USPTO Examiner KIM SEHWAN - Art Unit 2129

Recent Applications

Detailed information about the 100 most recent patent applications.

Application NumberTitleFiling DateDisposal DateDispositionTime (months)Office ActionsRestrictionsInterviewAppeal
18783409DATA MODIFICATION OPERATORS FOR REDUCING BIAS IN MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE MODELSJuly 2024November 2025Allow1530YesNo
18651384AUGMENTING MACHINE LEARNING LANGUAGE MODELS USING SEARCH ENGINE RESULTSApril 2024February 2025Allow1000YesNo
18605337Generative Artificial Intelligence Model Prompt Injection ClassifierMarch 2024January 2025Allow1020YesNo
18385559AUTOMATED COMPREHENSION AND INTEREST-BASED OPTIMIZATION OF CONTENTOctober 2023October 2024Allow1210YesNo
18497924NEURAL PROGRAMMINGOctober 2023November 2024Allow1310YesNo
18358823AUTOMATED DETECTION OF CONTENT GENERATED BY ARTIFICIAL INTELLIGENCEJuly 2023January 2025Allow1840YesNo
18259682Network Model Training Method and Apparatus, Electronic Apparatus and Computer-readable Storage MediumJune 2023February 2025Allow1920YesNo
18268465System, Method, and Computer Program Product for Multi-Domain Ensemble Learning Based on Multivariate Time Sequence DataJune 2023May 2024Allow1110YesNo
18300707METHODS AND APPARATUS FOR TIME-SERIES FORECASTING USING DEEP LEARNING MODELS OF A DEEP BELIEF NETWORK WITH QUANTUM COMPUTINGApril 2023September 2025Allow2941YesNo
18131831MODEL SELECTION IN ENSEMBLE LEARNINGApril 2023February 2025Abandon2340YesNo
18104210AUGMENTING MACHINE LEARNING LANGUAGE MODELS USING SEARCH ENGINE RESULTSJanuary 2023January 2024Allow1220YesNo
18081242MACHINE LEARNING TECHNIQUES FOR VALIDATING AND MUTATING OUTPUTS FROM PREDICTIVE SYSTEMSDecember 2022September 2025Allow3300YesNo
18000845AUTOMATED ELECTRIC SUBMERSIBLE PUMP (ESP) FAILURE ANALYSISDecember 2022February 2026Allow3810YesNo
17979486INTERACTIVE QUALITATIVE-QUANTITATIVE LIVE LABELING FOR DEEP LEARNING ARTIFICIAL INTELLIGENCENovember 2022September 2024Allow2230YesNo
17899124PREDICTIVE FOG DATA CENTER MIGRATIONAugust 2022February 2026Allow4110YesNo
17876451EVALUATING OUTPUT SEQUENCES USING AN AUTO-REGRESSIVE LANGUAGE MODEL NEURAL NETWORKJuly 2022May 2024Allow2130YesNo
17869780CROSS-HIERARCHICAL MACHINE LEARNING PREDICTIONJuly 2022August 2025Allow3730YesYes
17649791Motion Compensation and Refinement in Recurrent Neural NetworksFebruary 2022October 2025Abandon4410NoNo
17362997HARDWARE AND NEURAL ARCHITECTURE CO-SEARCHJune 2021August 2022Allow1330YesNo
17358891APPARATUSES, COMPUTER-IMPLEMENTED METHODS, AND COMPUTER PROGRAM PRODUCTS FOR IMPROVED GLOBAL QUBIT POSITIONING IN A QUANTUM COMPUTING ENVIRONMENTJune 2021November 2025Allow5310YesNo
17293458TRAINING DEVICE, METHOD AND PROGRAMMay 2021October 2025Abandon5310NoNo
17286982ELECTRONIC DEVICE AND CONTROL METHOD THEREFORApril 2021November 2024Allow4320YesNo
