Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19292142 | ARITHMETIC ENCODER FOR ARITHMETICALLY ENCODING AND ARITHMETIC DECODER FOR ARITHMETICALLY DECODING A SEQUENCE OF INFORMATION VALUES, METHODS FOR ARITHMETICALLY ENCODING AND DECODING A SEQUENCE OF INFORMATION VALUES AND COMPUTER PROGRAM FOR IMPLEMENTING THESE METHODS | August 2025 | February 2026 | Allow | 6 | 1 | 0 | No | No |
| 19245413 | System and Method for Federated Two-Stage Compression Within a Persistent Cognitive Machine | June 2025 | September 2025 | Allow | 2 | 1 | 0 | No | No |
| 19242953 | Hierarchical Smart Caching for Machine Learning Codeword Responses | June 2025 | August 2025 | Allow | 2 | 0 | 0 | No | No |
| 19070411 | SYSTEM AND METHOD FOR COMPRESSING REGULAR DATA STREAMS USING INSTRUCTION CACHE-RESIDENT PERFECT HASH FUNCTIONS | March 2025 | May 2025 | Allow | 2 | 0 | 0 | No | No |
| 19048882 | SYSTEM AND METHOD FOR EDGE BASED MULTI-MODAL HOMOMORPHIC COMPRESSION | February 2025 | May 2025 | Allow | 3 | 1 | 0 | No | No |
| 19048904 | DISTRIBUTED SYSTEM AND METHOD FOR ADAPTIVE NEURAL NETWORK-BASED DATA COMPRESSION | February 2025 | April 2025 | Allow | 2 | 0 | 0 | No | No |
| 19048846 | SYSTEM AND METHOD FOR ADAPTIVE QUALITY DRIVEN COMPRESSION OF GENOMIC DATA USING NEURAL NETWORKS | February 2025 | June 2025 | Allow | 4 | 1 | 0 | No | No |
| 19044355 | SYSTEM AND METHOD FOR ADAPTIVE PROTOCOL CACHING IN EVENT-DRIVEN DATA COMMUNICATION NETWORKS | February 2025 | May 2025 | Allow | 3 | 1 | 0 | No | No |
| 19026345 | FEDERATED LATENT TRANSFORMER DEEP LEARNING CORE | January 2025 | July 2025 | Allow | 6 | 2 | 0 | No | No |
| 19026329 | FEDERATED LATENT TRANSFORMER DEEP LEARNING CORE | January 2025 | November 2025 | Allow | 10 | 2 | 0 | No | No |
| 19017639 | FEDERATED LARGE CODEWORD MODEL DEEP LEARNING ARCHITECTURE | January 2025 | August 2025 | Allow | 7 | 2 | 0 | No | No |
| 19007525 | SYSTEM AND METHODS FOR UPSAMPLING OF DECOMPRESSED GENOMIC DATA AFTER LOSSY COMPRESSION USING A NEURAL NETWORK | January 2025 | June 2025 | Allow | 5 | 0 | 0 | No | No |
| 18972797 | SYSTEM AND METHOD FOR COMPRESSING AND RESTORING DATA USING HIERARCHICAL AUTOENCODERS AND CORRELATION NETWORKS | December 2024 | March 2025 | Allow | 3 | 1 | 0 | No | No |
| 18961011 | Compressing Entropy Tables With Interpolative Coding | November 2024 | February 2025 | Allow | 3 | 0 | 0 | No | No |
| 18939560 | INTEGRATED PROTOCOL ADAPTATION SYSTEM FOR UNIVERSAL CODEWORD APPLICATIONS | November 2024 | March 2025 | Allow | 4 | 1 | 0 | No | No |
| 18919394 | FEDERATED LARGE CODEWORD MODEL DEEP LEARNING ARCHITECTURE WITH HOMOMORPHIC COMPRESSION AND ENCRYPTION | October 2024 | December 2024 | Allow | 2 | 0 | 0 | No | No |
| 18909976 | DEEP LEARNING USING LARGE CODEWORD MODEL WITH HOMOMORPHICALLY COMPRESSED DATA | October 2024 | January 2025 | Allow | 3 | 0 | 0 | No | No |
| 18907442 | SYSTEMS AND METHODS FOR NEURAL NETWORK BASED DATA COMPRESSION | October 2024 | December 2024 | Allow | 2 | 1 | 0 | No | No |
| 18898608 | SYSTEM AND METHOD FOR FEDERATED TWO-STAGE COMPRESSION WITH FEDERATED JOINT LEARNING | September 2024 | March 2025 | Allow | 6 | 1 | 0 | No | No |
