Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18662972 | SCALABLE AND COMPRESSIVE NEURAL NETWORK DATA STORAGE SYSTEM | May 2024 | October 2025 | Allow | 17 | 2 | 0 | No | No |
| 18440079 | TECHNIQUES FOR DISTRIBUTED INTERFACE COMPONENT GENERATION | February 2024 | April 2025 | Allow | 15 | 2 | 0 | Yes | No |
| 18410957 | BROWSING HIERARCHICAL DATASETS | January 2024 | September 2025 | Allow | 21 | 3 | 0 | Yes | No |
| 18371391 | HYBRID SEARCH SYSTEM FOR CUSTOMIZABLE MEDIA | September 2023 | January 2025 | Allow | 16 | 1 | 0 | Yes | No |
| 18234613 | USER INTERFACES FOR AUDIO MEDIA CONTROL | August 2023 | October 2024 | Allow | 14 | 1 | 0 | Yes | No |
| 18217054 | Method and Apparatus for Vehicle Damage Mapping | June 2023 | September 2024 | Allow | 15 | 1 | 0 | Yes | No |
| 18197662 | INFORMATION OUTPUT SYSTEM AND METHOD | May 2023 | July 2024 | Allow | 15 | 3 | 0 | Yes | No |
| 18314704 | COMBINING FIRST USER INTERFACE CONTENT INTO SECOND USER INTERFACE | May 2023 | November 2024 | Allow | 18 | 3 | 0 | Yes | No |
| 18193315 | MACHINE LEARNING INTEGRATION IN LOW-CODE NO-CODE APPLICATION DEVELOPMENT | March 2023 | December 2025 | Allow | 33 | 2 | 0 | Yes | No |
| 18190865 | GENERATING AND PROVIDING SYNTHESIZED TASKS PRESENTED IN A CONSOLIDATED GRAPHICAL USER INTERFACE | March 2023 | October 2024 | Allow | 19 | 2 | 0 | Yes | No |
| 18123540 | METHODS FOR FACILITATING ACCESS AND CUSTOMIZABLE INTERACTION WITH DATA VIA A CUSTOMIZED GRAPHICAL USER INTERFACE AND DEVICES THEREOF | March 2023 | November 2025 | Allow | 32 | 4 | 0 | No | No |
| 18184266 | EMPLOYEE WORKFLOW NAVIGATION SYSTEM | March 2023 | October 2025 | Allow | 31 | 4 | 0 | Yes | No |
| 18157162 | MULTI-SESSION AUTOMATION WINDOWS FOR ROBOTIC PROCESS AUTOMATION USING SAME CREDENTIALS | January 2023 | September 2025 | Abandon | 32 | 2 | 0 | No | No |
| 18076240 | VISUALIZATION OF APPLICATION CAPABILITIES | December 2022 | November 2025 | Allow | 36 | 3 | 0 | Yes | No |
| 17984076 | ELECTRONIC APPARATUS AND CONTROLLING METHOD THEREOF | November 2022 | July 2024 | Allow | 21 | 3 | 0 | Yes | No |
| 17918263 | MONITORING AN ELECTRICAL-ENERGY TRANSMISSION SYSTEM | October 2022 | October 2024 | Allow | 25 | 3 | 0 | Yes | No |
| 17956515 | METHOD AND SYSTEM FOR FACILITATING WORKFLOWS VIA VOICE COMMUNICATION | September 2022 | March 2026 | Abandon | 41 | 6 | 0 | Yes | Yes |
| 17870848 | CIGARETTE DEVICE MANAGEMENT SYSTEM AND METHOD | July 2022 | November 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17868148 | Method for Gas Detection Based on Multiple Quantum Neural Networks | July 2022 | December 2025 | Abandon | 41 | 1 | 0 | No | No |
| 17741268 | TRANSITIONING APPLICATION WINDOWS BETWEEN LOCAL AND REMOTE DESKTOPS | May 2022 | June 2025 | Allow | 37 | 5 | 0 | Yes | No |
| 17773093 | SYSTEM AND METHOD FOR OPERATING AN EVENT-DRIVEN ARCHITECTURE | April 2022 | September 2025 | Allow | 41 | 1 | 0 | Yes | No |
| 17699263 | FEDERATED LEARNING METHOD USING SYNONYM | March 2022 | August 2025 | Allow | 41 | 1 | 0 | No | No |
| 17697104 | FEDERATED LEARNING SYSTEM USING SYNONYM | March 2022 | August 2025 | Allow | 41 | 1 | 0 | No | No |
| 17592345 | Congruent Quantum Computation Theory (CQCT) | February 2022 | March 2026 | Abandon | 49 | 1 | 0 | No | No |
| 17649576 | CONTROLLED PROPAGATION OF INPUT VALUES IN QUANTUM COMPUTING | February 2022 | September 2025 | Allow | 43 | 1 | 0 | No | No |
