the 73% percentile among all examiners. Recommendation: Interviews provide an above-average benefit with this examiner and are worth considering.
When applicants file an RCE with this examiner, 22.9% of applications are subsequently allowed. This success rate is in the 30% percentile among all examiners. Strategic Insight: RCEs show below-average effectiveness with this examiner. Carefully evaluate whether an RCE or continuation is the better strategy.
This examiner enters after-final amendments leading to allowance in 19.8% of cases where such amendments are filed. This entry rate is in the 24% 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, 54.5% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 47% 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 54.8% of appeals filed. This is in the 26% percentile among all examiners. Of these withdrawals, 21.7% 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, 30.5% are granted (fully or in part). This grant rate is in the 18% percentile among all examiners. Strategic Note: Petitions are rarely granted regarding this examiner's actions compared to other examiners. Ensure you have a strong procedural basis before filing a petition, as the Technology Center Director typically upholds this examiner's decisions.
Examiner's Amendments: This examiner makes examiner's amendments in 0.3% of allowed cases (in the 56% percentile). This examiner makes examiner's amendments more often than average to place applications in condition for allowance (MPEP § 1302.04).
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.