| 18896535 | OPTICALLY BASED ANALOG-DIGITAL CONVERTER | September 2024 | February 2026 | Allow | 16 | 2 | 0 | No | No |
| 18895409 | Adaptive Neural Upsampling System for Decoding Lossy Compressed Data Streams | September 2024 | December 2024 | Allow | 3 | 0 | 0 | No | No |
| 18890774 | SYSTEM AND METHOD FOR MULTI-MODAL HOMOMORPHIC COMPRESSION | September 2024 | December 2024 | Allow | 2 | 1 | 0 | No | No |
| 18890748 | SYSTEM AND METHOD FOR FEDERATED TWO-STAGE COMPRESSION WITH FEDERATED JOINT LEARNING | September 2024 | April 2025 | Allow | 6 | 1 | 0 | No | No |
| 18887504 | MULTIMODAL FINANCIAL TECHNOLOGY DEEP LEARNING CORE WITH JOINT OPTIMIZATION OF VECTOR-QUANTIZED VARIATIONAL AUTOENCODER AND NEURAL UPSAMPLER | September 2024 | April 2025 | Allow | 6 | 1 | 0 | No | No |
| 18827741 | EVENT-DRIVEN DATA TRANSMISSION USING CODEBOOKS WITH PROTOCOL PREDICTION AND TRANSLATION | September 2024 | November 2024 | Allow | 2 | 0 | 0 | No | No |
| 18822532 | LINEARIZED OPTICAL DIGITAL-TO-ANALOG MODULATOR | September 2024 | April 2025 | Allow | 7 | 1 | 0 | No | No |
| 18822203 | UPSAMPLING OF COMPRESSED FINANCIAL TIME-SERIES DATA USING A JOINTLY TRAINED VECTOR QUANTIZED VARIATIONAL AUTOENCODER NEURAL NETWORK | September 2024 | December 2024 | Allow | 3 | 1 | 0 | No | No |
| 18818593 | UNIFIED PLATFORM FOR MULTI-TYPE DATA COMPRESSION AND DECOMPRESSION USING HOMOMORPHIC ENCRYPTION AND NEURAL UPSAMPLING | August 2024 | March 2025 | Allow | 6 | 1 | 0 | No | No |
| 18797124 | ANALOG-TO-DIGITAL CONVERTER METASTABILITY ADJUSTMENT | August 2024 | February 2026 | Allow | 19 | 0 | 0 | No | No |
| 18791425 | CONTROLLABLE LOSSY COMPRESSION SYSTEM USING JOINT LEARNING | August 2024 | October 2024 | Allow | 3 | 0 | 0 | No | No |
| 18769416 | SYSTEM AND METHODS FOR UPSAMPLING OF DECOMPRESSED GENOMIC DATA AFTER LOSSY COMPRESSION USING A NEURAL NETWORK | July 2024 | October 2024 | Allow | 3 | 1 | 0 | No | No |
| 18755653 | System and Method for Homomorphic Compression Using Latent Space Preprocessing and Neural Upsampling | June 2024 | October 2024 | Allow | 4 | 1 | 0 | No | No |
| 18741910 | TIME SIGNAL PROCESSOR BASED ON MULTIPLYING PHASE INTERPOLATION CIRCUIT | June 2024 | October 2024 | Allow | 4 | 0 | 0 | No | No |
| 18736275 | SYSTEM AND METHODS FOR UPSAMPLING OF DECOMPRESSED CORRELATED MULTICHANNEL DATA USING A NEURAL NETWORK | June 2024 | February 2026 | Allow | 21 | 1 | 0 | No | No |
| 18673343 | DIFFERENTIAL SUCCESSIVE APPROXIMATION REGISTER ANALOG-TO-DIGITAL CONVERTER WITH DYNAMIC INPUT COMMON-MODE VOLTAGE CONTROL AND ASSOCIATED METHOD | May 2024 | November 2025 | Allow | 18 | 0 | 0 | No | No |
| 18661769 | Compensation circuit and compensation method for successive-approximation register (SAR) analog-to-digital converter (ADC) | May 2024 | November 2025 | Allow | 18 | 0 | 0 | No | No |
| 18709456 | METHOD AND SYSTEM FOR OPTIMIZING TRANSMISSION OF SERIALIZED DATA USING DYNAMIC, ADAPTIVE SLICING AND REDUCTION OF SERIALIZED DATA | May 2024 | November 2025 | Allow | 18 | 0 | 0 | No | No |
| 18659548 | OVERCURRENT DETECTION WITH MULTI-BIT ANALOG-TO-DIGITAL CONVERTERS | May 2024 | February 2026 | Allow | 22 | 0 | 0 | No | No |
