Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19088950 | SYSTEM AND METHOD FOR DATA STORAGE, TRANSFER, SYNCHRONIZATION, AND SECURITY USING AUTOMATED MODEL MONITORING AND TRAINING WITH A LOAD-ADAPTIVE CACHE | March 2025 | December 2025 | Allow | 9 | 2 | 0 | No | No |
| 19060781 | SYSTEM AND METHOD FOR ASYMMETRIC DATA COMPRESSION USING DUAL CODEBOOKS | February 2025 | October 2025 | Allow | 8 | 2 | 0 | No | No |
| 18913556 | SYSTEM AND METHODS FOR BANDWIDTH-EFFICIENT DATA ENCODING | October 2024 | December 2025 | Allow | 14 | 1 | 0 | No | No |
| 18904106 | SYSTEM AND METHOD FOR SECURING HIGH-SPEED INTRACHIP COMMUNICATIONS | October 2024 | November 2025 | Allow | 14 | 1 | 0 | No | No |
| 18886191 | VALIDITY MAPPING TECHNIQUES | September 2024 | December 2025 | Allow | 15 | 1 | 0 | No | No |
| 18883268 | Fabric Data Rate Limiting Proportional to Electrical Current Threshold Violations | September 2024 | February 2026 | Allow | 17 | 0 | 0 | No | No |
| 18773999 | SYSTEM AND METHOD FOR CODEBOOK MANAGEMENT BASED ON DATA SOURCE GROUPING | July 2024 | October 2025 | Allow | 15 | 1 | 0 | No | No |
| 18714587 | CACHE MEMORY CONTROL APPARATUS AND CACHE MEMORY CONTROL METHOD | May 2024 | October 2025 | Allow | 17 | 2 | 0 | No | No |
| 18673255 | Adaptive Data Storage Management | May 2024 | February 2026 | Allow | 21 | 2 | 0 | Yes | No |
| 18609303 | CHOOSING AMONG STORAGE OPTIMIZATIONS WHEN STORING CANDIDATE DATA | March 2024 | February 2026 | Allow | 23 | 1 | 0 | No | No |
| 18499215 | A SYSTEM AND METHOD FOR OPERATING SYSTEM MULTILOADING AND VIRTUALIZATION USING CODEBOOK ENCODING OF DATA STREAMS AND PROCESS CALLS | November 2023 | November 2025 | Allow | 24 | 2 | 0 | No | No |
| 18367921 | SYSTEM AND METHOD FOR IMPLEMENTING TEMPERATURE COMPENSATION IN A MEMORY DEVICE | September 2023 | December 2025 | Allow | 27 | 1 | 0 | No | No |
| 18340637 | MODULAR DATA STORAGE SYSTEM WITH DATA RESILIENCY | June 2023 | October 2025 | Allow | 28 | 2 | 0 | No | Yes |
| 18308035 | METHOD AND SYSTEM FOR SUPPORTING DEDUPE, COMPRESSION, LOGICAL VOLUME CRYPTO-ERASURE, AND PHYSICAL VOLUME CRYPTO-ERASURE ON A STORAGE ARRAY | April 2023 | September 2025 | Allow | 29 | 0 | 1 | No | No |
| 18167096 | SYSTEM AND METHOD FOR DATA COMPACTION AND SECURITY USING MULTIPLE ENCODING ALGORITHMS WITH PRE-CODING AND COMPLEXITY ESTIMATION | February 2023 | November 2025 | Allow | 33 | 2 | 0 | No | No |
| 18106399 | INCREASING DATA PERFORMANCE BY TRANSFERRING DATA BETWEEN STORAGE TIERS USING WORKLOAD CHARACTERISTICS | February 2023 | November 2025 | Allow | 33 | 2 | 0 | Yes | Yes |
| 18148799 | MEMORY SYSTEMS AND OPERATION METHODS THEREOF TO IMPROVE WEAR LEVELING OF A MEMORY DEVICE | December 2022 | February 2026 | Allow | 37 | 3 | 0 | Yes | No |
| 18067665 | DETERMINING LOGICAL STABILIZER INSTRUMENT FOR STABILIZER CIRCUIT | December 2022 | January 2026 | Allow | 37 | 1 | 0 | Yes | No |
| 18078199 | METHOD AND ELECTRONIC DEVICE FOR PERFORMING DEEP NEURAL NETWORK OPERATION | December 2022 | December 2025 | Allow | 37 | 1 | 0 | Yes | No |
| 17977519 | ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION METHOD AND APPARATUS, DEVICE, STORAGE MEDIUM AND PROGRAM PRODUCT | October 2022 | January 2026 | Allow | 39 | 1 | 0 | Yes | No |
| 17962768 | METHOD OF OPERATING MEMORY-BASED DEVICE | October 2022 | February 2026 | Allow | 40 | 2 | 0 | No | No |
| 17796841 | METHOD AND DEVICE FOR THE CONCEPTION OF A COMPUTATIONAL MEMORY CIRCUIT | August 2022 | February 2026 | Allow | 43 | 5 | 0 | Yes | No |