17280184CLASSIFICATION DEVICE, CLASSIFICATION METHOD, AND CLASSIFICATION PROGRAMMarch 2021September 2025Abandon5310NoNo
17275981METHOD FOR DETECTING ANOMALIES IN A DATA SETMarch 2021October 2025Abandon5640YesNo
17197677METHOD AND APPARATUS FOR QUANTIZING NEURAL NETWORK MODEL IN DEVICEMarch 2021November 2025Abandon5640YesNo
17196626SYSTEM AND METHOD FOR DETECTION OF IMPAIRMENT IN COGNITIVE FUNCTIONMarch 2021December 2024Allow4510YesNo
17182053TRAINING TREE-BASED MACHINE-LEARNING MODELING ALGORITHMS FOR PREDICTING OUTPUTS AND GENERATING EXPLANATORY DATAFebruary 2021February 2025Allow4810YesNo
17165226INTELLIGENT DATA CURATIONFebruary 2021January 2022Allow1220YesNo
17160606SYSTEMS AND METHODS FOR EVALUATING TEMPORAL DEPENDENCY TREESJanuary 2021September 2021Allow710YesNo
17127908MACHINE LEARNING MODEL FOR ANALYSIS OF INSTRUCTION SEQUENCESDecember 2020August 2023Allow3210YesNo
17116724METHOD, APPARATUS, AND SYSTEM FOR PROVIDING PLACE CATEGORY PREDICTIONDecember 2020November 2024Abandon4720NoNo
17098007Systems and Methods for Out-of-Distribution DetectionNovember 2020November 2025Allow6030YesNo
17078066BRAIN OPERATING SYSTEM INFRASTRUCTUREOctober 2020October 2025Abandon5920NoYes
17071482Computer SystemOctober 2020December 2024Abandon5020NoNo
17069794SYSTEMS AND METHODS FOR ARTIFICIAL INTELLIGENCE DISCOVERED CODESOctober 2020September 2022Allow2340YesNo
17067753METHOD OF JUDGING RELIABILITY OF DEEP LEARNING MACHINEOctober 2020November 2022Abandon2520YesNo
17046492DECISION-MAKING DEVICE, UNMANNED SYSTEM, DECISION-MAKING METHOD, AND PROGRAMOctober 2020March 2026Allow6040YesYes
17063606MODEL SELECTION FOR PRODUCTION SYSTEM VIA AUTOMATED ONLINE EXPERIMENTSOctober 2020December 2024Allow5120YesNo
17027241PERSON RE-IDENTIFICATION METHOD COMBINING REVERSE ATTENTION AND MULTI-SCALE DEEP SUPERVISIONSeptember 2020March 2022Abandon1820NoNo
17025759HYPER-PARAMETER TUNING METHOD FOR MACHINE LEARNING ALGORITHMS USING PATTERN RECOGNITION AND REDUCED SEARCH SPACE APPROACHSeptember 2020September 2024Abandon4810YesNo
16980592Low Overhead Quantum Computation Using Lattice SurgerySeptember 2020June 2025Allow5721YesNo
16988232SYSTEMS AND METHODS FOR EMBEDDING PROBLEMS INTO AN ANALOG PROCESSORAugust 2020September 2023Allow3710YesNo
16968347EVALUATION DEVICEAugust 2020March 2025Abandon5530YesNo
16987808DISPLAYING CONTEXTUAL INFORMATION OF MEDIAAugust 2020May 2025Allow5740YesNo
16938402SUBGRAPH GUIDED KNOWLEDGE GRAPH QUESTION GENERATIONJuly 2020October 2025Abandon6040YesNo
16928474ANOMALY DETECTION IN NETWORK TOPOLOGYJuly 2020September 2024Allow5020YesNo
16918484UNSUPERVISED CONCEPT DISCOVERY AND CROSS-MODAL RETRIEVAL IN TIME SERIES AND TEXT COMMENTS BASED ON CANONICAL CORRELATION ANALYSISJuly 2020March 2024Abandon4520YesNo
16908499PREDICTIVE ANALYTIC METHOD FOR PATTERN AND TREND RECOGNITION IN DATASETSJune 2020July 2024Abandon4910NoNo
16889695GBDT MODEL FEATURE INTERPRETATION METHOD AND APPARATUSJune 2020August 2021Allow1420YesNo