| 18657683 | SYSTEM AND METHOD FOR HOMOMORPHIC COMPRESSION | May 2024 | August 2024 | Allow | 3 | 1 | 0 | No | No |
| 18657719 | SYSTEM AND METHOD FOR MULTI-TYPE DATA COMPRESSION OR DECOMPRESSION WITH A VIRTUAL MANAGEMENT LAYER | May 2024 | July 2024 | Allow | 3 | 0 | 0 | No | No |
| 18653522 | EXTRACTING DATA FROM A COMPRESSED AND ENCRYPTED DATA STREAM | May 2024 | December 2025 | Allow | 20 | 1 | 0 | No | No |
| 18648340 | SYSTEM AND METHOD FOR COMPRESSING AND RESTORING DATA USING MULTI - LEVEL AUTOENCODERS AND CORRELATION NETWORKS | April 2024 | August 2024 | Allow | 3 | 1 | 0 | No | No |
| 18644019 | EVENT-DRIVEN DATA TRANSMISSION USING CODEBOOKS WITH PROTOCOL ADAPTION | April 2024 | June 2024 | Allow | 2 | 0 | 0 | No | No |
| 18637821 | SIGMA-DELTA MODULATOR WITH RESIDUE CONVERTER FOR LOW-OFFSET MEASUREMENT SYSTEM | April 2024 | February 2026 | Allow | 22 | 1 | 0 | No | No |
| 18630959 | CONTINUOUS-TIME DELTA-SIGMA ANALOG-TO-DIGITAL CONVERTER WITH DUTY-CYCLE-CONTROLLED INPUT PATH | April 2024 | February 2026 | Allow | 23 | 1 | 0 | No | No |
| 18623018 | SYSTEM AND METHOD FOR LEARNING - BASED LOSSLESS DATA COMPRESSION | March 2024 | June 2024 | Allow | 2 | 0 | 0 | No | No |
| 18619018 | DIGITAL-TO-ANALOG CONVERTER | March 2024 | February 2026 | Allow | 23 | 1 | 0 | No | No |
| 18618082 | INITIATOR IDENTIFIER COMPRESSION | March 2024 | January 2026 | Allow | 21 | 1 | 0 | Yes | No |
| 18618306 | DATA ENCODING METHOD, DATA DECODING METHOD, AND DATA PROCESSING APPARATUS | March 2024 | August 2025 | Allow | 17 | 0 | 0 | No | No |
| 18618630 | CAPACITIVE DIGITAL-TO-ANALOG CONVERTERS WITH SHAPED OUTPUT CURRENT | March 2024 | February 2026 | Allow | 23 | 1 | 0 | No | No |
| 18614147 | SYSTEM AND METHOD FOR DATA COMPRESSION WITH HOMOMORPHIC ENCRYPTION | March 2024 | October 2025 | Allow | 19 | 1 | 0 | No | No |
| 18612917 | POPULATION BASED TRAINING OF NEURAL NETWORKS | March 2024 | January 2025 | Allow | 10 | 1 | 0 | No | No |
| 18597217 | VOLTAGE-TO-TIME CONVERTERS AND METHODS OF OPERATING SAME | March 2024 | February 2026 | Allow | 24 | 1 | 0 | No | No |
| 18594783 | SYSTEM-LEVEL DATA COMPRESSION SCHEME | March 2024 | January 2026 | Allow | 22 | 1 | 0 | No | No |
| 18591217 | Intermediate Frequency Digital-to-Analog Conversion (IFDAC) System | February 2024 | December 2025 | Allow | 21 | 1 | 0 | No | No |
| 18440948 | SYSTEMS AND METHODS FOR COMPRESSION OF ARTIFICIAL INTELLIGENCE | February 2024 | March 2026 | Allow | 25 | 2 | 0 | Yes | No |
| 18427716 | UPSAMPLING OF DECOMPRESSED FINANCIAL TIME - SERIES DATA USING A NEURAL NETWORK | January 2024 | May 2024 | Allow | 3 | 1 | 0 | No | No |
| 18423287 | DATA COMPRESSION WITH PROTOCOL ADAPTATION | January 2024 | September 2024 | Allow | 8 | 0 | 0 | No | No |
| 18420771 | SYSTEM AND METHODS FOR UPSAMPLING OF DECOMPRESSED GENOMIC DATA AFTER LOSSY COMPRESSION USING A NEURAL NETWORK | January 2024 | May 2024 | Allow | 4 | 1 | 0 | No | No |
| 18420033 | SYSTEMS AND METHODS FOR PRECHARGING DRIVER CIRCUITRY FOR AN ANALOG-TO-DIGITAL CONVERTER | January 2024 | July 2025 | Allow | 18 | 0 | 0 | No | No |
| 18580918 | A CIRCUIT AND A METHOD FOR SAMPLING AN ANALOG SIGNAL | January 2024 | March 2026 | Allow | 25 | 1 | 0 | No | No |