| 17578416 | COMPUTING CIRCUIT AND DATA PROCESSING METHOD BASED ON CONVOLUTIONAL NEURAL NETWORK AND COMPUTER READABLE STORAGE MEDIUM | January 2022 | September 2025 | Allow | 44 | 1 | 0 | No | No |
| 17623665 | Human-Machine Multi-Turn Conversation Method and System for Human-Machine Interaction, and Intelligent Apparatus | December 2021 | June 2025 | Allow | 42 | 1 | 0 | No | No |
| 17562124 | METHOD OF DRIVING A QUANTUM COMPUTER TO FIND ONE OR MORE STATES OF INTEREST OF A NETWORK | December 2021 | February 2026 | Allow | 49 | 1 | 0 | No | No |
| 17604670 | METHOD AND APPARATUS FOR ADAPTING DEEP LEARNING MODEL, AND ELECTRONIC DEVICE | October 2021 | July 2025 | Allow | 45 | 1 | 0 | Yes | No |
| 17497193 | ELECTRONIC DEVICE AND CONTROL METHOD THEREOF | October 2021 | August 2025 | Allow | 46 | 2 | 0 | No | No |
| 17496934 | INFORMATION PROCESSING DEVICE, METHOD FOR SETTING HIDDEN NODES, AND METHOD FOR MANUFACTURING INFORMATION PROCESSING DEVICE | October 2021 | September 2025 | Abandon | 48 | 1 | 0 | No | No |
| 17491240 | GENERATING ESTIMATES BY COMBINING UNSUPERVISED AND SUPERVISED MACHINE LEARNING | September 2021 | February 2026 | Allow | 52 | 2 | 0 | No | No |
| 17489090 | PHASE INTERFEROMETRY DIRECTION FINDING VIA DEEP LEARNING TECHNIQUES | September 2021 | September 2025 | Abandon | 48 | 1 | 0 | No | No |
| 17479547 | AUTOMATED DIGITAL TEXT OPTIMIZATION AND MODIFICATION | September 2021 | January 2026 | Allow | 51 | 2 | 0 | Yes | No |
| 17477713 | LEARNING BASED MODELING OF EMERGENT BEHAVIOUR OF COMPLEX SYSTEM | September 2021 | August 2025 | Allow | 47 | 2 | 0 | Yes | No |
| 17478486 | SYSTEM AND METHOD TO GENERATE INSIGHT TEMPLATES FOR RISK PROBABILITY ANALYSIS | September 2021 | August 2025 | Allow | 47 | 2 | 0 | Yes | No |
| 17446020 | MULTI-MODAL FEW-SHOT LEARNING DEVICE FOR USER IDENTIFICATION USING WALKING PATTERN BASED ON DEEP LEARNING ENSEMBLE | August 2021 | October 2025 | Abandon | 50 | 2 | 0 | No | No |
| 17406431 | DYNAMIC VEHICLE OPERATION | August 2021 | November 2025 | Abandon | 51 | 2 | 0 | Yes | No |
| 17344254 | TRAINING PERSPECTIVE COMPUTER VISION MODELS USING VIEW SYNTHESIS | June 2021 | April 2025 | Allow | 47 | 1 | 0 | Yes | No |
| 17342719 | SENSOR DATA PROCESSING | June 2021 | November 2025 | Allow | 54 | 2 | 0 | No | No |
| 17341511 | MULTI-USER CAMERA SWITCH ICON DURING VIDEO CALL | June 2021 | October 2025 | Allow | 52 | 6 | 0 | Yes | Yes |
| 17328661 | Operational Analysis For Machine Learning Model | May 2021 | July 2025 | Allow | 50 | 2 | 0 | Yes | No |
| 17321709 | Supporting Database Constraints in Synthetic Data Generation Based on Generative Adversarial Networks | May 2021 | May 2025 | Allow | 48 | 1 | 0 | Yes | No |
| 17239320 | ENERGY BASED PROCESSES FOR EXCHANGEABLE DATA | April 2021 | April 2025 | Abandon | 48 | 1 | 0 | No | No |
| 17235183 | MULTI-DOMAIN DETECTOR BASED ON ARTIFICIAL NEURAL NETWORK | April 2021 | April 2025 | Allow | 48 | 1 | 0 | Yes | No |
| 17283254 | DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND DATA CLASSIFICATION PROGRAM | April 2021 | July 2025 | Allow | 51 | 2 | 0 | Yes | No |
| 17276949 | AI MODEL DEVELOPMENT METHOD AND APPARATUS | March 2021 | June 2025 | Abandon | 51 | 2 | 0 | No | No |
| 17277016 | METHOD FOR DECODING, COMPUTER PROGRAM PRODUCT, AND DEVICE | March 2021 | October 2025 | Abandon | 55 | 2 | 0 | No | No |