| 17498771 | MEMORY MANAGEMENT METHOD, MEMORY STORAGE DEVICE, AND MEMORY CONTROL CIRCUIT UNIT | October 2021 | January 2026 | Allow | 51 | 8 | 0 | Yes | No |
| 16659911 | OPTIMIZING TIMING FOR DATA MIGRATION FROM OLD GENERATION TAPES TO NEW GENERATION TAPES | October 2019 | January 2021 | Allow | 15 | 0 | 0 | No | No |
| 16297330 | DATA RECOVERY OPERATIONS, SUCH AS RECOVERY FROM MODIFIED NETWORK DATA MANAGEMENT PROTOCOL DATA | March 2019 | December 2020 | Allow | 21 | 3 | 0 | Yes | No |
| 16290503 | PROCESSING DATA ACCESS REQUESTS IN ACCORDANCE WITH A STORAGE UNIT MEMORY PRESSURE LEVEL | March 2019 | January 2021 | Allow | 23 | 1 | 0 | Yes | No |
| 16257440 | METHODS AND SYSTEMS FOR METADATA TAG INHERITANCE BETWEEN MULTIPLE FILE SYSTEMS WITHIN A STORAGE SYSTEM | January 2019 | March 2021 | Allow | 25 | 3 | 0 | No | No |
| 16257466 | METHODS AND SYSTEMS FOR METADATA TAG INHERITANCE FOR DATA TIERING | January 2019 | March 2021 | Allow | 25 | 3 | 0 | No | No |
| 16257425 | METHODS AND SYSTEMS FOR METADATA TAG INHERITANCE FOR DATA BACKUP | January 2019 | March 2021 | Allow | 25 | 3 | 0 | No | No |
| 16202326 | DYNAMIC WRITE-BACK TO NON-VOLATILE MEMORY | November 2018 | June 2021 | Allow | 31 | 5 | 0 | Yes | No |
| 15943079 | MEMORY REDUCTION FOR NEURAL NETWORKS WITH FIXED STRUCTURES | April 2018 | May 2020 | Allow | 25 | 2 | 0 | Yes | No |
| 15895597 | POINT-IN-TIME COPY WITH TARGET WRITE OPTIMIZATION | February 2018 | February 2020 | Allow | 24 | 1 | 0 | No | No |
| 15672425 | TECHNOLOGIES FOR POSITION-INDEPENDENT PERSISTENT MEMORY POINTERS | August 2017 | January 2018 | Allow | 5 | 0 | 0 | No | No |
| 15627404 | METHOD FOR PERFORMING REPLICATION CONTROL IN STORAGE SYSTEM WITH AID OF RELATIONSHIP TREE WITHIN DATABASE, AND ASSOCIATED APPARATUS | June 2017 | May 2019 | Allow | 23 | 1 | 0 | No | No |
| 15461262 | ITERATOR REGISTER FOR STRUCTURED MEMORY | March 2017 | September 2017 | Allow | 6 | 0 | 0 | No | No |
| 15443907 | ITERATOR REGISTER FOR STRUCTURED MEMORY | February 2017 | November 2017 | Allow | 9 | 1 | 0 | No | No |
| 15419272 | DATA RECOVERY OPERATIONS, SUCH AS RECOVERY FROM MODIFIED NETWORK DATA MANAGEMENT PROTOCOL DATA | January 2017 | December 2018 | Allow | 22 | 3 | 0 | No | No |
| 15121136 | DATA STORAGE DEVICE INCLUDING MULTIPLE MEMORY MODULES AND CIRCUITRY TO MANAGE COMMUNICATION AMONG THE MULTIPLE MEMORY MODULES | August 2016 | March 2019 | Allow | 31 | 4 | 0 | Yes | No |
| 14939063 | MEMORY MAPPING FOR OBJECT-BASED STORAGE DEVICES | November 2015 | September 2017 | Allow | 22 | 1 | 0 | Yes | No |
| 14751454 | TECHNOLOGIES FOR POSITION-INDEPENDENT PERSISTENT MEMORY POINTERS | June 2015 | May 2017 | Allow | 23 | 0 | 0 | No | No |
| 14261589 | SYSTEM PERFORMANCE CONTROL COMPONENT AND METHOD THEREFOR | April 2014 | April 2016 | Allow | 23 | 1 | 0 | No | No |
| 14220888 | SUB-LUN INPUT/OUTPUT PROFILING FOR SSD DEVICES | March 2014 | October 2016 | Allow | 31 | 5 | 0 | No | No |
| 14220960 | SUB-LUN INPUT/OUTPUT PROFILING FOR SSD DEVICES | March 2014 | August 2016 | Abandon | 29 | 5 | 0 | No | No |
| 14169674 | METHOD AND APPARATUS TO MANAGE TIER INFORMATION | January 2014 | April 2017 | Allow | 39 | 3 | 0 | No | No |
| 14158899 | SOLID-STATE STORAGE MANAGEMENT | January 2014 | August 2017 | Allow | 43 | 7 | 0 | Yes | No |
| 13790709 | MANAGING HIGH SPEED MEMORY | March 2013 | July 2014 | Allow | 16 | 2 | 0 | No | No |