| 18415655 | DIGITAL-TO-ANALOG CONVERTER, DATA DRIVER, AND DISPLAY DEVICE | January 2024 | December 2025 | Allow | 23 | 1 | 0 | No | No |
| 18413042 | SYSTEM AND METHOD FOR EXTRACTING DATA FROM A COMPRESSED AND ENCRYPTED DATA STREAM | January 2024 | March 2024 | Allow | 2 | 0 | 0 | No | No |
| 18410980 | SYSTEM AND METHODS FOR UPSAMPLING OF DECOMPRESSED TIME-SERIES DATA USING A NEURAL NETWORK | January 2024 | April 2024 | Allow | 3 | 0 | 0 | No | No |
| 18402964 | SIGMA-DELTA ANALOG-TO-DIGITAL CONVERTER AND METHOD FOR CONVERTING AN ANALOG INPUT SIGNAL TO A DIGITAL OUTPUT SIGNAL AT A SAMPLING FREQUENCY | January 2024 | December 2025 | Allow | 23 | 1 | 0 | Yes | No |
| 18399455 | DATA COMPRESSION METHOD AND APPARATUS, AND DATA DECOMPRESSION METHOD AND APPARATUS | December 2023 | February 2026 | Allow | 26 | 1 | 0 | No | No |
| 18392309 | DATA COMPRESSION DEVICE, DATA COMPRESSION METHOD, AND RECORDING MEDIUM | December 2023 | August 2025 | Allow | 20 | 0 | 0 | No | No |
| 18544916 | INTERPOLATION BETWEEN LOG AND ONE-HOT ENCODINGS | December 2023 | March 2026 | Allow | 27 | 1 | 0 | No | No |
| 18541025 | A COMPRESSION METHOD FOR QUBOS AND ISING MODELS | December 2023 | February 2026 | Allow | 26 | 1 | 0 | No | No |
| 18536057 | CONVERSION DEVICE, MEMORY SYSTEM, DECOMPRESSION DEVICE, AND METHOD | December 2023 | September 2025 | Allow | 21 | 0 | 0 | No | No |
| 18528023 | ARTIFICIAL INTELLIGENCE LAYER-BASED PROCESS EXTRACTION FOR ROBOTIC PROCESS AUTOMATION | December 2023 | August 2024 | Allow | 9 | 1 | 0 | No | No |
| 18521725 | METHODS, SYSTEMS, AND APPARATUSES FOR REDUCING DC BIAS | November 2023 | November 2025 | Allow | 24 | 1 | 0 | No | No |
| 18522178 | SYSTEM AND METHOD FOR DATA COMPRESSION WITH HOMOMORPHIC ENCRYPTION | November 2023 | February 2024 | Allow | 3 | 0 | 0 | No | No |
| 18521839 | TEMPORAL RESOLUTION AND FIDELITY ENHANCEMENT OF ARBITRARY WAVEFORMS | November 2023 | November 2024 | Allow | 12 | 2 | 0 | No | No |
| 18518517 | Multi-shot Time-to-Digital Converter and time-measurement device | November 2023 | July 2025 | Allow | 20 | 0 | 0 | No | No |
| 18387242 | TIME-TO-DIGITAL CONVERTER USING VOLTAGE AS A REPRESENTATION OF TIME OFFSET | November 2023 | December 2024 | Allow | 14 | 1 | 0 | No | No |
| 18501987 | SYSTEM AND METHOD FOR DATA COMPRESSION WITH PROTOCOL ADAPTATION | November 2023 | December 2023 | Allow | 1 | 0 | 0 | No | No |
| 18386710 | CONVERTING A DIGITAL SIGNAL FROM A FIRST SAMPLING RATE TO A SECOND SAMPLING RATE | November 2023 | July 2025 | Allow | 20 | 0 | 0 | No | No |
| 18500419 | Lossless Binary Data Compression | November 2023 | December 2025 | Allow | 25 | 1 | 0 | Yes | No |
| 18497605 | SYSTEM AND METHOD FOR PERFORMING ADAPTIVE VOLTAGE SCALING (AVS) FOR ANALOG-TO-DIGITAL CONVERTERS (ADCS) | October 2023 | October 2025 | Allow | 24 | 1 | 0 | Yes | No |
| 18496436 | ADC ARCHITECTURE INCORPORATING CONTINUOUS-TIME QUANTIZER | October 2023 | March 2026 | Allow | 28 | 1 | 0 | No | No |
| 18494541 | HIGH FREQUENCY, LOW POWER, N-PATH SIGMA-DELTA MODULATOR | October 2023 | November 2025 | Allow | 25 | 1 | 0 | No | No |