| 17277259 | LEARNING DEVICE, ESTIMATION DEVICE, LEARNING METHOD, ESTIMATION METHOD, AND PROGRAM | March 2021 | October 2025 | Abandon | 55 | 2 | 0 | No | No |
| 17273428 | SELECTING DEVICE AND SELECTING METHOD | March 2021 | June 2025 | Abandon | 51 | 2 | 0 | No | No |
| 17270853 | ARCHITECTURE OF A COMPUTER FOR CALCULATING A CONVOLUTION LAYER IN A CONVOLUTIONAL NEURAL NETWORK | February 2021 | January 2026 | Allow | 59 | 4 | 0 | Yes | No |
| 17169718 | SORTING ATTENTION NEURAL NETWORKS | February 2021 | March 2025 | Allow | 49 | 2 | 0 | Yes | No |
| 17127778 | SYSTEM AND METHOD FOR PERFORMING TREE-BASED MULTIMODAL REGRESSION | December 2020 | January 2026 | Abandon | 60 | 4 | 0 | Yes | No |
| 17127904 | METHOD FOR STATIC SCHEDULING OF ARTIFICIAL NEURAL NETWORKS FOR A PROCESSOR | December 2020 | March 2025 | Allow | 51 | 1 | 0 | Yes | No |
| 17091499 | Knowledge-Driven and Self-Supervised System for Question-Answering | November 2020 | November 2025 | Allow | 60 | 3 | 0 | No | No |
| 17090553 | SYSTEMS AND METHODS FOR A K-NEAREST NEIGHBOR BASED MECHANISM OF NATURAL LANGUAGE PROCESSING MODELS | November 2020 | November 2024 | Allow | 49 | 2 | 0 | Yes | No |
| 17049065 | ARITHMETIC DEVICE | October 2020 | August 2024 | Allow | 46 | 2 | 0 | Yes | No |
| 17070456 | WORKBOOKS FOR ONLINE TOOLS | October 2020 | November 2024 | Abandon | 49 | 6 | 0 | Yes | No |
| 17037525 | ORCHESTRATION FOR BUILDING AND EXECUTING MACHINE LEARNING PIPELINES ON GRAPH DATA | September 2020 | April 2025 | Allow | 54 | 3 | 0 | Yes | No |
| 16845451 | CREATING AN APP METHOD AND SYSTEM | April 2020 | May 2025 | Abandon | 60 | 6 | 0 | Yes | Yes |
| 16571315 | INTELLIGENT ENCLOSURE SYSTEMS AND COMPUTING METHODS | September 2019 | September 2025 | Abandon | 60 | 6 | 0 | Yes | Yes |
| 16291399 | EXPERT-DRIVEN, TECHNOLOGY-FACILITATED INTERVENTION SYSTEM FOR IMPROVING INTERPERSONAL RELATIONSHIPS | March 2019 | October 2025 | Abandon | 60 | 3 | 0 | No | Yes |
| 16254128 | Methods for Detecting Events in Sports using a Convolutional Neural Network | January 2019 | August 2024 | Allow | 60 | 6 | 0 | Yes | No |
| 15414960 | INFORMATION PROCESSING APPARATUS AND REGISTRATION METHOD | January 2017 | September 2019 | Allow | 32 | 1 | 0 | Yes | No |
| 15205979 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM, AND DISTRIBUTION DEVICE | July 2016 | April 2019 | Allow | 33 | 2 | 0 | No | No |
| 15186824 | IMAGE PROCESSING APPARATUS, METHOD FOR CONTROLLING OPERATION OF IMAGE PROCESSING APPARATUS, AND RECORDING MEDIUM | June 2016 | April 2019 | Allow | 34 | 2 | 0 | No | No |
| 14515646 | Providing Enhanced Application Interoperability | October 2014 | February 2019 | Allow | 52 | 4 | 0 | Yes | No |
| 14341326 | METHOD FOR CONTROLLING A VIRTUAL KEYBOARD FROM A TOUCHPAD OF A COMPUTERIZED DEVICE | July 2014 | October 2017 | Allow | 38 | 2 | 0 | Yes | No |
| 14059360 | TEXT ENTRY BASED ON PERSISTING ACTIONS | October 2013 | May 2018 | Allow | 55 | 5 | 0 | Yes | No |
| 14009095 | APPLICATION EQUIVALENCE MAP FOR SYNCHRONIZED POSITIONING OF APPLICATION ICONS ACROSS DEVICE PLATFORMS | September 2013 | April 2017 | Allow | 43 | 4 | 0 | Yes | No |
| 13485814 | GENERATING NOTIFICATIONS BASED ON FORMATION OF MEMBERSHIPS | May 2012 | September 2017 | Allow | 60 | 6 | 0 | Yes | No |
| 13343265 | WEB VIDEO OCCLUSION: A METHOD FOR RENDERING THE VIDEOS WATCHED OVER MULTIPLE WINDOWS | January 2012 | February 2015 | Allow | 38 | 3 | 0 | Yes | No |
