Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18631372 | SYSTEM FOR ENABLING WORKSPACE SHARING | April 2024 | February 2025 | Allow | 10 | 1 | 0 | No | No |
| 18610490 | PORTABLE TERMINAL DEVICE | March 2024 | July 2025 | Allow | 16 | 1 | 0 | Yes | No |
| 18584899 | LIVE LOCATION SHARING | February 2024 | March 2025 | Allow | 12 | 1 | 0 | No | No |
| 18436884 | SYSTEM AND METHOD FOR DYNAMIC PROFILE PHOTOS | February 2024 | April 2025 | Allow | 14 | 1 | 0 | No | No |
| 18413623 | GENERATING A VIRTUAL REALITY LEARNING ENVIRONMENT | January 2024 | January 2025 | Allow | 12 | 1 | 0 | No | No |
| 18515454 | IMAGE BASED PAIRING SYSTEM | November 2023 | March 2026 | Abandon | 27 | 3 | 0 | No | No |
| 18513488 | SURFACING RELEVANT TOPICS IN A GROUP-BASED COMMUNICATION SYSTEM | November 2023 | June 2025 | Allow | 19 | 2 | 0 | Yes | No |
| 18127955 | PATIENT SUPPORT SYSTEMS AND METHODS FOR ASSISTING CAREGIVERS WITH PATIENT CARE | March 2023 | June 2025 | Allow | 27 | 1 | 1 | No | No |
| 18152691 | COMPUTER VISION TO DEPICT USER INPUT TO ONE DEVICE AT ANOTHER DEVICE | January 2023 | April 2025 | Allow | 27 | 1 | 0 | No | No |
| 18148980 | PROVIDING SHARED CONTENT COLLECTIONS WITHIN A MESSAGING SYSTEM | December 2022 | July 2025 | Allow | 31 | 3 | 0 | No | No |
| 18147340 | CONTENT-BASED MENUS FOR TABBED USER INTERFACE | December 2022 | October 2025 | Allow | 34 | 2 | 0 | Yes | No |
| 17930507 | GENERATING AND MODIFYING A COLLECTION CONTENT ITEM FOR ORGANIZING AND PRESENTING CONTENT ITEMS | September 2022 | June 2025 | Allow | 33 | 4 | 0 | Yes | No |
| 17902638 | DEFINING AN INTERACTIVE SESSION THAT ANALYZES USER INPUT PROVIDED BY A PARTICIPANT | September 2022 | November 2025 | Abandon | 39 | 1 | 0 | No | No |
| 17896590 | CONTRASTIVE TIME SERIES REPRESENTATION LEARNING VIA META-LEARNING | August 2022 | February 2026 | Allow | 41 | 1 | 0 | Yes | No |
| 17893493 | Minimized Bandwidth Requirements for Transmitting Mobile HMD Gaze Data | August 2022 | June 2025 | Abandon | 34 | 4 | 0 | Yes | No |
| 17816337 | INTERACTIVE CHART USING A DATA PROCESSING PACKAGE | July 2022 | December 2024 | Allow | 28 | 3 | 0 | No | No |
| 17810201 | QUANTUM GATE PROTOCOL FOR THE EXECUTION OF SPIN LOCKING ONTO SUPERCONDUCTING QUBIT ARCHITECTURES | June 2022 | October 2025 | Allow | 40 | 0 | 0 | No | No |
| 17835288 | APPLICATION CONTROL METHOD AND ELECTRONIC DEVICE | June 2022 | May 2025 | Abandon | 35 | 4 | 0 | No | No |
| 17723342 | APPLICATION RATING AND FEEDBACK | April 2022 | October 2025 | Abandon | 42 | 6 | 0 | Yes | No |
| 17692918 | NETWORK DATA OBJECT PROCESSING SYSTEM WITH INTERDEPENDENCE IDENTIFICATION ENGINE AND MULTI-CAROUSEL INTERFACE | March 2022 | July 2024 | Allow | 29 | 2 | 1 | Yes | No |
| 17691069 | APPARATUS AND PARTICULARLY COMPUTER-IMPLEMENTED METHOD FOR NON-DETERMINISTIC TECHNICAL SYSTEMS | March 2022 | February 2026 | Allow | 47 | 2 | 0 | No | No |
