Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19098005 | Profiler Tool for Assessing Impact of Shape on a Continuous and/or Categorical Response | April 2025 | August 2025 | Allow | 5 | 1 | 0 | Yes | No |
| 19067257 | THREE-DIMENSIONAL COLOR SELECTION INTERFACE | February 2025 | October 2025 | Allow | 7 | 2 | 0 | Yes | No |
| 18719200 | CONTENT PUBLISHING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM | June 2024 | July 2025 | Allow | 13 | 2 | 0 | No | No |
| 18591123 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM FOR PERSON SEARCH | February 2024 | December 2025 | Abandon | 22 | 1 | 0 | No | No |
| 18385842 | METHODS AND SYSTEMS FOR POPULATING DATA FOR CONTENT ITEM | October 2023 | February 2026 | Allow | 27 | 2 | 0 | No | No |
| 18378470 | EDITING FEATURES OF AN AVATAR | October 2023 | January 2025 | Allow | 15 | 0 | 0 | No | No |
| 18377593 | USER INTERFACE LOGICAL AND EXECUTION VIEW NAVIGATION AND SHIFTING | October 2023 | December 2024 | Allow | 14 | 1 | 0 | No | No |
| 18474115 | CUSTOMIZING USER INTERFACES BASED ON NEURODIVERSE CLASSIFICATION | September 2023 | January 2025 | Allow | 16 | 3 | 0 | Yes | No |
| 18231673 | SMART TABLE SYSTEM UTILIZING EXTENDED REALITY | August 2023 | December 2024 | Allow | 16 | 1 | 0 | Yes | No |
| 18219910 | METHOD AND SYSTEM FOR SYSTEMATIC ENHANCEMENT OF HUMAN INTERACTION CAPABILITIES VIA DYNAMIC USER INTERFACE MANAGEMENT | July 2023 | August 2024 | Allow | 13 | 3 | 0 | Yes | No |
| 18326681 | THREE-DIMENSIONAL INTERACTION SYSTEM | May 2023 | June 2025 | Allow | 25 | 2 | 0 | Yes | No |
| 18297421 | SOFTWARE PARAMETER MANAGEMENT THROUGH A UNIVERSAL INTERFACE | April 2023 | May 2025 | Allow | 25 | 2 | 0 | Yes | No |
| 18129014 | VIRTUAL WHITEBOARD PLATFORM HAVING AN INTERFACE FOR ISSUE OBJECT CREATION IN AN ISSUE TRACKING PLATFORM | March 2023 | January 2025 | Allow | 22 | 1 | 0 | Yes | No |
| 18183982 | APPARATUS AND METHOD OF CONTROLLING IMAGE DISPLAY | March 2023 | October 2024 | Allow | 19 | 1 | 0 | Yes | No |
| 18096759 | OPTIMIZATION ON AN INPUT SENSOR BASED ON SENSOR DATA | January 2023 | December 2025 | Abandon | 36 | 4 | 0 | Yes | No |
| 18151881 | ONTOLOGY-BASED TIME SERIES VISUALIZATION AND ANALYSIS | January 2023 | November 2024 | Allow | 22 | 3 | 0 | Yes | No |
| 18068994 | DEVELOPMENT, REPRESENTATION AND DISPLAY | December 2022 | December 2024 | Abandon | 23 | 2 | 0 | No | No |
| 18062810 | GROUP MESSAGE PROCESSING METHOD AND GROUP MESSAGE PROCESSING PROGRAM | December 2022 | August 2024 | Allow | 21 | 2 | 0 | Yes | No |
| 17919884 | METHODS, APPARATUS AND MACHINE-READABLE MEDIA RELATING TO DATA ANALYTICS IN A COMMUNICATIONS NETWORK | October 2022 | March 2026 | Allow | 41 | 1 | 0 | No | No |
| 17919542 | LEARNING DEVICE, LEARNING METHOD, AND LEARNING PROGRAM | October 2022 | January 2026 | Allow | 39 | 1 | 0 | Yes | No |
| 17962256 | SYSTEM AND METHOD OF GENERATING DIGITAL INK NOTES | October 2022 | June 2025 | Abandon | 33 | 4 | 0 | Yes | No |
| 17943070 | DISPLAYING ON A DISPLAY WITH AN IRREGULAR FEATURE | September 2022 | October 2024 | Allow | 25 | 3 | 0 | No | No |
| 17942014 | SYSTEMS, METHODS, AND DEVICES FOR REAL-TIME TEXTING | September 2022 | August 2024 | Allow | 23 | 2 | 0 | Yes | No |
| 17903446 | TARGET FACTORY | September 2022 | February 2026 | Allow | 41 | 1 | 0 | No | No |