16859811NEURAL PROGRAMMINGApril 2020June 2023Allow3720YesNo
16747076WINOGRAD TRANSFORM CONVOLUTION OPERATIONS FOR NEURAL NETWORKSJanuary 2020December 2024Abandon5940YesNo
16632328METHODS, SYSTEMS AND NON-TRANSITORY COMPUTER READABLE MEDIA FOR AUTOMATED DESIGN OF MOLECULES WITH DESIRED PROPERTIES USING ARTIFICIAL INTELLIGENCEJanuary 2020June 2025Allow6040YesNo
16744824DUAL CAPACITOR MIXED SIGNAL MUTIPLIERJanuary 2020August 2024Allow5520YesNo
16744327UPDATE OF ATTENUATION COEFFICIENT FOR A MODEL CORRESPONDING TO TIME-SERIES INPUT DATAJanuary 2020May 2022Allow2810YesNo
16741824MACHINE LEARNING MODEL VALIDATION AND AUTHENTICATIONJanuary 2020June 2024Allow5320YesNo
16731854Hierarchy Optimization Method for Machine LearningDecember 2019October 2023Allow4520YesNo
16570284DEEP NEURAL NETWORK BASED USER SEGMENTATIONSeptember 2019January 2024Allow5310YesNo
16527755LEARNING DEVICE AND LEARNING METHODJuly 2019May 2024Allow5720YesNo
16525777RETRIEVAL OF FREQUENCY ASKED QUESTIONS USING ATTENTIVE MATCHINGJuly 2019May 2023Allow4530YesNo
16515521METHOD FOR INTEGRATING PREDICTION RESULTJuly 2019May 2022Abandon3420YesNo
16457884DECISION TREE TRAINING USING A DATABASE SYSTEMJune 2019May 2025Allow6080YesNo
16453380Dataset Dependent Low Rank Decomposition Of Neural NetworksJune 2019October 2025Allow6070YesNo
16417600PREDICTING THE DISASTER RECOVERY INVOCATION RESPONSE TIMEMay 2019February 2023Allow4540YesNo
16462196METHODS AND SYSTEMS FOR ENGINEERING COLLAGENMay 2019December 2023Abandon5550YesNo
16373913METHOD AND APPARATUS FOR STOCHASTIC INFERENCE BETWEEN MULTIPLE RANDOM VARIABLES VIA COMMON REPRESENTATIONApril 2019November 2022Allow4440YesNo
16374738METHODS AND DEVICES FOR OPTIMIZING MACHINE LEARNING MODEL COMPACTNESS AND ACCURACY THROUGH HARDWARE LATENCY HYSTERESIS EFFECTApril 2019January 2024Abandon5720YesNo
16358701METHOD FOR EXECUTING ACTIVATION FUNCTION FOR DEEP LEARNING ALGORITHM, AND APPARATUS FOR EXECUTING SAID METHODMarch 2019December 2022Abandon4520NoNo
16352587FAILED AND CENSORED INSTANCES BASED REMAINING USEFUL LIFE (RUL) ESTIMATION OF ENTITIESMarch 2019December 2022Allow4520YesNo
16299225DEEP FOREST MODEL DEVELOPMENT AND TRAININGMarch 2019November 2023Allow5740YesNo
16280292FAULT DIAGNOSIS APPARATUS AND MACHINE LEARNING DEVICEFebruary 2019November 2023Abandon5750YesNo
16269639METHOD FOR ADJUSTING TREATMENT BY USING ADJUSTED CONTINUOUS VARIABLES AND METHOD AND APPARATUS FOR ADJUSTING TREATMENT BY ANALYZING CORRELATIONS USING THE SAMEFebruary 2019February 2023Allow4830YesNo
16266806AVOIDING DEAD ENDS IN REAL-TIME HEURISTIC SEARCHFebruary 2019May 2024Abandon6030YesNo
16260726INCREMENTAL AI FIRMWARE UPDATES USING IN-DEVICE TRAINING AND PEER-TO-PEER UPDATESJanuary 2019March 2024Abandon6050NoNo
16314374Binning for Nonlinear ModelingDecember 2018April 2023Allow5210YesNo
16226521HYBRID NEURAL NETWORK PRUNINGDecember 2018November 2024Allow6060YesNo