| 13160938 | GRAPHICAL USER INTERFACE DEVICE | June 2011 | July 2015 | Allow | 49 | 5 | 0 | Yes | No |
| 13155536 | VIRTUAL MEETING VIDEO SHARING | June 2011 | August 2013 | Allow | 27 | 2 | 0 | Yes | No |
| 13155760 | LETTER INPUT METHOD AND APPARATUS OF PORTABLE TERMINAL | June 2011 | April 2014 | Allow | 35 | 3 | 0 | Yes | No |
| 13077010 | METHOD AND APPARATUS FOR PROVIDING COLLABORATION BETWEEN REMOTE AND ON-SITE USERS OF INDIRECT AUGMENTED REALITY | March 2011 | February 2015 | Allow | 47 | 2 | 0 | Yes | No |
| 11582314 | IMAGE REPRODUCTION APPARATUS AND IMAGE REPRODUCTION PROGRAM | October 2006 | January 2014 | Allow | 60 | 5 | 0 | No | No |
| 10346351 | System and method for mouseless navigation of web applications | January 2003 | May 2017 | Allow | 60 | 6 | 0 | No | Yes |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner DASGUPTA, SHOURJO.
With a 20.0% 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, 14.3% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the bottom 25% across the USPTO, indicating that filing appeals is less effective here than in most other areas.
⚠ 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 DASGUPTA, SHOURJO works in Art Unit 2144 and has examined 52 patent applications in our dataset. With an allowance rate of 73.1%, this examiner has a below-average tendency to allow applications. Applications typically reach final disposition in approximately 50 months.
Examiner DASGUPTA, SHOURJO's allowance rate of 73.1% places them in the 37% percentile among all USPTO examiners. This examiner has a below-average tendency to allow applications.
On average, applications examined by DASGUPTA, SHOURJO receive 2.75 office actions before reaching final disposition. This places the examiner in the 80% 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 DASGUPTA, SHOURJO 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 +32.2% benefit to allowance rate for applications examined by DASGUPTA, SHOURJO. This interview benefit is in the 80% 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, 18.5% of applications are subsequently allowed. This success rate is in the 18% percentile among all examiners. Strategic Insight: RCEs show lower effectiveness with this examiner compared to others. Consider whether a continuation application might be more strategic, especially if you need to add new matter or significantly broaden claims.
This examiner enters after-final amendments leading to allowance in 41.0% of cases where such amendments are filed. This entry rate is in the 63% percentile among all examiners. Strategic Recommendation: This examiner shows above-average receptiveness to after-final amendments. If your amendments clearly overcome the rejections and do not raise new issues, consider filing after-final amendments before resorting to an RCE.
When applicants request a pre-appeal conference (PAC) with this examiner, 100.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 71% percentile among all examiners. Strategic Recommendation: Pre-appeal conferences show above-average effectiveness with this examiner. If you have strong arguments, a PAC request may result in favorable reconsideration.
This examiner withdraws rejections or reopens prosecution in 37.5% of appeals filed. This is in the 6% 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 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.
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.