| 17901261 | TESTING AND BASELINING A MACHINE LEARNING MODEL AND TEST DATA | September 2022 | February 2026 | Allow | 41 | 1 | 0 | Yes | No |
| 17901535 | SYSTEM AND METHOD FOR DYNAMICALLY CONFIGURING GRAPHICAL USER INTERFACES BASED ON TRACKING RESPONSE TO INTERFACE COMPONENTS | September 2022 | August 2024 | Allow | 24 | 3 | 0 | Yes | No |
| 17854738 | DYNAMIC OBJECT AUTO-LABELING | June 2022 | November 2025 | Allow | 41 | 1 | 0 | Yes | No |
| 17805742 | EFFICIENT MULTILABEL CLASSIFICATION BY CHAINING ORDERED CLASSIFIERS AND OPTIMIZING ON UNCORRELATED LABELS | June 2022 | January 2026 | Allow | 43 | 1 | 0 | Yes | No |
| 17805377 | REDUCING BIAS IN MACHINE LEARNING MODELS UTILIZING A FAIRNESS DEVIATION CONSTRAINT AND DECISION MATRIX | June 2022 | November 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17804828 | CLICKSTREAM PROCESSING FOR INTELLIGENT ROUTING | May 2022 | January 2025 | Abandon | 31 | 5 | 0 | Yes | No |
| 17804537 | SYSTEMS AND METHODS FOR FREQUENT MACHINE LEARNING MODEL RETRAINING AND RULE OPTIMIZATION | May 2022 | December 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17804513 | MACHINE LEARNING FOR MANAGEMENT OF POSITIONING TECHNIQUES AND RADIO FREQUENCY USAGE | May 2022 | December 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17778822 | Ensemble Coupled Assimilation System for Numerical Prediction and Method thereof | May 2022 | October 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17741909 | RANDOMIZED MOVEMENT CONTROL | May 2022 | January 2025 | Allow | 32 | 4 | 0 | Yes | No |
| 17662568 | DYNAMIC USER-INTERFACE COMPARISON BETWEEN MACHINE LEARNING OUTPUT AND TRAINING DATA | May 2022 | November 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17737938 | LIGHT SOURCE COLOR COORDINATE ESTIMATION SYSTEM AND DEEP LEARNING METHOD THEREOF | May 2022 | March 2026 | Allow | 46 | 2 | 0 | No | No |
| 17718803 | ARTIFICIAL INTELLIGENCE-BASED TECHNIQUES FOR AUTOMATED VISUAL DATA SEARCHING USING EDGE DEVICES | April 2022 | September 2025 | Allow | 41 | 1 | 0 | Yes | No |
| 17657911 | GESTURE-BASED APPLICATION INVOCATION | April 2022 | November 2024 | Allow | 32 | 4 | 0 | Yes | No |
| 17710864 | MACHINE LEARNING USING A HYBRID SERVERLESS COMPUTE ARCHITECTURE | March 2022 | January 2026 | Allow | 45 | 1 | 0 | Yes | No |
| 17695325 | EDGE-SIDE FEDERATED LEARNING FOR ANOMALY DETECTION | March 2022 | March 2025 | Allow | 36 | 1 | 0 | Yes | No |
| 17673671 | OBJECT POSITION ADJUSTMENT METHOD AND ELECTRONIC DEVICE | February 2022 | August 2024 | Allow | 30 | 3 | 0 | No | No |
| 17671092 | ADAPTIVE AND EVOLUTIONARY FEDERATED LEARNING SYSTEM | February 2022 | August 2025 | Allow | 42 | 1 | 0 | No | No |
| 17671314 | FEDERATED LEARNING PLATFORM AND METHODS FOR USING SAME | February 2022 | November 2025 | Abandon | 45 | 1 | 0 | No | No |
| 17576735 | Systems, Methods, and Graphical User Interfaces for Automatic Measurement in Augmented Reality Environments | January 2022 | March 2025 | Allow | 38 | 5 | 0 | Yes | No |
| 17559452 | MIGRATING QUANTUM SERVICES BASED ON TEMPERATURE THRESHOLDS | December 2021 | March 2025 | Allow | 38 | 0 | 0 | No | No |
| 17643515 | ENHANCED TECHNIQUES FOR BUILDING USER INTERFACES | December 2021 | January 2025 | Allow | 38 | 4 | 0 | Yes | No |