| 13750811 | SYSTEMS WITH PROGRAMMABLE HETEROGENEOUS MEMORY CONTROLLERS FOR MAIN MEMORY | January 2013 | January 2014 | Allow | 11 | 1 | 0 | No | No |
| 13648009 | APPARATUS, SYSTEM, AND METHOD FOR SOLID-STATE STORAGE AS CACHE FOR HIGH-CAPACITY, NON-VOLATILE STORAGE | October 2012 | October 2016 | Allow | 48 | 7 | 0 | Yes | No |
| 13619424 | SOLID-STATE DEVICE MANAGEMENT | September 2012 | May 2017 | Allow | 56 | 8 | 0 | Yes | No |
| 13367567 | COMMUNICATING CHUNKS BETWEEN DEVICES | February 2012 | September 2016 | Allow | 55 | 2 | 0 | No | Yes |
| 13357465 | APPARATUS, SYSTEM, AND METHOD FOR DESTAGING CACHED DATA | January 2012 | August 2016 | Allow | 54 | 1 | 1 | Yes | No |
| 13336385 | SOLID-STATE STORAGE MANAGEMENT | December 2011 | April 2017 | Allow | 60 | 7 | 0 | Yes | No |
| 13241625 | DATA RECOVERY OPERATIONS, SUCH AS RECOVERY FROM MODIFIED NETWORK DATA MANAGEMENT PROTOCOL DATA | September 2011 | September 2015 | Allow | 48 | 1 | 1 | No | No |
| 13192412 | SYSTEM AND METHOD FOR VIRTUAL PARTITION MONITORING | July 2011 | November 2015 | Allow | 52 | 4 | 0 | Yes | No |
| 13088211 | APPARATUS, SYSTEM, AND METHOD FOR DESTAGING CACHED DATA | April 2011 | April 2015 | Allow | 48 | 1 | 1 | Yes | No |
| 12842958 | ITERATOR REGISTER FOR STRUCTURED MEMORY | July 2010 | November 2016 | Allow | 60 | 6 | 1 | Yes | No |
| 12774643 | DISK DRIVE USING NON-VOLATILE CACHE WHEN GARBAGE COLLECTING LOG STRUCTURED WRITES | May 2010 | October 2016 | Allow | 60 | 4 | 0 | Yes | Yes |
| 11943441 | METHOD FOR MANAGING METRICS TABLE PER VIRTUAL PORT IN A LOGICALLY PARTITIONED DATA PROCESSING SYSTEM | November 2007 | September 2008 | Allow | 10 | 1 | 0 | No | No |
| 11838852 | DATA DISPLACEMENT BYPASS SYSTEM | August 2007 | May 2010 | Allow | 33 | 0 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner ALSIP, MICHAEL.
With a 100.0% reversal rate, the PTAB has reversed the examiner's rejections more often than affirming them. This reversal rate is in the top 25% across the USPTO, indicating that appeals are more successful here than in most other areas.
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, 100.0% 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 ALSIP, MICHAEL works in Art Unit 2139 and has examined 37 patent applications in our dataset. With an allowance rate of 97.3%, this examiner allows applications at a higher rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 25 months.
Examiner ALSIP, MICHAEL's allowance rate of 97.3% places them in the 88% percentile among all USPTO examiners. This examiner is more likely to allow applications than most examiners at the USPTO.
On average, applications examined by ALSIP, MICHAEL receive 2.84 office actions before reaching final disposition. This places the examiner in the 83% 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 ALSIP, MICHAEL is 25 months. This places the examiner in the 78% percentile for prosecution speed. Applications move through prosecution relatively quickly with this examiner.
Conducting an examiner interview provides a +4.8% benefit to allowance rate for applications examined by ALSIP, MICHAEL. 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, 22.7% 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 19.2% of cases where such amendments are filed. This entry rate is in the 23% 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 5% 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.