16310851INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND RECORDING MEDIUMDecember 2018April 2023Abandon5220YesNo
16216296UTILIZING RECURRENT NEURAL NETWORKS TO RECOGNIZE AND EXTRACT OPEN INTENT FROM TEXT INPUTSDecember 2018January 2024Allow6040YesNo
16203124METHODS OF PROCESSING AND GENERATING IMAGE DATA IN A CONNECTIONIST NETWORKNovember 2018May 2022Allow4210YesNo
16198853Automated Personalized Classification of Journey Data Captured by One or More Movement-Sensing DevicesNovember 2018October 2022Allow4720YesNo
16139386METHOD AND SYSTEM FOR SERVICE AGENT ASSISTANCE OF ARTICLE RECOMMENDATIONS TO A CUSTOMER IN AN APP SESSIONSeptember 2018September 2022Allow4820YesNo
16085315METHOD FOR DYNAMICALLY SELECTING OPTIMAL MODEL BY THREE-LAYER ASSOCIATION FOR LARGE DATA VOLUME PREDICTIONSeptember 2018February 2024Abandon6040NoNo
16033460NEURAL NETWORK MODEL FOR PREDICTING USAGE IN A HYPER-CONVERGED INFRASTRUCTUREJuly 2018May 2024Allow6040YesYes
15921737FEATURE-BASED SELECTIVE CONTROL OF A NEURAL NETWORKMarch 2018August 2022Abandon5310NoNo
15905988OPTIMIZING COMBINED SENSORY DATA BY UTILITARIAN SELECTION OF A SUBGROUP OF AVAILABLE SENSORSFebruary 2018March 2025Allow6060YesNo
15892890NEURAL NETWORK COMPRESSIONFebruary 2018December 2023Allow6030YesNo
15886109ESTABLISHING A LOGICAL CONNECTION BETWEEN AN INDIRECT UTTERANCE AND A TRANSACTIONFebruary 2018February 2024Allow6040YesNo
15843900MALWARE DETECTION AND CLASSIFICATION USING ARTIFICIAL NEURAL NETWORKDecember 2017January 2025Abandon6060YesNo
15833985LAYER-LEVEL QUANTIZATION IN NEURAL NETWORKSDecember 2017August 2023Abandon6050YesNo
15830067METHOD AND DEVICE FOR A COMPUTERIZED MECHANICAL DEVICEDecember 2017May 2022Allow5430YesNo
15830710DATA-DRIVEN GHOSTING USING DEEP IMITATION LEARNINGDecember 2017August 2024Allow6060YesNo
15804197NEURAL NETWORK COOPERATIONNovember 2017November 2022Allow6040YesNo
15715460ARTIFICIAL INTELLIGENCE DEVELOPMENT VIA USER-SELECTABLE/CONNECTABLE MODEL REPRESENTATIONSSeptember 2017March 2023Allow6040YesNo
15671829Zero Coefficient Skipping Convolution Neural Network EngineAugust 2017January 2022Abandon5310NoNo
15620926Data Processing System with Machine Learning Engine to Provide Profile Generation and Event Control FunctionsJune 2017March 2022Abandon5730YesNo
15620510METHODS AND SYSTEMS FOR DETERMINING PAST ACTIVITIES OF A USER AND TRIGGERING AN ACTION ACCORDINGLYJune 2017November 2021Abandon5320YesNo
15620400AUTOMATED COMPREHENSION AND INTEREST-BASED OPTIMIZATION OF CONTENTJune 2017July 2023Allow6050YesYes
15612777COMMUNICATION REPLY BOTJune 2017November 2023Abandon6080YesNo
15591235ENTITY MODEL ESTABLISHMENTMay 2017August 2021Allow5130YesNo
15476685COLLABORATIVE PERSONALIZATION VIA SIMULTANEOUS EMBEDDING OF USERS AND THEIR PREFERENCESMarch 2017June 2022Allow6060YesNo
15476291ENTITY RESOLUTION FOR THE INTERNET OF THINGSMarch 2017December 2021Allow5640YesNo