| 17539828 | DETECTING CATEGORY-SPECIFIC BIAS USING OVERFITTED MACHINE LEARNING MODELS | December 2021 | May 2025 | Allow | 41 | 1 | 0 | Yes | No |
| 17609408 | ROAD TRAFFIC JAM EARLY WARNING METHOD AND SYSTEM | November 2021 | July 2025 | Abandon | 45 | 1 | 0 | No | No |
| 17511517 | METHODS, APPARATUSES, AND SYSTEMS FOR UPDATING SERVICE MODEL BASED ON PRIVACY PROTECTION | October 2021 | September 2025 | Abandon | 47 | 1 | 0 | No | No |
| 17511280 | CHARACTER EDITING ON A PHYSICAL DEVICE VIA INTERACTION WITH A VIRTUAL DEVICE USER INTERFACE | October 2021 | October 2025 | Allow | 47 | 3 | 0 | Yes | Yes |
| 17604202 | ELECTRONIC DEVICE AND OPERATION METHOD OF COLLECTING DATA FROM MULTIPLE DEVICES FOR GENERATING AN ARTIFICIAL INTELLIGENCE MODEL | October 2021 | April 2025 | Allow | 42 | 1 | 0 | No | No |
| 17483349 | System and Method for Interactive Visualization of Placement of Objects in an Electronic Design | September 2021 | December 2024 | Allow | 38 | 3 | 0 | Yes | No |
| 17445888 | VECTOR PROCESSING OF DECISION TREES TO FORM INFERENCES | August 2021 | August 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17395118 | FEDERATED LEARNING FOR ANOMALY DETECTION | August 2021 | March 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17382749 | ARCHITECTURE ESTIMATION DEVICE, ARCHITECTURE ESTIMATION METHOD, AND COMPUTER READABLE MEDIUM | July 2021 | July 2025 | Allow | 47 | 1 | 0 | Yes | No |
| 17378437 | UNCERTAINTY AWARE PARAMETER PROVISION FOR A VARIATIONAL QUANTUM ALGORITHM | July 2021 | August 2025 | Allow | 49 | 2 | 0 | Yes | No |
| 17357480 | ORDERING COLLABORATIVE ACTIONS IN A GRAPHICAL USER INTERFACE | June 2021 | April 2025 | Allow | 46 | 4 | 0 | No | Yes |
| 17325082 | DECISION RECOMMENDATION VIA CAUSAL FEATURE DISPLAY | May 2021 | February 2025 | Allow | 45 | 2 | 0 | No | No |
| 17302481 | CROSS-ENTITY SIMILARITY DETERMINATIONS USING MACHINE LEARNING FRAMEWORKS | May 2021 | February 2025 | Allow | 46 | 1 | 0 | Yes | No |
| 17239425 | TECHNIQUES FOR MANIPULATING COMPUTER-GENERATED OBJECTS IN A COMPUTER GRAPHICS EDITOR OR ENVIRONMENT | April 2021 | January 2025 | Allow | 45 | 5 | 0 | Yes | Yes |
| 17231639 | COGNITIVE RECOMMENDATION OF COMPUTING ENVIRONMENT ATTRIBUTES | April 2021 | August 2024 | Allow | 40 | 1 | 0 | Yes | No |
| 17231757 | PREDICTING A STATE OF A COMPUTER-CONTROLLED ENTITY | April 2021 | November 2025 | Allow | 55 | 3 | 0 | No | No |
| 17249620 | SURROUNDING ASSESSMENT FOR HEAT MAP VISUALIZATION | March 2021 | March 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17133949 | PROCESSING METHOD AND APPARATUS OF NEURAL NETWORK MODEL | December 2020 | November 2024 | Abandon | 47 | 1 | 0 | No | No |
| 17255824 | METHOD OF MODELLING FOR CHECKING THE RESULTS PROVIDED BY AN ARTIFICIAL NEURAL NETWORK AND OTHER ASSOCIATED METHODS | December 2020 | November 2024 | Abandon | 47 | 1 | 0 | No | No |
| 17127404 | DETERMINING AND EXECUTING PROACTIVE DELIVERY ACTIONS USING ARTIFICIAL INTELLIGENCE | December 2020 | October 2025 | Allow | 58 | 4 | 0 | Yes | No |
| 17079882 | QUANTIFYING MACHINE LEARNING MODEL UNCERTAINTY | October 2020 | November 2025 | Allow | 60 | 4 | 0 | Yes | No |
| 17050773 | OPTIMIZATION DEVICE, OPTIMIZATION METHOD, AND PROGRAM | October 2020 | August 2025 | Abandon | 58 | 3 | 0 | No | No |