| 17688659 | GRADIENT DESCENT TRAINING FOR DEFENSIBLE ARTIFICIAL INTELLIGENCE | March 2022 | May 2025 | Allow | 38 | 1 | 0 | No | No |
| 17675442 | SYSTEMS AND METHODS FOR SAMPLE EFFICIENT TRAINING OF MACHINE LEARNING MODELS | February 2022 | March 2026 | Allow | 48 | 2 | 0 | Yes | No |
| 17670736 | MACHINE LEARNING SYSTEMS AND METHODS FOR POURBAIX DIAGRAM DESCRIPTOR-BASED PREDICTION OF ELETROCHEMICAL FIGURES OF MERIT | February 2022 | December 2025 | Abandon | 46 | 1 | 0 | No | No |
| 17583280 | Guided Collaborative Viewing of Navigable Image Content | January 2022 | February 2025 | Allow | 37 | 5 | 0 | No | No |
| 17644488 | SYSTEMS AND METHODS FOR IMPLEMENTING ALL-TO-ALL CONNECTIVITY IN GATE-BASED QUANTUM COMPUTERS USING NEAREST-NEIGHBOR INTERACTIONS | December 2021 | August 2025 | Allow | 44 | 0 | 0 | No | No |
| 17541823 | ACTIVE LEARNING DRIFT ANALYSIS AND TRAINING | December 2021 | December 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17612768 | COUPLING MULTIPLE ARTIFICIALLY LEARNING UNITS WITH A PROJECTION LEVEL | November 2021 | March 2026 | Allow | 52 | 1 | 0 | No | No |
| 17519163 | SYNAPSE ARRAY OF A NEUROMORPHIC DEVICE INCLUDING A SYNAPSE ARRAY HAVING A PLURALITY OF FERROELECTRICITY FIELD EFFECT TRANSISTORS | November 2021 | November 2025 | Abandon | 49 | 1 | 0 | No | No |
| 17518107 | Importance Sampling via Machine Learning (ML)-Based Gradient Approximation | November 2021 | March 2026 | Abandon | 52 | 2 | 0 | No | No |
| 17513291 | GUI ELEMENT ACQUISITION USING A PLURALITY OF ALTERNATIVE REPRESENTATIONS OF THE GUI ELEMENT | October 2021 | May 2025 | Allow | 42 | 3 | 0 | No | Yes |
| 17491777 | DATA CLUSTERING FOR NETWORK TRAFFIC MODELING | October 2021 | February 2026 | Allow | 52 | 3 | 0 | Yes | No |
| 17492391 | NONLINEAR AUTOREGRESSIVE EXOGENOUS (NARX) MODELLING FOR POWER ELECTRONIC DEVICE MODELLING | October 2021 | December 2025 | Abandon | 50 | 1 | 0 | No | No |
| 17490769 | OPTIMIZING CIRCUIT COMPILER FOR TRAPPED-ION QUANTUM COMPUTERS | September 2021 | March 2025 | Allow | 42 | 0 | 0 | No | No |
| 17490352 | AUTOMATED GENERATION OF A MACHINE LEARNING MODEL FROM COMPUTATIONAL SIMULATION DATA | September 2021 | February 2026 | Allow | 52 | 2 | 0 | Yes | No |
| 17488261 | DYNAMIC QUANTIZATION FOR ENERGY EFFICIENT DEEP LEARNING | September 2021 | September 2025 | Allow | 48 | 2 | 0 | Yes | No |
| 17485643 | SYSTEMS AND METHODS FOR REPLACING A STORED VERSION OF MEDIA WITH A VERSION BETTER SUITED FOR A USER | September 2021 | July 2024 | Allow | 34 | 3 | 0 | Yes | No |
| 17486798 | REUSE OF MACHINE LEARNING MODELS | September 2021 | January 2026 | Allow | 52 | 3 | 0 | Yes | No |
| 17481557 | RECOMMENDATION APPARATUS | September 2021 | November 2025 | Abandon | 49 | 2 | 0 | No | No |
| 17446537 | MACHINE LEARNING MODEL SELECTION BASED ON FEATURE MERGING FOR A SPATIAL LOCATION ACROSS MULTIPLE TIME WINDOWS | August 2021 | February 2026 | Allow | 53 | 3 | 0 | No | No |
