Listed by the USPTO as SACKALOSKY, COREY MATTHEW
Tech Center 3600 • Art Units: 2128 2141 2145 2148 2183 3629
This examiner grants 64% of resolved cases
SACKALOSKY, COREY MATTHEW works in tech center 3600 and art unit 2128. Across 47 resolved cases, the allowance rate is 63.8%, the interview lift is 29.7%, and the median time to allowance is 1520 days. The small record limits broad inference, while the timing figure points to a potentially extended prosecution path.
Wells Fargo Bank, N.A., Dell Products L.P., and Capital One Services LLC are the leading companies. FOLEY & LARDNER LLP, K&L Gates LLP, and BakerHostetler are the leading firms. The interview result supports considering examiner discussions, particularly where written responses alone may not efficiently resolve claim interpretation issues.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 18033668 | DYNAMIC MODEL SCOPE SELECTION FOR CONNECTED VEHICLES | Final Rejection | Telefonaktiebolaget LM Ericsson (publ) |
| 18333554 | MACHINE LEARNING METHOD, INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING APPARATUS, SERVER, AND PROGRAM | Final Rejection | FUJIFILM Corporation |
| 18357086 | SYSTEMS AND METHODS FOR FEDERATED LEARNING | Final Rejection | Capital One Services, LLC |
| 18073269 | CONTROL METHOD AND SYSTEM BASED ON LAYER-WISE ADAPTIVE CHANNEL PRUNING | Non-Final OA | SAMSUNG ELECTRONICS CO., LTD. |
| 18190745 | MACHINE LEARNING TECHNIQUES FOR PREDICTIVE MULTI-VARIATE TEMPORAL FEATURE IMPACT DETERMINATIONS | Final Rejection | Wells Fargo Bank, N.A. |
| 18184174 | SYSTEMS AND METHODS FOR GENERATING PREDICTIVE OUTCOMES FOR SCENARIOS USING GENERATIVE ARTIFICIAL INTELLIGENCE | Final Rejection | Wells Fargo Bank, N.A. |
| 18644621 | IMPROVEMENT TOOL RECOMMENDATION ENGINE | Non-Final OA | State Farm Mutual Automobile Insurance Company |
| 18099364 | SYSTEMS, APPARATUSES, METHODS, AND NON-TRANSITORY COMPUTER-READABLE STORAGE DEVICES FOR TRAINING ARTIFICIAL-INTELLIGENCE MODELS USING ADAPTIVE DATA-SAMPLING | Final Rejection | Huawei Technologies Co., Ltd. |
| 18429282 | MACHINE LEARNING FOR TABULAR DATA | Non-Final OA | Fujitsu Limited |
| 17348246 | AUTOMATICALLY AND EFFICIENTLY GENERATING SEARCH SPACES FOR NEURAL NETWORK | Non-Final OA | Lemon Inc. |
| 17731691 | METHOD AND SYSTEM FOR SPECTROSCOPIC PREDICTION OF SUBSURFACE PROPERTIES USING MACHINE LEARNING | Non-Final OA | Saudi Arabian Oil Company |
| 18430289 | MACHINE LEARNING DEVELOPMENT USING LANGUAGE MODELS | Non-Final OA | MICROSOFT TECHNOLOGY LICENSING, LLC |
| 17984350 | MACHINE LEARNING BASED CODE MAPPING | Non-Final OA | ADP, Inc. |
| 18197347 | RESOURCE FORECASTING USING ARTIFICIAL INTELLIGENCE TECHNIQUES | Final Rejection | Dell Products L.P. |
| 17814055 | EFFICIENT SAMPLING OF EDGE-WEIGHTED QUANTIZATION FOR FEDERATED LEARNING | Non-Final OA | Dell Products L.P. |
| 18844798 | TRAINING OBJECT DISCOVERY NEURAL NETWORKS AND FEATURE REPRESENTATION NEURAL NETWORKS USING SELF-SUPERVISED LEARNING | Non-Final OA | DeepMind Technologies Limited |
| 17580251 | DOMAIN BATCH BALANCING FOR TRAINING A MACHINE LEARNING ALGORITHM WITH DATA FROM MULTIPLE DATASETS | Non-Final OA | GM Cruise Holdings LLC |
IP Author analyzes examiner patterns and generates tailored response strategies with the highest chance of allowance.
Build Your Strategy63.8% of resolved applications examined by Corey Matthew Sackalosky were allowed (47 resolved cases), compared with 38.7% across Art Unit 2128 over the last five years.
This examiner's interview lift is +29.7 percentage points: the difference in allowance rate between resolved applications that had an examiner interview and those that did not.
Applications allowed by Corey Matthew Sackalosky took 1,520 days on average from filing to allowance.
Corey Matthew Sackalosky examines applications in Art Unit 2128 in Tech Center 3600 (Transportation, E-Commerce & Mechanical Systems).