| 17044276 | INFERENCE COMPUTING APPARATUS, MODEL TRAINING APPARATUS, INFERENCE COMPUTING SYSTEM | September 2020 | November 2024 | Allow | 49 | 2 | 0 | No | No |
| 17030576 | SYSTEMS AND METHODS TO GENERATE SAMPLES FOR MACHINE LEARNING USING QUANTUM COMPUTING | September 2020 | September 2024 | Allow | 48 | 2 | 0 | Yes | No |
| 17030219 | Devices, Methods, and Graphical User Interfaces for Interacting with Three-Dimensional Environments | September 2020 | April 2024 | Allow | 43 | 4 | 0 | Yes | No |
| 17023766 | DATA GENERATION AND ANNOTATION FOR MACHINE LEARNING | September 2020 | December 2024 | Allow | 51 | 3 | 0 | Yes | No |
| 17016340 | INTERACTION BETWEEN USER-INTERFACE AND MASTER CONTROLLER | September 2020 | February 2025 | Allow | 53 | 3 | 0 | No | No |
| 16866380 | MESSAGE APPLICATION IMPROVEMENT FOR RECALLING ONE TO MANY PRIVATE CONVERSATIONS | May 2020 | February 2025 | Allow | 57 | 5 | 0 | No | Yes |
| 16697620 | INTERACTIVE MACHINE LEARNING | November 2019 | August 2024 | Allow | 57 | 3 | 0 | Yes | No |
| 15766905 | SYSTEM AND METHOD FOR PROVIDING A VISUALIZATION OF SAFETY EVENTS OF A PROCESS CONTROL SYSTEM OVER TIME | April 2018 | July 2024 | Allow | 60 | 8 | 0 | Yes | Yes |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner LU, HWEI-MIN.
With a 50.0% 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, 60.0% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the top 25% across the USPTO, indicating that filing appeals is particularly effective here. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
✓ 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 LU, HWEI-MIN works in Art Unit 2142 and has examined 32 patent applications in our dataset. With an allowance rate of 84.4%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 47 months.
Examiner LU, HWEI-MIN's allowance rate of 84.4% places them in the 59% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by LU, HWEI-MIN receive 2.53 office actions before reaching final disposition. This places the examiner in the 74% 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 LU, HWEI-MIN is 47 months. This places the examiner in the 9% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +38.5% benefit to allowance rate for applications examined by LU, HWEI-MIN. This interview benefit is in the 86% 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, 32.3% of applications are subsequently allowed. This success rate is in the 68% 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 7.1% of cases where such amendments are filed. This entry rate is in the 7% 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, 0.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 6% percentile among all examiners. Note: Pre-appeal conferences show limited success with this examiner compared to others. While still worth considering, be prepared to proceed with a full appeal brief if the PAC does not result in favorable action.
This examiner withdraws rejections or reopens prosecution in 55.6% of appeals filed. This is in the 27% percentile among all examiners. 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, 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 10% 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.