| 17411802 | SECURITY / AUTOMATION SYSTEM CONTROL PANEL GRAPHICAL USER INTERFACE | August 2021 | March 2025 | Allow | 43 | 4 | 0 | Yes | No |
| 17400094 | SRAM-SHARING FOR RECONFIGURABLE NEURAL PROCESSING UNITS | August 2021 | May 2025 | Allow | 45 | 1 | 0 | No | No |
| 17384563 | SYSTEMS AND METHODS FOR CREATING A KNOWLEDGE GRAPH | July 2021 | November 2025 | Allow | 52 | 2 | 0 | Yes | No |
| 17384197 | SPECTRAL CLUSTERING OF HIGH-DIMENSIONAL DATA | July 2021 | March 2025 | Allow | 44 | 1 | 0 | Yes | No |
| 17350084 | ROBOTIC PROCESS AUTOMATION | June 2021 | September 2024 | Allow | 39 | 5 | 0 | Yes | No |
| 17331938 | Fully Explainable Document Classification Method And System | May 2021 | November 2025 | Abandon | 53 | 2 | 0 | No | No |
| 17315878 | DEVICE AND COMPUTER-IMPLEMENTED METHOD FOR MACHINE LEARNING | May 2021 | June 2025 | Abandon | 50 | 2 | 0 | No | No |
| 17280932 | EVENT-BASED PROCESSING USING THE OUTPUT OF A DEEP NEURAL NETWORK | March 2021 | November 2024 | Abandon | 44 | 1 | 0 | No | No |
| 17277623 | LEARNING-TYPE REAL SPACE INFORMATION FORMATION SYSTEM | March 2021 | January 2026 | Allow | 58 | 3 | 0 | Yes | No |
| 17272540 | Spiking Neuron Device and Combinatorial Optimization Problem Calculation Device | March 2021 | August 2024 | Allow | 42 | 0 | 0 | No | No |
| 17186792 | PROVIDER PERFORMANCE SCORING USING SUPERVISED AND UNSUPERVISED LEARNING | February 2021 | July 2025 | Allow | 53 | 2 | 0 | Yes | No |
| 17185045 | DETECTING ASSOCIATED EVENTS | February 2021 | December 2025 | Allow | 57 | 4 | 0 | Yes | No |
| 17269992 | IMAGE GENERATION DEVICE, ROBOT TRAINING SYSTEM, IMAGE GENERATION METHOD, AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM | February 2021 | January 2025 | Allow | 47 | 2 | 0 | No | No |
| 17268777 | Optical Signal Processing Device | February 2021 | November 2024 | Allow | 45 | 1 | 0 | No | No |
| 17153282 | METHOD AND APPARATUS WITH NEURAL ARCHITECTURE SEARCH BASED ON HARDWARE PERFORMANCE | January 2021 | September 2025 | Allow | 56 | 3 | 0 | Yes | No |
| 17151222 | METHOD FOR DIFFERENTIABLE ARCHITECTURE SEARCH BASED ON A HIERARCHICAL GROUPING MECHANISM | January 2021 | November 2024 | Allow | 46 | 2 | 0 | Yes | No |
| 17109835 | ITERATIVE MACHINE LEARNING AND RELEARNING | December 2020 | February 2025 | Allow | 51 | 2 | 0 | Yes | No |
| 17103833 | EFFICIENT TEMPORAL MEMORY FOR SPARSE BINARY SEQUENCES | November 2020 | September 2024 | Allow | 46 | 2 | 0 | No | No |
| 16692261 | ENHANCED VIEWS AND NOTIFICATIONS OF LOCATION AND CALENDAR INFORMATION | November 2019 | March 2026 | Allow | 60 | 5 | 0 | Yes | Yes |
| 16595294 | WorkMerk Flowchart | October 2019 | November 2025 | Abandon | 60 | 5 | 1 | No | No |
| 15458653 | SYSTEM AND METHOD TO REVISE VERTICAL PROFILE OF A FLIGHT PLAN | March 2017 | June 2019 | Allow | 27 | 1 | 0 | No | No |
| 15338725 | SYSTEMS, METHODS, AND MOBILE DEVICES FOR PROVIDING A USER INTERFACE TO FACILITATE ACCESS TO PREPAID WIRELESS ACCOUNT INFORMATION | October 2016 | August 2019 | Allow | 33 | 1 | 0 | Yes | No |