| 18383847 | METHODS AND SYSTEMS FOR SIGNAL SAMPLING USING SPATIAL DISPERSION | October 2023 | October 2025 | Allow | 24 | 1 | 0 | Yes | No |
| 18381793 | Device and method for ratiometric measurement of voltages for an analog-digital-converter | October 2023 | March 2026 | Allow | 29 | 2 | 0 | Yes | No |
| 18488275 | TEXT COMPRESSION WITH PREDICTED CONTINUATIONS | October 2023 | December 2024 | Allow | 14 | 1 | 0 | No | No |
| 18481416 | DECODING APPARATUS, DECODING METHOD, AND PROGRAM | October 2023 | September 2024 | Allow | 11 | 1 | 0 | No | No |
| 18471437 | SUCCESSIVE APPROXIMATION ANALOG-TO-DIGITAL CONVERSION DEVICE SKIPPING COMPARISON RESULTS AND ITS OPERATING METHOD | September 2023 | October 2025 | Allow | 25 | 1 | 0 | No | No |
| 18472069 | APPARATUS, SENSOR AND ELECTRONIC DEVICE | September 2023 | October 2025 | Allow | 25 | 1 | 0 | Yes | No |
| 18471178 | DATA COMPRESSION VIA BINARY SUBSTITUTION | September 2023 | August 2024 | Allow | 11 | 1 | 0 | No | No |
| 18370052 | CIRCUIT ARRANGEMENT COMPRISING A MOS SENSOR, IN PARTICULAR TMOS SENSOR, AND A CORRESPONDING METHOD FOR OPERATING THE CIRCUIT ARRANGEMENT | September 2023 | September 2025 | Allow | 24 | 1 | 0 | No | No |
| 18470373 | DIGITAL-TO-ANALOG CONVERSION CIRCUIT, DATA DRIVER, AND DISPLAY DEVICE | September 2023 | September 2025 | Allow | 24 | 1 | 0 | No | No |
| 18469040 | Method of Fabricating an Antenna Having a Substrate Configured to Facilitate Through-Metal Energy Transfer Via Near Field Magnetic Coupling | September 2023 | June 2024 | Allow | 9 | 0 | 0 | No | No |
| 18467157 | SYSTEM AND METHOD FOR OFF-CHIP DATA COMPRESSION AND DECOMPRESSION FOR MACHINE LEARNING NETWORKS | September 2023 | December 2025 | Allow | 27 | 2 | 0 | No | No |
| 18466027 | GATED RING OSCILLATOR LINEARIZATION | September 2023 | January 2025 | Allow | 16 | 1 | 0 | No | No |
| 18466046 | Bootstrap Circuit with Boosted Impedance | September 2023 | June 2024 | Allow | 9 | 1 | 0 | Yes | No |
| 18465495 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO DECODE ZERO-VALUE-COMPRESSION DATA VECTORS | September 2023 | May 2025 | Allow | 20 | 0 | 0 | No | No |
| 18463143 | GRAPH-BASED COMPRESSION OF DATA RECORDS | September 2023 | July 2024 | Allow | 11 | 1 | 0 | No | No |
| 18461152 | AUXILIARY ADC-BASED CALIBRATION FOR NON-LINEARITY CORRECTION OF ADC | September 2023 | July 2024 | Allow | 11 | 1 | 0 | No | No |
| 18279425 | 9B/10B ENCODING AND DECODING METHOD | August 2023 | May 2025 | Allow | 21 | 0 | 0 | No | No |
| 18455291 | SIGMA-DELTA ANALOGUE TO DIGITAL CONVERTER | August 2023 | May 2025 | Allow | 21 | 0 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner JEANGLAUDE, JEAN BRUNER.
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.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner JEANGLAUDE, JEAN BRUNER works in Art Unit 2845 and has examined 1,118 patent applications in our dataset. With an allowance rate of 96.9%, this examiner allows applications at a higher rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 12 months.
Examiner JEANGLAUDE, JEAN BRUNER's allowance rate of 96.9% places them in the 87% percentile among all USPTO examiners. This examiner is more likely to allow applications than most examiners at the USPTO.