Appeals Overview

This analysis examines appeal outcomes and the strategic value of filing appeals for examiner KIM, SEHWAN.

Strategic Value of Filing an Appeal

Total Appeal Filings
5
Allowed After Appeal Filing
2
(40.0%)
Not Allowed After Appeal Filing
3
(60.0%)
Filing Benefit Percentile
65.4%
Higher than average

Understanding Appeal Filing Strategy

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, 40.0% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is above the USPTO average, suggesting that filing an appeal can be an effective strategy for prompting reconsideration.

Strategic Recommendations

✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.

Examiner KIM, SEHWAN - Prosecution Strategy Guide

Executive Summary

Examiner KIM, SEHWAN works in Art Unit 2129 and has examined 95 patent applications in our dataset. With an allowance rate of 62.1%, this examiner allows applications at a lower rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 55 months.

Allowance Patterns

Examiner KIM, SEHWAN's allowance rate of 62.1% places them in the 22% percentile among all USPTO examiners. This examiner is less likely to allow applications than most examiners at the USPTO.

Office Action Patterns

On average, applications examined by KIM, SEHWAN receive 3.33 office actions before reaching final disposition. This places the examiner in the 92% 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.

Prosecution Timeline

The median time to disposition (half-life) for applications examined by KIM, SEHWAN is 55 months. This places the examiner in the 2% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.

Interview Effectiveness

Conducting an examiner interview provides a +72.0% benefit to allowance rate for applications examined by KIM, SEHWAN. This interview benefit is in the 99% 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.

Request for Continued Examination (RCE) Effectiveness

When applicants file an RCE with this examiner, 20.1% of applications are subsequently allowed. This success rate is in the 22% 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.

After-Final Amendment Practice

This examiner enters after-final amendments leading to allowance in 3.3% of cases where such amendments are filed. This entry rate is in the 5% 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.

Pre-Appeal Conference Effectiveness

When applicants request a pre-appeal conference (PAC) with this examiner, 50.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 43% percentile among all examiners. Note: Pre-appeal conferences show below-average success with this examiner. Consider whether your arguments are strong enough to warrant a PAC request.

Appeal Withdrawal and Reconsideration

This examiner withdraws rejections or reopens prosecution in 100.0% of appeals filed. This is in the 89% 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 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.

Petition Practice

When applicants file petitions regarding this examiner's actions, 0.0% are granted (fully or in part). This grant rate is in the 1% 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 Cooperation and Flexibility

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 10% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.

Prosecution Strategy Recommendations

Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:

  • Prepare for rigorous examination: With a below-average allowance rate, ensure your application has strong written description and enablement support. Consider filing a continuation if you need to add new matter.
  • Expect multiple rounds of prosecution: This examiner issues more office actions than average. Address potential issues proactively in your initial response and consider requesting an interview early in prosecution.
  • Prioritize examiner interviews: Interviews are highly effective with this examiner. Request an interview after the first office action to clarify issues and potentially expedite allowance.
  • Plan for RCE after final rejection: This examiner rarely enters after-final amendments. Budget for an RCE in your prosecution strategy if you receive a final rejection.
  • Appeal filing as negotiation tool: This examiner frequently reconsiders rejections during the appeal process. Filing a Notice of Appeal may prompt favorable reconsideration during the mandatory appeal conference.
  • Plan for extended prosecution: Applications take longer than average with this examiner. Factor this into your continuation strategy and client communications.

Relevant MPEP Sections for Prosecution Strategy

  • MPEP § 713.10: Examiner interviews - available before Notice of Allowance or transfer to PTAB
  • MPEP § 714.12: After-final amendments - may be entered "under justifiable circumstances"
  • MPEP § 1002.02(c): Petitionable matters to Technology Center Director
  • MPEP § 1004: Actions requiring primary examiner signature (allowances, final rejections, examiner's answers)
  • MPEP § 1207.01: Appeal conferences - mandatory for all appeals
  • MPEP § 1214.07: Reopening prosecution after appeal

Important Disclaimer

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.