| 14925450 | MOBILE TERMINAL AND METHOD FOR CONTROLLING THE SAME | October 2015 | September 2018 | Allow | 34 | 1 | 0 | No | No |
| 14918633 | AUTOMATED MODIFICATION OF GRAPHICAL USER INTERFACES | October 2015 | June 2019 | Allow | 44 | 3 | 0 | Yes | No |
| 14489376 | BACKGROUND RELOADING OF CURRENTLY DISPLAYED CONTENT | September 2014 | April 2018 | Allow | 43 | 3 | 0 | Yes | No |
| 14083799 | METHOD OF DISPLAYING LOCATION OF A DEVICE | November 2013 | January 2018 | Allow | 50 | 4 | 0 | Yes | No |
| 13671783 | VIRTUAL MEETINGS | November 2012 | June 2017 | Allow | 55 | 5 | 0 | No | No |
| 13661230 | VIRTUAL MEETINGS | October 2012 | June 2017 | Allow | 56 | 7 | 0 | Yes | No |
| 13550716 | SYSTEM AND METHOD FOR SEARCHING THROUGH A GRAPHIC USER INTERFACE | July 2012 | November 2014 | Allow | 28 | 1 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner CHIUSANO, ANDREW TSUTOMU.
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, 50.0% 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 CHIUSANO, ANDREW TSUTOMU works in Art Unit 2144 and has examined 44 patent applications in our dataset. With an allowance rate of 81.8%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 49 months.
Examiner CHIUSANO, ANDREW TSUTOMU's allowance rate of 81.8% places them in the 53% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by CHIUSANO, ANDREW TSUTOMU receive 2.34 office actions before reaching final disposition. This places the examiner in the 66% 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 CHIUSANO, ANDREW TSUTOMU is 49 months. This places the examiner in the 6% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +36.4% benefit to allowance rate for applications examined by CHIUSANO, ANDREW TSUTOMU. This interview benefit is in the 84% 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, 34.8% of applications are subsequently allowed. This success rate is in the 77% percentile among all examiners. Strategic Insight: RCEs are highly effective with this examiner compared to others. If you receive a final rejection, filing an RCE with substantive amendments or arguments has a strong likelihood of success.
This examiner enters after-final amendments leading to allowance in 15.4% 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, 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 50.0% of appeals filed. This is in the 16% percentile among all examiners. Strategic Insight: This examiner rarely withdraws rejections during the appeal process compared to other examiners. If you file an appeal, be prepared to fully prosecute it to a PTAB decision. Per MPEP § 1207, the examiner will prepare an Examiner's Answer maintaining the rejections.
When applicants file petitions regarding this examiner's actions, 100.0% are granted (fully or in part). This grant rate is in the 90% 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.