On average, applications examined by JEANGLAUDE, JEAN BRUNER receive 0.71 office actions before reaching final disposition. This places the examiner in the 4% percentile for office actions issued. This examiner issues significantly fewer office actions than most examiners.
The median time to disposition (half-life) for applications examined by JEANGLAUDE, JEAN BRUNER is 12 months. This places the examiner in the 100% percentile for prosecution speed. Applications move through prosecution relatively quickly with this examiner.
Conducting an examiner interview provides a +3.6% benefit to allowance rate for applications examined by JEANGLAUDE, JEAN BRUNER. This interview benefit is in the 26% percentile among all examiners. Recommendation: Interviews provide a below-average benefit with this examiner.
When applicants file an RCE with this examiner, 41.5% of applications are subsequently allowed. This success rate is in the 93% 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 71.7% of cases where such amendments are filed. This entry rate is in the 93% percentile among all examiners. Strategic Recommendation: This examiner is highly receptive to after-final amendments compared to other examiners. Per MPEP § 714.12, after-final amendments may be entered "under justifiable circumstances." Consider filing after-final amendments with a clear showing of allowability rather than immediately filing an RCE, as this examiner frequently enters such amendments.
When applicants request a pre-appeal conference (PAC) with this examiner, 200.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 96% percentile among all examiners. Strategic Recommendation: Pre-appeal conferences are highly effective with this examiner compared to others. Before filing a full appeal brief, strongly consider requesting a PAC. The PAC provides an opportunity for the examiner and supervisory personnel to reconsider the rejection before the case proceeds to the PTAB.
This examiner withdraws rejections or reopens prosecution in 100.0% of appeals filed. This is in the 93% percentile among all examiners. Of these withdrawals, 50.0% occur early in the appeal process (after Notice of Appeal but before Appeal Brief). Strategic Insight: This examiner frequently reconsiders rejections during the appeal process compared to other examiners. Per MPEP § 1207.01, all appeals must go through a mandatory appeal conference. Filing a Notice of Appeal may prompt favorable reconsideration even before you file an Appeal Brief.
When applicants file petitions regarding this examiner's actions, 28.7% are granted (fully or in part). This grant rate is in the 16% 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 1.7% of allowed cases (in the 73% 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 31.9% of allowed cases (in the 96% percentile). Per MPEP § 714.14, a Quayle action indicates that all claims are allowable but formal matters remain. This examiner frequently uses Quayle actions compared to other examiners, which is a positive indicator that once substantive issues are resolved, allowance follows quickly.
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.